[00:00] (0.00s)
TV came out 21. Yeah. So, GPD3 came out
[00:02] (2.40s)
right after the build conference in
[00:04] (4.08s)
2020. Kevin Scott and Sam Alman did a
[00:06] (6.16s)
session about transformers and Dutch
[00:07] (7.68s)
language models. And then after that,
[00:08] (8.96s)
GP3 got into the preview and we got
[00:11] (11.28s)
access to that and through the OpenAI
[00:13] (13.12s)
Microsoft partnership and we realized
[00:15] (15.04s)
together with OpenAI that it was able to
[00:16] (16.96s)
write decent code in different
[00:18] (18.40s)
programming languages and wouldn't not
[00:20] (20.08s)
mix up the syntax between Python, OB and
[00:22] (22.56s)
JavaScript. And then OpenAI fine-tuned a
[00:24] (24.96s)
model that was called Codex that was
[00:27] (27.20s)
specific for these coding scenarios. And
[00:28] (28.96s)
so in 2020 in August we wrote a paper
[00:31] (31.36s)
with three ideas. We had text to code
[00:33] (33.36s)
code to text as in describing code and
[00:35] (35.36s)
conversational coding is what we called
[00:36] (36.72s)
it which then today is known as chat.
[00:38] (38.32s)
And those two letter scenarios didn't
[00:39] (39.92s)
work well enough. But text to code as it
[00:41] (41.92s)
prompting the model within the editor
[00:43] (43.84s)
and ultimately building autocomp
[00:45] (45.04s)
completion that worked so well that very
[00:47] (47.20s)
quickly we saw our internal hubbers
[00:49] (49.52s)
adopting the tool giving it really high
[00:51] (51.20s)
scores saying this is great. I want to
[00:52] (52.96s)
keep using this. It's not the typical
[00:54] (54.88s)
management says you have to use it and
[00:56] (56.64s)
you don't want to. But ultimately
[00:58] (58.16s)
writing in the early days 25% of the
[01:00] (60.32s)
code in those files it was enabled and
[01:02] (62.08s)
then shortly thereafter that number got
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into the 50% range or 46% I think early
[01:06] (66.40s)
2023 and so that was the early days of
[01:08] (68.96s)
copilot and then June 2021 we went into
[01:11] (71.12s)
the public preview and within a few
[01:12] (72.96s)
months this had grown to a million users
[01:14] (74.80s)
and you saw more and more folks on
[01:16] (76.32s)
social media saying well I was skeptical
[01:18] (78.16s)
that this could ever work but it
[01:19] (79.84s)
actually is good enough that I don't
[01:21] (81.12s)
want to work without it anymore. GitHub
[01:22] (82.96s)
recently turned 17 years old, but how
[01:25] (85.12s)
did it start and how did the platform
[01:26] (86.96s)
evolve? I sat down with GitHub CEO
[01:29] (89.28s)
Thomas Dunca, who has been a GitHub user
[01:31] (91.28s)
for 16 years, has been working at GitHub
[01:33] (93.52s)
for 7 years, and has been the CEO of the
[01:35] (95.52s)
company for the last 4 years since 2021.
[01:38] (98.48s)
In today's episode, we discuss GitHub's
[01:40] (100.88s)
remote first and async first engineering
[01:42] (102.56s)
culture and why the company barely uses
[01:44] (104.80s)
email. Why GitHub seemingly stopped
[01:46] (106.80s)
shipping features between 2015 and 2020
[01:49] (109.44s)
and how they created GitHub copilot in
[01:51] (111.44s)
2021. GitHub's interesting internal
[01:54] (114.16s)
tools in the early days like hastack,
[01:56] (116.08s)
GitHub TV, and Hul. How GitHub sees
[01:58] (118.80s)
about 10 billion API requests per day.
[02:01] (121.12s)
That's about 120,000 per second. and why
[02:03] (123.92s)
Thomas doesn't believe that autonomous
[02:05] (125.60s)
AI tools would solve hard engineering
[02:07] (127.76s)
challenges and many more topics. If
[02:10] (130.56s)
you're interested in the past, present,
[02:12] (132.00s)
or future of a high growth company like
[02:13] (133.68s)
GitHub, this episode is for you. If you
[02:16] (136.40s)
enjoy the show, please subscribe to the
[02:17] (137.76s)
podcast on any podcast platform and on
[02:19] (139.76s)
YouTube. So, Thomas, welcome to the
[02:22] (142.40s)
podcast. Thank you so much for having
[02:23] (143.84s)
me. It's great to meet in person after
[02:26] (146.56s)
exchanging emails and putting a name to
[02:28] (148.72s)
the face and reading your newsletter
[02:30] (150.56s)
every week. Yeah, twice a week, I guess.
[02:33] (153.68s)
I appreciate that. That's where
[02:34] (154.96s)
interaction started. Before we jump into
[02:36] (156.64s)
the history, I just wanted to go through
[02:38] (158.32s)
a couple of like just interesting things
[02:40] (160.32s)
that people might or might not know
[02:42] (162.16s)
about GitHub. Number one is a tech
[02:44] (164.16s)
stack. It is pretty commonly known or it
[02:46] (166.64s)
used to be that this was Ruby on Rails
[02:48] (168.88s)
monolith. At some point it might have
[02:50] (170.40s)
been the biggest in the world and then I
[02:51] (171.92s)
think you know Shopify might might have
[02:53] (173.84s)
come but today is it still a Ruby on
[02:56] (176.96s)
Rails monolith or have things changed?
[02:59] (179.04s)
It's still Ruby on Rails and I think
[03:00] (180.88s)
it's still one of the largest Ruby on
[03:02] (182.80s)
Rails applications. The other one you
[03:04] (184.48s)
didn't mention was Twitter was in the
[03:06] (186.32s)
early days also Ruby. I think all three
[03:09] (189.12s)
companies in one form or another have
[03:11] (191.68s)
somewhat moved away from this being the
[03:14] (194.08s)
only part of the stack. So we still have
[03:15] (195.60s)
a large monolith um with about um 700 uh
[03:19] (199.04s)
engineers in the within the company
[03:21] (201.04s)
contributing to it, you know, at
[03:22] (202.64s)
different times of of the year. Not all
[03:24] (204.96s)
of them are working constantly in the
[03:26] (206.24s)
monolith. um we actually just passed um
[03:28] (208.16s)
two million git commits into the
[03:30] (210.40s)
monolith and you know tens of thousands
[03:32] (212.00s)
of of pull requests and um but we also
[03:34] (214.40s)
have moved um uh beyond just just that
[03:37] (217.36s)
one architecture. Um so for example
[03:39] (219.20s)
we're using more and more react uh on
[03:41] (221.52s)
the front end. Uh we have a number of
[03:43] (223.60s)
you know services that outside the
[03:45] (225.28s)
monolith. Um for example the copilot API
[03:47] (227.68s)
is written in go given it needs you know
[03:50] (230.40s)
lots of API calls for inference. The G
[03:52] (232.80s)
actions uh sits on a completely
[03:54] (234.48s)
different tech stack. um kind of
[03:56] (236.00s)
actions. Um I I would imagine Rails
[03:58] (238.24s)
might not be the best for a very heavy
[04:00] (240.16s)
workflow. And it has a it has actually a
[04:02] (242.48s)
um history um because uh a large part of
[04:04] (244.96s)
the action stack um came from what was
[04:07] (247.52s)
back then Visual Studio Team Services
[04:09] (249.84s)
and then became Azure DevOps and so
[04:11] (251.76s)
Azure pipelines um and so there was a
[04:13] (253.92s)
lot of net code uh in that code base and
[04:16] (256.40s)
and over time we are now evolving that
[04:18] (258.96s)
into into a more more modern
[04:20] (260.40s)
architecture with the goal of you know
[04:22] (262.16s)
one of your other posts of getting to
[04:24] (264.08s)
49s and beyond and so our text is is
[04:27] (267.52s)
very diverse today obviously we're doing
[04:29] (269.04s)
also swift um for iPhone app we have
[04:31] (271.12s)
cotlin for Android app um we using you
[04:34] (274.16s)
know all the clouds um u beyond um also
[04:37] (277.44s)
having our own uh metal in uh commercial
[04:40] (280.16s)
data centers and we like a modern um
[04:43] (283.04s)
modern software company with all the
[04:44] (284.96s)
complexity and all the challenges that
[04:46] (286.48s)
that everybody else has as well and I
[04:48] (288.40s)
guess all the not simple trade-offs for
[04:50] (290.32s)
example it's easy to point you know the
[04:52] (292.00s)
community loves to say Rails does not
[04:53] (293.68s)
scale or why would you do it but I mean
[04:55] (295.60s)
you are one example obviously there's
[04:57] (297.12s)
other companies we mentioned that it
[04:58] (298.48s)
feels like it's less about the
[04:59] (299.84s)
technology itself but what you're
[05:01] (301.84s)
building on it and you know your history
[05:03] (303.76s)
of it and then I mean we can spend a
[05:05] (305.68s)
whole hour probably just talking about
[05:07] (307.36s)
the benefits of having a mono monor repo
[05:10] (310.56s)
with a monolith versus you know hundreds
[05:13] (313.36s)
of microservices. Um you know when
[05:15] (315.44s)
GitHub was uh in 2007 was founded for I
[05:18] (318.72s)
think more than a year it was only the
[05:20] (320.32s)
three original founders um Chris PJ and
[05:22] (322.72s)
and Tom plus the Scott um who's now the
[05:26] (326.96s)
uh founder of Git Butler and um Scott
[05:29] (329.36s)
Sha who's kind of like the first
[05:30] (330.96s)
employee but was often seen as as the
[05:32] (332.72s)
fourth founder and so you know a team of
[05:34] (334.80s)
four is way better off of working in a
[05:36] (336.88s)
single codebase. Uh you can move much
[05:39] (339.44s)
faster. I think that was always um uh
[05:42] (342.24s)
important for GitHub to be able to move
[05:44] (344.16s)
really fast and and ship new features
[05:45] (345.92s)
and it's much easier to you know get to
[05:47] (347.36s)
learn the codebase and and try to
[05:49] (349.04s)
understand the dependencies. Uh as as
[05:51] (351.52s)
the company scales and the product
[05:52] (352.88s)
scales uh it it makes more sense to move
[05:54] (354.80s)
away from that architecture. I I'm I'm
[05:56] (356.80s)
so glad you're you're saying this. The
[05:58] (358.08s)
other day I was talking with an early
[05:59] (359.36s)
Amazon employee and he was saying the
[06:00] (360.64s)
same thing how early Amazon it made
[06:02] (362.24s)
sense and then as you grow you know you
[06:04] (364.00s)
figure out your trade-offs. If you want
[06:05] (365.60s)
to build a great product you have to
[06:07] (367.20s)
ship quickly. But how do you know what
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works? More importantly, how do you
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avoid shipping things that don't work?
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techchnology.dev/pragmatic.
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Now you mentioned something really
[08:07] (487.92s)
interesting which I also heard that you
[08:09] (489.92s)
run your own data centers or
[08:11] (491.20s)
historically have run your own data
[08:12] (492.40s)
centers but I talked with some current
[08:13] (493.76s)
GitHub folks and they said that you in
[08:15] (495.84s)
in some parts still do. So why did you
[08:18] (498.00s)
do this? uh how is it changing and and
[08:20] (500.72s)
are you obviously since you're now part
[08:22] (502.56s)
of Microsoft as well does it make sense
[08:24] (504.40s)
to use some parts of Azure and and if so
[08:26] (506.56s)
what parts are using and you also
[08:27] (507.76s)
mentioned other cloud so like how are
[08:29] (509.20s)
you thinking of own data center which
[08:30] (510.72s)
again we used to say oh it's just move
[08:33] (513.36s)
to the cloud and there's there's own
[08:34] (514.64s)
opposite thinking as well what's your
[08:36] (516.48s)
take on this get up you know started on
[08:38] (518.56s)
uh on the on the cloud um really early
[08:41] (521.12s)
days it was um to my memory uh it was
[08:44] (524.56s)
engineered uh as a platform as a service
[08:47] (527.36s)
provider and then AWS Yes. Um behind the
[08:49] (529.76s)
scenes and okay, you know it's it's easy
[08:52] (532.40s)
to forget in today's world where lots of
[08:54] (534.88s)
startups announce huge funding rounds,
[08:56] (536.72s)
GitHub had no funding until um I think 5
[09:00] (540.24s)
years into its journey um when the back
[09:02] (542.88s)
then unheard of 100 million uh came came
[09:05] (545.92s)
from around led by Andre Howitz. But
[09:07] (547.76s)
until that point in time, GitHub was
[09:09] (549.28s)
bootstrapped and it had very fast
[09:11] (551.60s)
adoption. you know when um when it
[09:13] (553.68s)
launched in April 2008 very quickly uh
[09:16] (556.32s)
the number of users number of both
[09:18] (558.00s)
public and private repositories uh kept
[09:20] (560.48s)
kept growing you can still find you know
[09:22] (562.48s)
people um talking about that they're
[09:24] (564.32s)
begging the founders to introduce a paid
[09:26] (566.32s)
tier so they have the confidence that
[09:28] (568.40s)
the company can be will be around and
[09:31] (571.76s)
and so it was a natural business
[09:33] (573.28s)
decision um for the founders to say how
[09:35] (575.76s)
can we host this with more optimized
[09:38] (578.32s)
cost um given that we are bootstrapping
[09:40] (580.40s)
this and we're having to pay for the
[09:41] (581.84s)
service uh from our own uh revenue
[09:44] (584.48s)
stream and we they couldn't be burning
[09:46] (586.64s)
money because they had you know they had
[09:48] (588.16s)
no money um from from venture
[09:50] (590.08s)
capitalists and so I think that was part
[09:51] (591.92s)
of daring the decision. The other one is
[09:53] (593.36s)
you know storing git data um what we
[09:55] (595.92s)
call today our git systems uh team uh uh
[09:59] (599.20s)
in file storage in itself is probably
[10:01] (601.60s)
not like the best use case for cloud
[10:04] (604.00s)
cloudives that existed you know in 2008
[10:06] (606.56s)
2009 uh where you had limited access um
[10:09] (609.36s)
to to that layer and where you know
[10:12] (612.00s)
especially the networking part of having
[10:13] (613.92s)
multiple you know nodes um communicating
[10:16] (616.08s)
with each other was much more complex
[10:17] (617.68s)
than it is today and so the decision was
[10:19] (619.20s)
made to move to servers in commercial
[10:22] (622.40s)
data center. So we own the servers. We
[10:24] (624.08s)
still own you know the servers and the
[10:25] (625.36s)
racks and and the storage and all that.
[10:26] (626.80s)
But the data center is a commercial data
[10:28] (628.16s)
center. So we don't own the data center.
[10:29] (629.92s)
So it's own in the sense of I'm making
[10:31] (631.92s)
air quotes for listeners is own in the
[10:33] (633.52s)
sense of we managed you know the servers
[10:35] (635.36s)
in those data centers. Now today's
[10:37] (637.12s)
GitHub still is a lot of that. the core
[10:39] (639.44s)
is in in these uh own data centers but
[10:42] (642.08s)
things like GitHub actions, GitHub code
[10:43] (643.76s)
spaces, GitHub copilot uh uh run on on
[10:46] (646.64s)
Azure in the cloud and leverage the
[10:48] (648.64s)
scale that you naturally need whether
[10:50] (650.32s)
it's you know CPUs and actions um or
[10:53] (653.12s)
GPUs uh in copilot of course copilot
[10:55] (655.76s)
given it's multimodel choice and has
[10:57] (657.92s)
anic models and openi models and gemini
[11:00] (660.40s)
models not all of these models are on
[11:02] (662.16s)
Azure so naturally we're also working
[11:04] (664.88s)
um often with both you know the first
[11:07] (667.04s)
party API um aka API that OpenAI or
[11:09] (669.84s)
Anthropic provide and you know other
[11:11] (671.84s)
clouds that um that have Vertex Bedrock
[11:14] (674.56s)
and so on and we in fact now have GitHub
[11:17] (677.12s)
um fully hosted on Azure for data
[11:19] (679.12s)
residencies. If you as an enterprise uh
[11:21] (681.84s)
customer in Europe want your data all
[11:23] (683.68s)
stored in Europe, you're getting a big
[11:25] (685.76s)
deal. You're getting a GitHub
[11:26] (686.80s)
organization on a stamp that fully runs
[11:29] (689.04s)
on Azure in the Netherlands and in
[11:31] (691.60s)
Sweden. Uh I mean we have the same for
[11:33] (693.04s)
Australia have just announced a US stem
[11:35] (695.52s)
that will be fed compliant and we're
[11:37] (697.76s)
going to expand into into more regions
[11:40] (700.40s)
in in the years to come. Yeah. I feel
[11:42] (702.00s)
these are the like really kind of boring
[11:43] (703.68s)
things but they're they start to become
[11:45] (705.52s)
really important when you are at a
[11:47] (707.36s)
company that you know is now starting to
[11:48] (708.88s)
care about these things. Well and
[11:50] (710.08s)
they're not boring from an perspective.
[11:51] (711.84s)
Well, not not not boring, but like it's
[11:54] (714.08s)
it's the thing that I think as a from
[11:56] (716.08s)
outside, you know, it's it's not the
[11:57] (717.76s)
shiny features, but I agree an
[11:59] (719.12s)
engineering perspective that actually
[12:00] (720.72s)
sounds pretty challenging. The the
[12:02] (722.64s)
challenge, you know, if you go back to
[12:04] (724.72s)
the rub on rails conversation is and if
[12:06] (726.64s)
you know a little bit about rails and
[12:07] (727.92s)
how um and we not only run on rails, we
[12:10] (730.48s)
also run on my SQL and so whenever you
[12:12] (732.64s)
change, you know, the schema of a
[12:14] (734.08s)
database table, a so-called migration is
[12:16] (736.16s)
run. Um how do you do that? that if you
[12:18] (738.16s)
not only have one stamp uh in one
[12:20] (740.16s)
region, but you actually have you know
[12:21] (741.84s)
five or 10 stamps and you deploy um you
[12:25] (745.12s)
know hundreds of times per day in fact
[12:26] (746.80s)
um I think this year we're forecasting
[12:29] (749.12s)
12 million deploys um across the about a
[12:32] (752.00s)
thousand or so IC engineers that that we
[12:34] (754.08s)
have in the company and so how do you do
[12:35] (755.68s)
that how do you deploy how do you go
[12:37] (757.20s)
from one you know central stamp uh on
[12:39] (759.36s)
our US uh data center cloud if you will
[12:42] (762.56s)
to having you know deployment that goes
[12:44] (764.64s)
to all these different stamps and run
[12:46] (766.64s)
the migrations and if you need to are
[12:48] (768.80s)
able to hold back. So that was a lot of
[12:50] (770.32s)
the engineering work that went into
[12:51] (771.76s)
that. Um less so I'd say um the actual
[12:55] (775.36s)
work of moving this to Azure was was
[12:56] (776.96s)
less work than getting the engineering
[12:58] (778.56s)
system the DX the developer experience
[13:00] (780.64s)
actually aligned with this now we are
[13:02] (782.40s)
running in multiple in multiple regions.
[13:04] (784.72s)
Yeah. One interesting thing that I
[13:07] (787.20s)
always surprise people who don't know
[13:08] (788.64s)
GitHub all that well is people think
[13:10] (790.24s)
well it's now Microsoft right? So it it
[13:12] (792.32s)
must work the same way as Microsoft and
[13:14] (794.08s)
then you know one like fact that shows
[13:16] (796.56s)
this is not the case GitHub is still
[13:18] (798.08s)
remote first. It started as remote first
[13:20] (800.48s)
initially and it was actually one of the
[13:22] (802.64s)
few companies that even before co truly
[13:25] (805.20s)
remote first and as I understand even
[13:27] (807.28s)
today it's remote first. Tell me about
[13:29] (809.60s)
this on a h how you managed to keep this
[13:33] (813.12s)
how it's working inside a larger company
[13:35] (815.12s)
which you know Microsoft is not remote
[13:36] (816.96s)
first. There are I understand parts of
[13:38] (818.40s)
it that are more supportive of it but
[13:39] (819.84s)
generally you know people are often in
[13:41] (821.60s)
the office. So the pre prefounders they
[13:43] (823.60s)
actually met in San Francisco. So you
[13:45] (825.04s)
could argue that very very early phase
[13:46] (826.80s)
was was kind of like three people in a
[13:48] (828.56s)
in a same place and that's often I guess
[13:50] (830.48s)
that helps how that how that goes. Um
[13:52] (832.40s)
but yeah very quickly GitHub started
[13:53] (833.92s)
hiring uh super fans you know people
[13:56] (836.48s)
that were interested in GitHub promoting
[13:58] (838.88s)
GitHub you know helped to drive in the
[14:00] (840.56s)
community those people got hired uh into
[14:03] (843.04s)
GitHub and they were naturally
[14:04] (844.40s)
everywhere in the world and so very
[14:05] (845.92s)
quickly GitHub moved from a culture that
[14:08] (848.88s)
was headquarterentric to a remote first
[14:11] (851.36s)
culture and um that you know gave us an
[14:13] (853.92s)
advantage when uh the pandemic came uh
[14:17] (857.60s)
because we were already used on uh on
[14:19] (859.68s)
being on video calls on using Slack Um,
[14:22] (862.40s)
in fact, you know, I think GitHub is
[14:24] (864.08s)
very different than Microsoft when it
[14:26] (866.00s)
comes to how the company communicates.
[14:28] (868.16s)
My joke always is when I wake up in the
[14:29] (869.60s)
morning because I'm obviously both. I'm
[14:30] (870.88s)
a Microsoft executive and I'm a GitHub
[14:32] (872.88s)
uh employee. When I wake up in the
[14:34] (874.80s)
morning, on the GitHub side, I have lots
[14:36] (876.32s)
of Slack messages, DMs, channels to to
[14:39] (879.12s)
look at into maybe, you know, a handful
[14:41] (881.44s)
of of customer emails or or emails from
[14:43] (883.44s)
you that cannot communicate with me in
[14:45] (885.04s)
Slack. On the Microsoft side, it's the
[14:46] (886.40s)
other way around. have like dozens of of
[14:48] (888.48s)
emails to pay attention to and maybe you
[14:50] (890.80s)
know a few a few teams messages and so I
[14:53] (893.20s)
think that shows the async part of our
[14:55] (895.76s)
culture that has grown over the last um
[14:58] (898.24s)
uh 17 years and that is so important. At
[15:00] (900.64s)
GitHub uh we are using GitHub for
[15:03] (903.68s)
everything and so all employees across
[15:05] (905.76s)
all the functions not just engineering
[15:07] (907.28s)
and product but HR and coms and finance
[15:10] (910.80s)
all the functions work on GitHub and so
[15:12] (912.96s)
they have repositories to describe their
[15:14] (914.48s)
team. You know they're using pull
[15:15] (915.92s)
requests to to make changes for example
[15:17] (917.68s)
to our terms of service. Um you know
[15:20] (920.40s)
every company write announcement is a
[15:22] (922.56s)
pull request against the repository that
[15:24] (924.32s)
we call the hub that gets published as a
[15:26] (926.80s)
GitHub pages page. uh that is only
[15:29] (929.44s)
internally accessible and that goes
[15:30] (930.88s)
through our identity provider and so
[15:32] (932.72s)
even there we don't do um companywide
[15:34] (934.80s)
emails um almost never uh we do an
[15:37] (937.36s)
announcement on the hub and there's a
[15:39] (939.28s)
link that is posted in a slack channel
[15:40] (940.88s)
but then we can everybody can see and
[15:42] (942.48s)
then we take the conversation there so
[15:44] (944.40s)
yeah today we are uh a very much remote
[15:46] (946.96s)
first company um with people all around
[15:49] (949.04s)
the world in different time zones um
[15:51] (951.04s)
almost everything is async um obviously
[15:53] (953.04s)
there's you know meetings and our town
[15:55] (955.12s)
hall meeting is called the git together
[15:57] (957.36s)
and So that has to be in some you know
[15:59] (959.68s)
time zone and challenge there is that if
[16:01] (961.84s)
you do it you know uh adjusting it for
[16:05] (965.12s)
the folks in the US, North America and
[16:07] (967.60s)
uh and Europe you you're missing out
[16:09] (969.60s)
those in Australia and India because
[16:11] (971.28s)
that's just impossible to meet. So we
[16:13] (973.44s)
try, you know, different times of a year
[16:14] (974.96s)
to have one that is in the apac friendly
[16:17] (977.36s)
time zone and you know a few that are
[16:18] (978.96s)
European friendly often, you know, it's
[16:21] (981.12s)
not the way when you do like one early
[16:23] (983.04s)
in the morning on the west coast. That's
[16:24] (984.56s)
actually bad time for the Europeans
[16:26] (986.32s)
because that's kind of like when you
[16:27] (987.28s)
pick up your kids from school and go go
[16:29] (989.68s)
and have family dinner. So many of them
[16:31] (991.60s)
actually prefer a later point on the day
[16:34] (994.08s)
on the West Coast. So is later in the
[16:36] (996.16s)
evening when maybe everybody's watching
[16:37] (997.76s)
TV or the kids are already in bed. So
[16:39] (999.44s)
yeah, we're trying to really keep that
[16:41] (1001.76s)
spirit and it enables us to hire talent
[16:44] (1004.24s)
um you know in different places um in
[16:46] (1006.32s)
different uh phases of their life and
[16:49] (1009.12s)
and I think that helps us as a company
[16:50] (1010.88s)
you know to be um as agile as possible.
[16:53] (1013.20s)
Yeah, it is pretty cool to hear because
[16:55] (1015.36s)
GitHub I mean you can use GitHub in many
[16:57] (1017.12s)
ways but like one one popular way to use
[16:59] (1019.12s)
it at this async way, right? So it's
[17:01] (1021.28s)
kind of cool that you're using it the
[17:03] (1023.12s)
same way as a lot of the startups are. I
[17:05] (1025.12s)
think one of the core pieces there is
[17:06] (1026.72s)
not only as the startups are but as the
[17:08] (1028.88s)
open source ecosystem is using it right
[17:11] (1031.04s)
but the open source ecosystem by design
[17:13] (1033.44s)
is async async and they're not all in
[17:15] (1035.68s)
the same place that would never work if
[17:17] (1037.44s)
an open source project could only you
[17:19] (1039.60s)
know uh you could only be a contributor
[17:21] (1041.52s)
if you're in the same place and all the
[17:23] (1043.04s)
same time zone and so given that we're
[17:25] (1045.60s)
catering to both you know commercial
[17:27] (1047.60s)
customers startups enterprises uh those
[17:30] (1050.16s)
that are paying us money for GitHub
[17:31] (1051.52s)
enterprise and copile business but we're
[17:33] (1053.52s)
also catering serving ing the open
[17:35] (1055.20s)
source um economy, the open source
[17:37] (1057.76s)
ecosystem and as such as a company even
[17:39] (1059.84s)
though you know the GitHub core itself
[17:42] (1062.16s)
was never open source and we're
[17:43] (1063.60s)
operating pretty much like an open
[17:44] (1064.96s)
source project. One fun fact I've I've
[17:47] (1067.44s)
heard is you have some really kind of
[17:49] (1069.92s)
fun and interesting internal tools. Some
[17:52] (1072.00s)
some are still here, some are not. One
[17:54] (1074.64s)
tool that I understand is no longer
[17:56] (1076.00s)
there was called Haststack, which was an
[17:57] (1077.92s)
internal exception tracking app and
[18:00] (1080.24s)
someone told me it was the best piece of
[18:01] (1081.84s)
software they've seen. Can can you share
[18:03] (1083.36s)
a little bit about like what past fun in
[18:06] (1086.40s)
internal tools you have and what kind of
[18:08] (1088.08s)
internal tools you still have today
[18:09] (1089.92s)
especially for like what engineers use?
[18:11] (1091.76s)
If you look back into GitHub's history
[18:13] (1093.84s)
and um we don't have the time to cover
[18:15] (1095.60s)
it all today. I can I can recommend if I
[18:17] (1097.84s)
if I'm allowed to another podcast the
[18:20] (1100.32s)
acquired podcast um they had an episode
[18:22] (1102.88s)
on June 5th 2018. So the day after the
[18:25] (1105.92s)
acquisition announcement that covers a
[18:27] (1107.84s)
lot of the history of GitHub in the
[18:29] (1109.60s)
early days and uh in general a really
[18:32] (1112.24s)
good podcast um and and and they
[18:34] (1114.80s)
actually mentioned this that in GitHub
[18:36] (1116.80s)
you know when it started had a very you
[18:39] (1119.36s)
know non-traditional way of operating
[18:41] (1121.04s)
there were no managers everybody was
[18:43] (1123.04s)
encouraged to work on their passion
[18:44] (1124.72s)
projects and as such GitHub you know for
[18:48] (1128.08s)
many years didn't have a traditional IT
[18:51] (1131.04s)
uh uh infrastructure in the company and
[18:53] (1133.12s)
so everybody was built in house because
[18:55] (1135.68s)
there was the belief you know we can
[18:57] (1137.44s)
build we as GitHub can do it better than
[19:00] (1140.00s)
a tool that we can buy off the shelf. We
[19:02] (1142.00s)
maybe we come back to this later when we
[19:03] (1143.44s)
talk about AI that future might actually
[19:06] (1146.16s)
come back to to some startups. So we had
[19:08] (1148.64s)
a tool uh we had our own internal video
[19:11] (1151.36s)
streaming platform it was called
[19:12] (1152.72s)
githuba.tv TV and so all the you know
[19:15] (1155.44s)
town halls um and so on you know
[19:18] (1158.64s)
streamed on our own platform and of
[19:20] (1160.32s)
course that no longer exists and we're
[19:22] (1162.00s)
using Loom using Loom for that haste you
[19:25] (1165.52s)
already mentioned that was exception
[19:26] (1166.72s)
tracking and know keep in mind 15 years
[19:29] (1169.44s)
ago there wasn't like established
[19:31] (1171.28s)
players in that market that you could
[19:33] (1173.28s)
use especially not in the in the Ruby
[19:35] (1175.04s)
Railsburg so haste one was one such tool
[19:37] (1177.12s)
today it's sentry that we're using for
[19:39] (1179.28s)
that another one was Help Halp which was
[19:42] (1182.96s)
our internal support system where
[19:44] (1184.88s)
tickets got routed um uh for folks to
[19:47] (1187.12s)
work on the ticket have internal comput
[19:49] (1189.36s)
teams and yeah and now this is all in
[19:51] (1191.36s)
zenesk and and help has been retired but
[19:53] (1193.52s)
you know some of these ideas have led to
[19:56] (1196.08s)
new startups right where hubbas have
[19:58] (1198.00s)
hubbas is what we call employees where
[19:59] (1199.52s)
hubbas have taken the idea and maybe
[20:01] (1201.28s)
they were a bit frustrated that we're
[20:02] (1202.64s)
shutting down the their internal passion
[20:04] (1204.48s)
project have taken that and and and
[20:08] (1208.56s)
um I think you know culturally we are
[20:10] (1210.64s)
still encouraging folks pretty much to
[20:12] (1212.88s)
experiment and to incubate new ideas but
[20:14] (1214.56s)
we're trying to make those external
[20:17] (1217.20s)
facing products and there's a number of
[20:19] (1219.20s)
examples from GitHub history as well
[20:21] (1221.36s)
there electron comes to mind which came
[20:23] (1223.68s)
out of Adam which was was our editor um
[20:26] (1226.16s)
oh yes um you know our desktop app or
[20:28] (1228.88s)
comment line interface those are all
[20:30] (1230.24s)
open source projects and so everybody
[20:32] (1232.00s)
can see what we're doing there and can
[20:33] (1233.76s)
take the ideas and you know we mentioned
[20:35] (1235.20s)
stack text earlier the CLI for example
[20:36] (1236.96s)
is with mang go um and so it's also
[20:39] (1239.44s)
gives a you know whoever wants to learn
[20:41] (1241.04s)
how to build a CLI can use the GitHub CI
[20:42] (1242.96s)
as an example. One thing that keeps
[20:45] (1245.12s)
surprising me out with GitHub is every
[20:47] (1247.12s)
now and then there's a security incident
[20:49] (1249.04s)
that is in the press that is like a big
[20:51] (1251.04s)
deal. Not always, but sometimes it
[20:53] (1253.36s)
starts with like X company X had a
[20:56] (1256.16s)
security issue and it starts like oh
[20:58] (1258.08s)
they detected it because GitHub alerted
[21:00] (1260.16s)
it for them. And a very famous one was
[21:02] (1262.40s)
in 2022. Heroku had a security incident
[21:06] (1266.24s)
and it started by not Heroku noticing
[21:08] (1268.40s)
that something leaked but the but GitHub
[21:10] (1270.64s)
itself noticed some strange patterns.
[21:13] (1273.20s)
They contacted the Heroku security team
[21:15] (1275.52s)
who then confirmed it. And this just
[21:17] (1277.44s)
struck me a little bit striking like
[21:19] (1279.12s)
hold on like uh how is GitHub having
[21:22] (1282.96s)
better or very strong security? I'm not
[21:25] (1285.28s)
going to say better but in in in some
[21:26] (1286.64s)
ways in this case clearly they got
[21:28] (1288.40s)
earlier. What is your approach to
[21:30] (1290.32s)
security? And and this was again this
[21:31] (1291.92s)
was not even right now. This was years
[21:34] (1294.00s)
back. It it it just suggests to me like
[21:36] (1296.56s)
you probably think about security a
[21:38] (1298.16s)
little bit differently than maybe some
[21:39] (1299.92s)
other companies. Security is part of our
[21:41] (1301.60s)
culture. We have this saying security as
[21:44] (1304.64s)
priority zebo for for everybody. And in
[21:47] (1307.44s)
fact our previous uh siso Mike Handley
[21:49] (1309.92s)
introduced this concept um he came from
[21:52] (1312.32s)
Duo uh the two-factor authentication
[21:54] (1314.56s)
company. he introduced this concept that
[21:56] (1316.40s)
when the question is asked who here is
[21:58] (1318.08s)
on the security team every hub raises
[22:00] (1320.64s)
their hand and so we institutionalized
[22:02] (1322.40s)
that security is is part of what we do
[22:05] (1325.20s)
of course we want to drive innovation
[22:06] (1326.80s)
I'm going to make customers happy but we
[22:08] (1328.56s)
cannot win in the market if we lose the
[22:10] (1330.64s)
trust and of course the worst day you
[22:12] (1332.96s)
know uh in my life would be that I get a
[22:14] (1334.96s)
call and say I lost you know the private
[22:16] (1336.96s)
repositories we lost you know as a
[22:19] (1339.12s)
platform so it's so important to
[22:20] (1340.64s)
companies your code to an attacker and
[22:22] (1342.80s)
um and now have to do the damage control
[22:25] (1345.04s)
and so it's really important for us the
[22:26] (1346.88s)
CSO and the chief security officer
[22:28] (1348.80s)
reports directly to me and we have a
[22:31] (1351.44s)
team of about 150 or so boys that take
[22:35] (1355.20s)
care of security from from multiple
[22:37] (1357.20s)
angles. one is of of cost threat
[22:38] (1358.96s)
intelligence um working closely with the
[22:41] (1361.20s)
Microsoft security team uh the so-called
[22:43] (1363.76s)
cyber defense operations center uh and
[22:46] (1366.00s)
those folks that look into uh you know
[22:48] (1368.64s)
finding security vulnerabilities um that
[22:50] (1370.96s)
teaming uh not only for you know the
[22:53] (1373.12s)
traditional software they're building
[22:54] (1374.40s)
but also for for the AI pieces and you
[22:56] (1376.64s)
can imagine you know at the scale of
[22:58] (1378.64s)
GitHub but even more so at the scale of
[23:00] (1380.40s)
Microsoft there's a lot of threat
[23:02] (1382.40s)
intelligence when you combine all that
[23:04] (1384.24s)
intelligence you get a lot of signal and
[23:06] (1386.72s)
one such example is a very trivial
[23:09] (1389.12s)
example is that if you have a person if
[23:11] (1391.92s)
you for example you know you your user
[23:14] (1394.00s)
ID accesses not only the pragmatic
[23:15] (1395.84s)
engineer repositories but also those of
[23:18] (1398.48s)
let's say BMW and Mercedes that person
[23:21] (1401.84s)
is very unlikely to exist in in the
[23:24] (1404.80s)
industry right like even if if you're
[23:26] (1406.88s)
working for like a systems integrator
[23:29] (1409.04s)
then you typically don't work on a BMW
[23:30] (1410.96s)
and a Mercedes project together so
[23:32] (1412.96s)
there's a lot of intelligence that we
[23:34] (1414.48s)
can collect by having the holistic view
[23:36] (1416.80s)
even more so when when you combine it
[23:38] (1418.32s)
with all the other Microsoft systems.
[23:39] (1419.76s)
And we also have a security lab um where
[23:41] (1421.52s)
we have a team of research that's uh
[23:43] (1423.36s)
that are hunting for security
[23:45] (1425.36s)
vulnerabilities using our own security
[23:47] (1427.28s)
products uh like CodeQL which is query
[23:49] (1429.76s)
language um that you can use to find
[23:52] (1432.08s)
variances um like variations of existing
[23:55] (1435.68s)
code flaws you know code vulnerabilities
[23:58] (1438.56s)
tries to find those in open source
[24:00] (1440.32s)
projects and then reports them to the
[24:02] (1442.00s)
open source maintainer in a responsible
[24:03] (1443.84s)
way helping them to fix those in the
[24:06] (1446.00s)
time of thelo disclosure hopefully uh
[24:08] (1448.32s)
you know the bug is already fixed And so
[24:09] (1449.84s)
we doing a lot of that. We're investing
[24:11] (1451.52s)
into a lot of that. But of course, you
[24:13] (1453.12s)
know, nobody is perfect. And so it's
[24:15] (1455.04s)
really crucial for us as a company to
[24:16] (1456.72s)
have this ingrained into our culture to
[24:18] (1458.56s)
not have secrets and source code. In
[24:20] (1460.00s)
fact, you're blocking all the pushes and
[24:22] (1462.00s)
Exactly. I guess I guess open source
[24:24] (1464.08s)
might help here. Your your big focus on
[24:25] (1465.84s)
open source, but you mentioned 150
[24:27] (1467.84s)
people working on on security as
[24:29] (1469.20s)
context. How how many people are
[24:30] (1470.72s)
engineers are in GitHub roughly these
[24:33] (1473.12s)
days? Yeah. So GitHub all up is about
[24:34] (1474.96s)
3,000 uh uh employees. um about half or
[24:38] (1478.56s)
so are in what I would call engineering
[24:40] (1480.32s)
product design or EPD. Um so that's
[24:43] (1483.20s)
that's about 10%. If I just look at the
[24:45] (1485.60s)
security roughly engineering function
[24:48] (1488.56s)
and then you look at just um engineers
[24:51] (1491.28s)
IC engineers it's a little bit under a
[24:53] (1493.20s)
thousand um that work and build software
[24:55] (1495.60s)
and then it's of course managers and
[24:56] (1496.88s)
product managers and technical program
[24:58] (1498.40s)
managers, designers and all that. One
[25:00] (1500.08s)
interesting thing I've heard from a
[25:01] (1501.36s)
current get employee is you are starting
[25:03] (1503.36s)
to look into hiring junior developers
[25:06] (1506.24s)
developers with less experienced which
[25:07] (1507.68s)
is a little bit different because most
[25:09] (1509.60s)
of the industry does we don't hear this.
[25:11] (1511.60s)
Yeah. Why are you deciding on this and
[25:13] (1513.84s)
like you know this is just a really
[25:15] (1515.36s)
positive thing to hear. I'd love to hear
[25:17] (1517.04s)
more about your thinking. We're really
[25:18] (1518.24s)
excited about working with young people.
[25:20] (1520.00s)
You saw some of those um uh on the in
[25:22] (1522.40s)
the second day keynote yesterday as
[25:24] (1524.16s)
well. And in fact you know just on
[25:26] (1526.00s)
Monday um our intern class for this for
[25:28] (1528.48s)
the summer started. We have three groups
[25:30] (1530.16s)
that start on different days and go
[25:31] (1531.60s)
through the internship. So those are the
[25:33] (1533.20s)
very early in career folks um that often
[25:35] (1535.44s)
oh not not often that still go to to
[25:37] (1537.52s)
college or university and um this is a
[25:39] (1539.92s)
program that we um institutionalized um
[25:43] (1543.04s)
after after the pandemic was over and
[25:44] (1544.96s)
you could bring people back in person
[25:46] (1546.80s)
because obviously or to half in person
[25:49] (1549.12s)
where they at least have you know a way
[25:50] (1550.96s)
you know to to meet with folks um um at
[25:53] (1553.52s)
our San Francisco headquarters or here
[25:56] (1556.40s)
in the Pacific Northwest or or elsewhere
[25:58] (1558.16s)
in the world and so we have an intern
[25:59] (1559.92s)
program and often uh you know these
[26:01] (1561.68s)
interns get a full-time offer at the end
[26:04] (1564.00s)
of the internship or maybe they come
[26:05] (1565.36s)
back for a second year. Uh and so it's a
[26:08] (1568.00s)
lovely to see uh that you know those
[26:10] (1570.16s)
folks that bring fresh ideas um a great
[26:13] (1573.04s)
amount of energy you know the the latest
[26:15] (1575.20s)
learnings uh from coalition university
[26:18] (1578.00s)
um and often you know a different uh you
[26:20] (1580.24s)
know diverse background uh into into the
[26:22] (1582.32s)
company and and and you know come in and
[26:24] (1584.64s)
and often you know the the folks you
[26:27] (1587.36s)
know that are younger in in Korea uh
[26:30] (1590.48s)
bring bring a new perspective to the
[26:32] (1592.32s)
team and say hey this is you know why
[26:34] (1594.40s)
why don't we try this or I want to
[26:36] (1596.00s)
incubate this idea Yeah. Um, and so we
[26:38] (1598.00s)
are very excited about having this kind
[26:40] (1600.48s)
of like both junior and and senior
[26:42] (1602.40s)
population in the company. And it's not
[26:44] (1604.16s)
only true in engineering, you know, it's
[26:45] (1605.36s)
the same in if you look in into sales or
[26:47] (1607.52s)
into marketing. Obviously, the way, you
[26:49] (1609.52s)
know, marketing works today, uh, is very
[26:52] (1612.32s)
different, um, than it was, you know, 5
[26:54] (1614.32s)
10 years ago when the press, you know,
[26:57] (1617.04s)
traditional media played a much bigger
[26:58] (1618.80s)
role. uh today uh you got to be you know
[27:01] (1621.36s)
in a podcast and and you have to be on
[27:03] (1623.76s)
on YouTube and Tik Tok and just like
[27:05] (1625.68s)
today just like today but yeah you you
[27:07] (1627.52s)
know that that you see more and more of
[27:09] (1629.20s)
that happening and of course you know
[27:10] (1630.96s)
the when you when you hire people
[27:13] (1633.28s)
earlier in Korea they give you those
[27:15] (1635.52s)
ideas they give you that input and you
[27:17] (1637.36s)
know how it is you you talk to a lot
[27:19] (1639.12s)
people in companies there's always a
[27:21] (1641.36s)
debate um there's always a debate
[27:23] (1643.12s)
between those um that are defending how
[27:25] (1645.44s)
we've always done it uh in a 50-year-old
[27:28] (1648.24s)
company like Microsoft that obviously
[27:30] (1650.08s)
exists and and those that come in and
[27:31] (1651.76s)
say, "Hey, you know, nobody in my peer
[27:34] (1654.00s)
group, you know, watches TV anymore and
[27:36] (1656.48s)
or CNBC or whatever." Uh, and they're
[27:38] (1658.88s)
all watching just, you know, 3 minute
[27:40] (1660.80s)
videos on on TikTok. Um, and so I think
[27:43] (1663.04s)
that's really important and and we're
[27:45] (1665.20s)
trying to have, you know, a nice balance
[27:47] (1667.36s)
between early career engineers, senior
[27:50] (1670.08s)
engineers. We have, you know, a number
[27:51] (1671.36s)
of distinguished engineers and they all
[27:53] (1673.04s)
contribute back to to our platform. No,
[27:54] (1674.56s)
I I I love it cuz like when when I when
[27:56] (1676.56s)
I worked both as an engineering manager
[27:58] (1678.32s)
or as an engineer, having an intern, it
[28:00] (1680.64s)
just like boosted morale. Like we were
[28:02] (1682.72s)
so much more enthusiastic. I'm not going
[28:04] (1684.56s)
to say that we necessarily did more
[28:06] (1686.08s)
work. I think we we might have, but we
[28:07] (1687.68s)
got fresh ideas. And it's just so
[28:10] (1690.72s)
rewarding looking back at those interns.
[28:12] (1692.48s)
You know, I now see them many many years
[28:14] (1694.40s)
later. Some are now principal engineers,
[28:16] (1696.08s)
some are CTO's. But the one question
[28:18] (1698.72s)
that a lot of people who are maybe less
[28:20] (1700.64s)
technical than you and have not seen the
[28:22] (1702.16s)
benefit of internships, they're thinking
[28:23] (1703.60s)
like, "Oh, I'm hearing all these AI
[28:25] (1705.52s)
things, including Microsoft, is saying
[28:27] (1707.20s)
it's so efficient, you know, now they're
[28:28] (1708.72s)
now talking about AI colleagues on on
[28:30] (1710.40s)
the keynote. Why?" And and and now this
[28:34] (1714.24s)
is non-Microsoft people, but we're
[28:35] (1715.60s)
hearing people at Google say like, "Oh,
[28:37] (1717.04s)
it's now at a level of a junior
[28:38] (1718.32s)
engineer." uh and they're thinking, hm,
[28:41] (1721.28s)
maybe let's hold off on hiring new grads
[28:43] (1723.92s)
because they're telling us, you know,
[28:45] (1725.36s)
some of these so-called experts that
[28:47] (1727.04s)
it's now at the level of junior
[28:48] (1728.32s)
engineers, so maybe we don't need junior
[28:49] (1729.84s)
engineers. What would you suggest to
[28:51] (1731.92s)
people who are in this thinking and may
[28:53] (1733.92s)
maybe not as informed because clearly
[28:55] (1735.52s)
you you've decided it makes sense and
[28:57] (1737.68s)
you know this this thing doesn't apply,
[28:59] (1739.36s)
but their thinking is real. I think
[29:01] (1741.04s)
that's backwards in many ways. I think
[29:03] (1743.12s)
actually folks that you know go to high
[29:05] (1745.28s)
school now or to college or or even you
[29:07] (1747.76s)
know kids earlier in in their education
[29:10] (1750.56s)
they get to use AI much faster and they
[29:13] (1753.20s)
they get it because they are you know
[29:14] (1754.96s)
taking this with an open mind. They they
[29:16] (1756.72s)
don't have to this is how we always done
[29:18] (1758.40s)
it. This you know don't touch never
[29:20] (1760.00s)
touch a running system. They haven't
[29:21] (1761.44s)
been in an experience where some change
[29:23] (1763.68s)
that was applied you know from from
[29:25] (1765.28s)
upper management or or from the
[29:27] (1767.04s)
engineers themselves has led to you know
[29:29] (1769.12s)
a big outage and things like that. So
[29:30] (1770.72s)
they're more open-minded. you you know
[29:32] (1772.56s)
you kind of see that when you look at
[29:34] (1774.08s)
media as as we already talked about like
[29:36] (1776.16s)
kids are much more uh open to just
[29:38] (1778.40s)
scrolling through shorts um and and and
[29:41] (1781.12s)
consuming the content they'd like to
[29:42] (1782.80s)
consume while you know when you and I
[29:44] (1784.32s)
were a child we had linear TV and you
[29:46] (1786.72s)
got to watch on the living room TV what
[29:48] (1788.80s)
your mom and dad decided is is on on
[29:51] (1791.20s)
tonight right and so they have much more
[29:52] (1792.56s)
freedom and I think this will lead to to
[29:55] (1795.04s)
ultimately um junior engineers coming or
[29:57] (1797.76s)
or interns coming into the companies and
[30:00] (1800.00s)
bringing in like prompting skills you
[30:02] (1802.08s)
know like experience with different
[30:03] (1803.60s)
models like you know intern doesn't mean
[30:06] (1806.24s)
I haven't worked for another company
[30:07] (1807.60s)
before it might be my third my second or
[30:09] (1809.84s)
third internship or might have already
[30:11] (1811.76s)
been coding with you know a group of
[30:13] (1813.44s)
students on on my own project on my own
[30:15] (1815.68s)
app so you get a lot of good new ideas
[30:18] (1818.08s)
and outside perspective that is
[30:19] (1819.60s)
ultimately crucial uh to compete in the
[30:22] (1822.08s)
market and I think vice versa you know
[30:23] (1823.92s)
these interns then go back into college
[30:25] (1825.92s)
and they have worked on something real I
[30:27] (1827.84s)
I remember my time at university I
[30:29] (1829.44s)
always had the feeling I got to get out
[30:30] (1830.88s)
into industry and learn how it's
[30:32] (1832.96s)
actually done because while you know
[30:34] (1834.88s)
there's you learn coding in university
[30:37] (1837.04s)
but you don't really have an engineering
[30:39] (1839.04s)
system you're not having tech debt
[30:41] (1841.36s)
you're not working on a legacy codebase
[30:43] (1843.28s)
becoming an engineer in a company means
[30:45] (1845.20s)
you're working on somebody else's code
[30:47] (1847.76s)
um often now you know GitHub 17 years
[30:50] (1850.00s)
old code uh and you have to follow up on
[30:53] (1853.12s)
decisions other other people made and
[30:55] (1855.36s)
that's not how you learn coding in in a
[30:57] (1857.12s)
university and so I think it's both for
[30:59] (1859.12s)
us important to have those fresh ideas
[31:01] (1861.36s)
within the company, but also for us
[31:02] (1862.72s)
important to to give back uh to to those
[31:06] (1866.24s)
that in the future become GitHub
[31:07] (1867.52s)
customers. I I love it and I feel it's
[31:09] (1869.44s)
also just a very it's the cheapest way
[31:11] (1871.20s)
to do it just like it, you know, you're
[31:12] (1872.88s)
not going to have the highest salary for
[31:14] (1874.16s)
the the new people. This is a silly way
[31:16] (1876.24s)
to think about it, but I talked with the
[31:17] (1877.68s)
product manager recently and I I just
[31:19] (1879.20s)
like had a deja vu when when you said
[31:20] (1880.72s)
it, this product manager was saying she
[31:22] (1882.48s)
she was saying this is while we were
[31:24] (1884.08s)
doing the Gen Z research about the
[31:25] (1885.68s)
latest generation. She said, "I love Gen
[31:28] (1888.08s)
Z." She's like, she's like, for years as
[31:30] (1890.08s)
a product manager, I'm sitting in front
[31:31] (1891.44s)
of engineers telling them, oh, you know,
[31:33] (1893.68s)
get product thinking, think about the
[31:35] (1895.44s)
customer, and they're like, just tell
[31:36] (1896.48s)
us, you know, what we need to do. And
[31:37] (1897.84s)
she's like, the new generation comes in
[31:39] (1899.60s)
and they have opinions. They're like, I
[31:41] (1901.52s)
think our customers would like this. I
[31:43] (1903.12s)
have tested a competitor. Here's what
[31:44] (1904.72s)
they're doing. Here's And she's like, I
[31:46] (1906.40s)
love it. Like they So, I I I want I
[31:48] (1908.96s)
wonder if like by hiring these people
[31:50] (1910.88s)
and actually just ignoring, as you say,
[31:52] (1912.56s)
the backward thinking, you might get the
[31:54] (1914.08s)
next generation of of software
[31:55] (1915.44s)
engineers. Gen Z is already too old I
[31:57] (1917.28s)
think to some degree because Gen Z I
[31:59] (1919.52s)
think starts 1980 or something like that
[32:01] (1921.36s)
the millennials Gen Alpha right like the
[32:03] (1923.84s)
60 years old are coding today and so
[32:06] (1926.24s)
that's Gen Alpha or you know soon the
[32:08] (1928.00s)
whatever the gen beta I guess is the
[32:09] (1929.60s)
next one and so but you're right you
[32:11] (1931.60s)
know you're you're getting folks that
[32:13] (1933.60s)
didn't learn to code on a on a on a
[32:15] (1935.52s)
Commodore 64 on a PC that you know have
[32:18] (1938.56s)
have a lot of low-level thinking but
[32:20] (1940.72s)
also you know learned in in a different
[32:22] (1942.72s)
in a different environment than those
[32:24] (1944.32s)
you know that cool with with smartphones
[32:26] (1946.16s)
that grew up with being always
[32:27] (1947.44s)
connected. They just have just from an
[32:29] (1949.76s)
expectation perspective, they they're
[32:31] (1951.60s)
looking at this often systems problem
[32:33] (1953.92s)
they're trying to solve with a different
[32:35] (1955.68s)
with a different perspective. Yeah. I I
[32:37] (1957.60s)
wonder just like silly thing. Would you
[32:40] (1960.00s)
rather hire an engineer with the same
[32:41] (1961.84s)
years of experience of like someone who
[32:43] (1963.44s)
has, you know, like has traditional
[32:44] (1964.96s)
coding and learned in university or same
[32:48] (1968.00s)
years old? you learned in university and
[32:49] (1969.92s)
did some university projects or this
[32:52] (1972.32s)
engineer or this this this fresh grad
[32:54] (1974.64s)
who did a university but they actually
[32:56] (1976.80s)
have before that five years of building
[32:59] (1979.04s)
programs and roadblocks and they
[33:00] (1980.64s)
actually built this like 100 person
[33:02] (1982.72s)
thing is like the skills that that
[33:04] (1984.40s)
person brings and the the mindset you
[33:06] (1986.16s)
know the way they think about things and
[33:07] (1987.44s)
there's a third group and and there's
[33:08] (1988.88s)
lots of folks you know at Microsoft and
[33:10] (1990.32s)
GitHub that don't have a formal uh
[33:12] (1992.40s)
university education and either dropped
[33:14] (1994.48s)
out or another event right that's that
[33:16] (1996.08s)
goes back to the earlier discussion
[33:17] (1997.60s)
about um being an an remote first
[33:20] (2000.32s)
company, you hire people because they're
[33:22] (2002.32s)
passionate about the product. You hire
[33:23] (2003.76s)
people because they have a green
[33:25] (2005.20s)
contribution graph on their GitHub
[33:26] (2006.88s)
profile uh because they have shown they
[33:29] (2009.04s)
contributed back to the Ruby on Rails
[33:30] (2010.88s)
codebase to the to the Git, you know,
[33:32] (2012.80s)
open source codebase where you know at
[33:34] (2014.56s)
GitHub we traditionally have employed
[33:36] (2016.72s)
folks that are spending a lot of time on
[33:38] (2018.88s)
maintaining git together with the open
[33:40] (2020.56s)
source community. So I think a lot you
[33:42] (2022.40s)
know uh what actually plays a role to us
[33:44] (2024.48s)
is that folks have shown the right
[33:46] (2026.16s)
mindset uh to join GitHub they if they
[33:48] (2028.72s)
if you don't have a green contribution
[33:50] (2030.16s)
graph on your GitHub profile um that I
[33:52] (2032.88s)
think matters more to us than whether
[33:54] (2034.48s)
you have five years at one company and
[33:56] (2036.16s)
five other company of course we you know
[33:58] (2038.16s)
take people to an interview loop and I
[33:59] (2039.76s)
think increasingly we're thinking about
[34:01] (2041.76s)
how do we leverage AI within the
[34:03] (2043.76s)
interview loop um there's nothing wrong
[34:06] (2046.00s)
about that from my perspective in fact I
[34:07] (2047.92s)
would say if you want to you know get a
[34:10] (2050.64s)
up in a tech company. Very soon, you're
[34:12] (2052.80s)
going to be asked to show your your
[34:14] (2054.40s)
prompting skills, your your co-pilot
[34:16] (2056.08s)
skills, if you will, and how you use uh
[34:18] (2058.24s)
something like agent mode or the coding
[34:19] (2059.76s)
agent that we introduced this week to to
[34:22] (2062.40s)
get the exercise done, you know, to
[34:24] (2064.32s)
basically because the the the goal of
[34:26] (2066.72s)
the future engineer is no longer to
[34:28] (2068.16s)
write it all from scratch and the goal
[34:29] (2069.92s)
is to, you know, combine their prompting
[34:31] (2071.76s)
skills and agent open source libraries
[34:34] (2074.16s)
into getting that problem solved much
[34:36] (2076.32s)
faster than they could have done two
[34:38] (2078.00s)
three years ago. So with with that these
[34:39] (2079.92s)
were some of the like a bunch of
[34:41] (2081.52s)
interesting facts. I wanted to talk
[34:43] (2083.52s)
about the the the past and then later
[34:45] (2085.60s)
the present and the future of GitHub
[34:47] (2087.28s)
starting with the past. So git uh we we
[34:50] (2090.88s)
I did a podcast episode with Linux
[34:53] (2093.12s)
kernel maintainer Greg KH and he he told
[34:56] (2096.00s)
a story about how git was created in in
[34:57] (2097.84s)
2005. In fact recently there's a podcast
[34:59] (2099.92s)
with GitHub a staff engineer at GitHub
[35:02] (2102.32s)
interviewed Linos in 2005. Lin store
[35:05] (2105.12s)
words got frustrated with uh the source
[35:07] (2107.92s)
control for the Linux project
[35:09] (2109.28s)
specifically. There was some commercial
[35:10] (2110.72s)
things we can see history sat down in 10
[35:13] (2113.04s)
days he wrote git which was obviously
[35:15] (2115.20s)
open source it was meant for Linux only
[35:17] (2117.20s)
but they released it and turns out it's
[35:19] (2119.28s)
pretty good. GitHub was founded in I
[35:21] (2121.84s)
believe 2008. Can can you tell me about
[35:24] (2124.00s)
these early days? What what what
[35:25] (2125.68s)
happened then? What you understand from
[35:27] (2127.28s)
talking with the early founders? The
[35:29] (2129.12s)
first commit was October 2007. So it was
[35:31] (2131.52s)
about 2 years after Lenos had done git,
[35:34] (2134.56s)
right? And then October 2007 to I
[35:36] (2136.88s)
believe February 2008 is when uh they
[35:39] (2139.44s)
started beta testing it with with folks
[35:42] (2142.24s)
in the Ruby Ruby Rails community. And
[35:44] (2144.64s)
then um April is when the public version
[35:47] (2147.76s)
of of GitHub launched. So it's really
[35:49] (2149.36s)
fast as well. um you know October to to
[35:51] (2151.44s)
April Fier six months you know if you go
[35:53] (2153.92s)
back you know to to the history books um
[35:56] (2156.48s)
it's Chris and Tom uh Tom Tom Creston
[35:59] (2159.44s)
Bourne and Chris Wstrad meeting in a bar
[36:01] (2161.84s)
as as I remember it and uh having seen
[36:04] (2164.56s)
Git and and and and figuring out that
[36:07] (2167.12s)
there isn't um a place um where you can
[36:09] (2169.92s)
host your your open source repositories
[36:12] (2172.00s)
and your private repositories together.
[36:13] (2173.76s)
There was obviously things like um
[36:15] (2175.44s)
Source Forge um which was the most
[36:18] (2178.08s)
popular open source platform back then
[36:20] (2180.24s)
but also you know painful to use um I
[36:23] (2183.68s)
think that's fair to say like those that
[36:25] (2185.44s)
I had a couple projects on saucer as
[36:27] (2187.12s)
well. It was kind of designed for a
[36:28] (2188.64s)
different era of the web and and didn't
[36:31] (2191.44s)
and didn't make the jump in that mode
[36:33] (2193.36s)
ultimately you know became known as as
[36:35] (2195.28s)
web uh as web web 2.0 or or cloud
[36:38] (2198.40s)
native. And so I think the the idea was
[36:40] (2200.64s)
okay, git is here. Git is amazing uh but
[36:43] (2203.28s)
I want to host it um without you know
[36:45] (2205.52s)
setting up a server and installing you
[36:47] (2207.20s)
know the back end and managing you know
[36:49] (2209.12s)
SSH access. And so they started building
[36:51] (2211.44s)
around around that idea. What always
[36:54] (2214.32s)
made GitHub GitHub is that they put the
[36:56] (2216.24s)
developers first. Like if you go on the
[36:58] (2218.24s)
Vback machine and look at the first you
[37:00] (2220.08s)
know GitHub homepage it isn't very
[37:02] (2222.48s)
fancy. It looks like a commit lock. this
[37:04] (2224.64s)
very short announcement of hey you know
[37:06] (2226.80s)
we shipped this new feature try it out
[37:08] (2228.24s)
and let us know what you think right the
[37:10] (2230.16s)
story about our logo uh what is now
[37:12] (2232.96s)
known as the octoad you know is is is a
[37:15] (2235.44s)
funny one and I learned that actually
[37:17] (2237.04s)
from the acquired podcast because they
[37:19] (2239.28s)
um they learned from the Twitter
[37:20] (2240.80s)
founders how they got their logo and
[37:22] (2242.16s)
they bought it on some uh stock graphic
[37:24] (2244.40s)
uh page um from a British designer I
[37:27] (2247.12s)
believe and so they looked you know for
[37:29] (2249.12s)
other graphics that that the same
[37:30] (2250.64s)
designer had done and and bought you
[37:33] (2253.12s)
know this this hybrid rid of an octopus
[37:35] (2255.44s)
and a and a cat uh and and and made that
[37:38] (2258.64s)
the logo. Um right. So there was a lot
[37:41] (2261.04s)
of you know as a bootstrap startup
[37:42] (2262.72s)
that's scrappy that has a cool
[37:44] (2264.96s)
technology that might you know become
[37:46] (2266.96s)
the next the future of of of version
[37:49] (2269.20s)
control and then they built what is now
[37:52] (2272.16s)
known as cloud native but a cloud native
[37:54] (2274.24s)
company and um and then yeah it grew
[37:58] (2278.08s)
fast and uh back in the day probably the
[38:01] (2281.92s)
product with the fastest product market
[38:03] (2283.68s)
fit. Uh nowadays you know there's there
[38:06] (2286.72s)
other companies that have it similar but
[38:08] (2288.32s)
it's a different time. It's a different
[38:09] (2289.60s)
time now and I think it was unheard of
[38:12] (2292.64s)
um how quickly it spread like wildfire.
[38:15] (2295.36s)
I was in 2008 still working in the
[38:17] (2297.68s)
automotive industry. I was at Bosch. Uh
[38:19] (2299.44s)
so I didn't use GitHub in the first year
[38:21] (2301.36s)
and then I quit Bosch at the end of 2008
[38:23] (2303.84s)
not because of GitHub but because of the
[38:25] (2305.20s)
iPhone SDK and I became you know an an
[38:28] (2308.72s)
ISV building apps for for German
[38:30] (2310.64s)
companies. And so I created I think my
[38:32] (2312.56s)
GitHub account in in in early 2009. We
[38:35] (2315.20s)
can look it up I think March or April
[38:36] (2316.88s)
2009. And then I was at Rails conf uh
[38:39] (2319.44s)
the Ruby Rails conference in Las Vegas
[38:41] (2321.60s)
in 2009 and saw Chris uh Wrath giving a
[38:44] (2324.56s)
talk about GitHub and and what they up
[38:46] (2326.64s)
to and that's I would say when I became
[38:48] (2328.32s)
a GitHub fan and and when I started
[38:50] (2330.00s)
using GitHub in in my projects um but
[38:52] (2332.16s)
until that point you would use some some
[38:54] (2334.00s)
help self was a tool you know install it
[38:56] (2336.08s)
on some wood server or maybe you already
[38:57] (2337.92s)
had the cloud and and and maintain all
[38:59] (2339.84s)
that yourself and ever since people just
[39:01] (2341.84s)
you know log in with GitHub and and
[39:03] (2343.20s)
create a repo. Yeah, when I looked
[39:04] (2344.88s)
through the history just the things that
[39:06] (2346.64s)
I could find what struck me as like so
[39:09] (2349.12s)
like as the first company was it 2007 in
[39:11] (2351.20s)
2008 the service was launched I think
[39:13] (2353.28s)
you said March or something like that
[39:15] (2355.04s)
April sorry and already in 2008 the
[39:18] (2358.96s)
Reddit, Yahoo, Twitter and Facebook
[39:21] (2361.68s)
already onboarded. Facebook was
[39:23] (2363.52s)
surprising to me cuz I knew they use
[39:25] (2365.28s)
Mercurial but apparently they use it for
[39:26] (2366.96s)
their open source things. And these are
[39:28] (2368.80s)
these were very hip and very trendy
[39:30] (2370.72s)
companies at the time. And obviously
[39:32] (2372.08s)
from there on as you said in 2009 this
[39:34] (2374.00s)
was the obvious place to to find. Why do
[39:36] (2376.40s)
you think it was so popular? Like what
[39:38] (2378.64s)
what what was the reason? Was it open
[39:40] (2380.08s)
source? Was it because git wasn't even
[39:42] (2382.72s)
like back we're talking 2008 2009 like
[39:45] (2385.12s)
now we know git is great and it works
[39:46] (2386.96s)
but back then this was not clear. There
[39:48] (2388.56s)
was s everyone was using svn. I remember
[39:51] (2391.04s)
at the time and Microsoft had their own
[39:53] (2393.12s)
really heavily invested TFS team
[39:55] (2395.36s)
foundation server. Why do you think this
[39:57] (2397.60s)
product market fit just hit so so bad
[39:59] (2399.92s)
and devs were like yeah GitHub is the
[40:01] (2401.60s)
place to be? get you know solve the pain
[40:04] (2404.00s)
point that we you have with all these
[40:05] (2405.84s)
other uh dist version control systems
[40:08] (2408.72s)
you know subversion TFS you know had its
[40:11] (2411.52s)
own uh version control until much later
[40:13] (2413.60s)
when they added git support uh they're
[40:15] (2415.76s)
painful to use um and they were painful
[40:17] (2417.92s)
to use especially when you had multiple
[40:20] (2420.08s)
teams working together within the same
[40:22] (2422.24s)
codebase git bought this concept of you
[40:25] (2425.20s)
have the full repository on your machine
[40:27] (2427.60s)
so you can switch from one branch to
[40:29] (2429.04s)
another even without having the
[40:31] (2431.92s)
connection and you had always everything
[40:33] (2433.52s)
on your computer. So, you know, you
[40:35] (2435.60s)
could make changes to multiple branches
[40:37] (2437.20s)
and then then pushed upstream or or
[40:39] (2439.28s)
shared with your co-workers. And in some
[40:41] (2441.44s)
ways, you know, GitHub, I think, is the
[40:43] (2443.04s)
irony of um of of software development
[40:45] (2445.36s)
tools um because you have a
[40:47] (2447.04s)
decentralized system like Git and then
[40:48] (2448.96s)
you have a central hub uh where that the
[40:52] (2452.32s)
world depends on today and where
[40:54] (2454.64s)
everybody pushes to. So this notion of
[40:56] (2456.80s)
of decentralized systems is still
[40:59] (2459.12s)
something that sounds great and when
[41:00] (2460.96s)
developers are chatting about technology
[41:03] (2463.44s)
uh but I think humans are are longing
[41:06] (2466.24s)
for home and you know today at GitHub we
[41:08] (2468.72s)
have the saying we're the home of
[41:10] (2470.40s)
software developers um where they
[41:12] (2472.00s)
collaborate um human to human and and
[41:14] (2474.16s)
soon human to agent. So I think that
[41:16] (2476.24s)
played a big role. um you had you have
[41:18] (2478.24s)
had a new version control system that
[41:19] (2479.76s)
people were intrinsically motivated to
[41:21] (2481.60s)
try out because they were frustrated
[41:23] (2483.28s)
with using or even CBS, you know, and um
[41:26] (2486.56s)
and something like that and and just
[41:28] (2488.40s)
wanted something new to solve that
[41:30] (2490.32s)
problem and then it was just easy to to
[41:32] (2492.48s)
to shoot an account and um and and try
[41:35] (2495.04s)
it out and and uh you know even user
[41:37] (2497.60s)
interfaces like browsing the repo,
[41:39] (2499.52s)
clicking through the file tree, GitHub,
[41:41] (2501.92s)
you know, innovated a lot in that
[41:43] (2503.60s)
compared to what was there before and
[41:45] (2505.36s)
making that Ajax requests. So they would
[41:47] (2507.68s)
load really fast and you wouldn't wait
[41:49] (2509.12s)
to full full pry load. GitHub invented
[41:51] (2511.36s)
the pull request. You know this notion
[41:52] (2512.96s)
of that you can fork a repo make your
[41:55] (2515.44s)
modifications. If you'd like to keep
[41:56] (2516.96s)
your fork, you can just do that. That's
[41:58] (2518.56s)
totally cool. Or you can send a pull
[42:00] (2520.32s)
request back. So asking the other
[42:02] (2522.08s)
maintainer uh to to merge in your
[42:03] (2523.92s)
changes before that diff files were
[42:05] (2525.84s)
exchanged. This episode is brought to
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you by Augment Code. You're a
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[42:57] (2577.04s)
Well, I think this is one of the biggest
[42:58] (2578.48s)
thing that people miss as as I
[42:59] (2579.84s)
understood like understanding. So like
[43:01] (2581.36s)
Lin store was designed git and a lot of
[43:03] (2583.60s)
github or the git functionality comes
[43:05] (2585.84s)
from there, but the Linux workflow was
[43:08] (2588.16s)
email based. So actually in git there is
[43:10] (2590.08s)
a command. I don't remember the exact
[43:11] (2591.84s)
command where I think it's something
[43:13] (2593.60s)
email where you send an email with your
[43:15] (2595.92s)
changes bundled with your git changes
[43:18] (2598.08s)
bundled and that's how Linux works. They
[43:19] (2599.68s)
just use email and GitHub does not do
[43:22] (2602.48s)
this indeed. GitHub invented the the
[43:24] (2604.72s)
pull request which is a big difference
[43:26] (2606.96s)
between even today how Linux uses get
[43:29] (2609.12s)
and and GitHub does and yeah it was a
[43:30] (2610.96s)
smash. When was the pull request
[43:32] (2612.16s)
invented? Do you know was it early on?
[43:34] (2614.00s)
I'm getting the date form. I think it
[43:35] (2615.36s)
was a year or so in into
[43:37] (2617.84s)
it wasn't definitely wasn't there on day
[43:39] (2619.36s)
one. uh it it came sometime later. Um we
[43:42] (2622.16s)
can you know look it up and add to show
[43:43] (2623.92s)
notes but um it was a new thing at the
[43:47] (2627.28s)
time and I think it it's ultimately
[43:49] (2629.84s)
liberating for for software developers
[43:52] (2632.08s)
where you send a pull request and you
[43:53] (2633.92s)
know if the maintainer doesn't like it
[43:55] (2635.36s)
they can just close the pull request or
[43:57] (2637.20s)
leave it open but others can see it you
[44:00] (2640.16s)
know and and if they want to pick it up
[44:02] (2642.00s)
they can just jump over to your fork and
[44:04] (2644.08s)
keep using it there. So you see, you
[44:06] (2646.00s)
know, um see a lot of that also
[44:07] (2647.84s)
happening that people just keep their
[44:09] (2649.20s)
forks independent uh because they want
[44:11] (2651.92s)
to they don't want to have the
[44:12] (2652.88s)
obligation to to engage with the main
[44:15] (2655.20s)
project. Like I have a bunch of forks
[44:17] (2657.12s)
where I made some small modification for
[44:19] (2659.52s)
my own, you know, hobby project. Um I
[44:22] (2662.24s)
don't see, you know, um I don't see a
[44:24] (2664.56s)
big reason that that needs to go back
[44:26] (2666.24s)
into the main branch. Some of that might
[44:28] (2668.00s)
be just with hackery as well, right? And
[44:30] (2670.64s)
so you it makes it much easier for
[44:32] (2672.24s)
developers that want to collaborate to
[44:33] (2673.92s)
collaborate with each other. And for for
[44:35] (2675.28s)
the others it democratizes how they
[44:37] (2677.52s)
engage with open source, how they learn
[44:38] (2678.96s)
from it, how they mix and match and and
[44:41] (2681.28s)
so on. So what one kind of gathering if
[44:43] (2683.28s)
I putting it together like open source
[44:44] (2684.64s)
was clearly one thing this new
[44:46] (2686.56s)
collaborative workflow especially with
[44:48] (2688.40s)
open source but also and I think one
[44:50] (2690.16s)
thing you didn't mention but I I wonder
[44:51] (2691.76s)
if you're if it is a a part is how even
[44:54] (2694.48s)
if you use GitHub you can always move to
[44:56] (2696.40s)
your own git server. It's very easy to
[44:58] (2698.00s)
migrate. It also works offline. So even
[45:00] (2700.96s)
if GitHub is offline, like yes, it's a
[45:02] (2702.96s)
central hub, but if there's a GitHub
[45:04] (2704.64s)
outage, I mean, we're not happy about it
[45:06] (2706.24s)
and people complain these days and
[45:07] (2707.60s)
there's not many of them to be fair. But
[45:09] (2709.44s)
even when that happens, I mean, oh, I
[45:11] (2711.68s)
guess I can keep working locally like I
[45:14] (2714.80s)
can keep pushing. So you might not if it
[45:16] (2716.80s)
if it's just again if it's just like a
[45:18] (2718.96s)
30-cond outage or a 1 minute one. Again,
[45:21] (2721.28s)
not advocating for it, but you might not
[45:23] (2723.12s)
even notice because you're you're just
[45:25] (2725.20s)
like doing your local thing. I I I I I
[45:27] (2727.68s)
think as developer like I think we
[45:29] (2729.28s)
appreciate when we know we are not
[45:30] (2730.72s)
locked into well by the way it's free
[45:32] (2732.32s)
like a lot of the the sorry not not
[45:34] (2734.72s)
GitHub per se but for open source it was
[45:36] (2736.64s)
always free right it was always free for
[45:38] (2738.56s)
open source um and in you you might say
[45:41] (2741.92s)
GitHub invented a version of the fremium
[45:44] (2744.40s)
model that is not adbased right
[45:46] (2746.16s)
traditionally fremium is adbased the
[45:48] (2748.16s)
free users get it uh get something for
[45:50] (2750.72s)
free with advertisement and then the
[45:52] (2752.56s)
paid users get get rid of the
[45:53] (2753.92s)
advertisement and get more features
[45:56] (2756.08s)
GitHub originally had the separation
[45:57] (2757.92s)
between everything you do in public as
[45:59] (2759.52s)
free because it helps the community
[46:01] (2761.44s)
obviously helps the social network quote
[46:03] (2763.44s)
unquote yes or GitHub growing and then
[46:06] (2766.56s)
when you wanted private repositories um
[46:08] (2768.80s)
you had to pay for them. Um a shortly
[46:11] (2771.12s)
after the acquisition early 2019 we
[46:13] (2773.60s)
changed that and instead of paying uh
[46:16] (2776.08s)
for private repositories we actually
[46:17] (2777.68s)
made private repositories free as well
[46:19] (2779.60s)
because we had a lot of uh uh individual
[46:21] (2781.52s)
developers giving us feedback. Um
[46:23] (2783.52s)
especially you know when you travel
[46:24] (2784.80s)
around the world um for an American $4 a
[46:27] (2787.68s)
month might not be a lot. Um but for
[46:29] (2789.68s)
somebody in a different country that
[46:30] (2790.96s)
that is a much more money uh relative to
[46:34] (2794.00s)
their income. And so we were private
[46:35] (2795.68s)
repository free. And today we charge for
[46:37] (2797.92s)
what you could call enterprise features
[46:39] (2799.76s)
like single sign on or branch protection
[46:42] (2802.24s)
things that a student or hobbyist you
[46:45] (2805.04s)
know probably doesn't need. If I'm
[46:46] (2806.88s)
honest when I work on my hobby projects
[46:49] (2809.20s)
I barely write any tests. I certainly
[46:51] (2811.44s)
don't send myself a pull request you
[46:53] (2813.28s)
know to review my own code. I just merge
[46:55] (2815.84s)
push into main blanch and that's cool.
[46:58] (2818.00s)
And so but yeah GitHub innovated in this
[47:00] (2820.16s)
in the business model space as well. And
[47:01] (2821.92s)
you know you mentioned uh that the the
[47:05] (2825.04s)
scenarios where it's helpful to use
[47:06] (2826.64s)
GitHub or Git on on your local machine.
[47:09] (2829.52s)
Um in 2007 2008 flights didn't have
[47:12] (2832.64s)
Wi-Fi at least in my memory.
[47:16] (2836.00s)
Wi-Fi wasn't like have Wi-Fi as far as I
[47:19] (2839.60s)
remember. I don't know if Starbucks
[47:20] (2840.96s)
maybe Starbucks already had it but like
[47:23] (2843.04s)
there was much more places where you
[47:24] (2844.48s)
would work just local on your machine uh
[47:26] (2846.88s)
for for quite a while and and and being
[47:29] (2849.04s)
able to commit into the repository.
[47:31] (2851.36s)
There wasn't, you know, subversion
[47:32] (2852.56s)
didn't have a push. It had uh you would
[47:34] (2854.24s)
always commit into the into the upstream
[47:36] (2856.64s)
uh change planes you know roll back all
[47:39] (2859.44s)
these operations that are now natural um
[47:42] (2862.08s)
with git that weren't natural in in
[47:45] (2865.28s)
2007208.
[47:46] (2866.96s)
So, so it gets GitHub started off it
[47:48] (2868.96s)
started to get real big traction 2008,
[47:51] (2871.28s)
2009, 2010. The next big kind of
[47:54] (2874.32s)
milestone I remember from developers
[47:55] (2875.92s)
perspective is until then to use GitHub
[47:58] (2878.56s)
you you could use the web version and
[48:00] (2880.40s)
you use the local command line
[48:01] (2881.84s)
interface. You just learned all the
[48:03] (2883.12s)
commands you know there books about like
[48:04] (2884.96s)
the easy ones are easy and then like
[48:06] (2886.72s)
cherrypicking and all that. I was always
[48:08] (2888.32s)
confused by that. Uh and then in around
[48:11] (2891.84s)
2014 was the first time that GitHub
[48:14] (2894.32s)
actually released desktop applications.
[48:16] (2896.64s)
But not only did it release desktop
[48:18] (2898.40s)
applications, it actually released the
[48:19] (2899.84s)
Atom text editor which I loved. I used
[48:22] (2902.08s)
it for so long. It was a lightweight
[48:23] (2903.44s)
editor. It it released the Electron
[48:25] (2905.52s)
framework which powered Atom and then
[48:27] (2907.92s)
and then GitHub desktop in 2014 2015.
[48:31] (2911.60s)
Why why do you think GitHub waited that
[48:34] (2914.16s)
long to have these desktop applications?
[48:36] (2916.00s)
What what what was the goal with atom
[48:37] (2917.60s)
and and how how did this help? Did it
[48:39] (2919.36s)
actually help like get more people who
[48:41] (2921.12s)
just liked a nice user interface and
[48:42] (2922.88s)
were not the command types? I don't know
[48:44] (2924.40s)
the history of of all these apps. My my
[48:46] (2926.88s)
suspicion is that um you know when you
[48:49] (2929.20s)
say waited this long, I'd make the
[48:50] (2930.96s)
counter argument how long is long for a
[48:53] (2933.76s)
startup to move from one core product to
[48:56] (2936.24s)
having multiple other products that may
[48:58] (2938.16s)
or may not become a distraction. I I
[49:00] (2940.64s)
think each of those solved a specific
[49:02] (2942.96s)
problems that that the team saw. Um Adam
[49:06] (2946.16s)
um came out you know I think a year or
[49:08] (2948.48s)
so before VS code launched and security
[49:12] (2952.08s)
the time was VIP you know for a new
[49:14] (2954.56s)
generation of idees of both of them were
[49:17] (2957.76s)
open source you know for the acquisition
[49:19] (2959.60s)
they they both ended in the same company
[49:21] (2961.44s)
and then OB made the decision uh to
[49:23] (2963.60s)
continue our journey on VS code and and
[49:25] (2965.52s)
retire atom but it goes back to this
[49:28] (2968.24s)
developer first culture it goes back to
[49:30] (2970.32s)
GitHub's origins where you would join as
[49:32] (2972.48s)
an employee and you wouldn't have a
[49:34] (2974.24s)
manager you wouldn't have a backlog. He
[49:36] (2976.08s)
would have the so so back then really
[49:37] (2977.84s)
there were no managers. There were no
[49:39] (2979.36s)
well there was obviously a CEO and like
[49:41] (2981.44s)
a little bit but that was very flat and
[49:43] (2983.76s)
and people when they when they
[49:45] (2985.52s)
onboarding was always at headquarters.
[49:47] (2987.12s)
So even though as a remote first company
[49:48] (2988.56s)
you would spend a week or so in our
[49:50] (2990.64s)
headquarters in San Francisco and you
[49:52] (2992.16s)
learned how to make an an espresso. Uh
[49:55] (2995.04s)
and that was literally one of the
[49:56] (2996.24s)
onboarding videos and you know they got
[49:59] (2999.36s)
to have some some whimsical future.
[50:01] (3001.84s)
Yeah. Whimsical culture. um and um you
[50:05] (3005.20s)
got told you know pick pick something
[50:07] (3007.20s)
that you're interested in and and that
[50:09] (3009.28s)
naturally leads you know to developers
[50:11] (3011.44s)
uh picking things that they want to
[50:13] (3013.28s)
solve for themselves that they care
[50:14] (3014.72s)
about and so Adam um was actually you
[50:17] (3017.36s)
know Chris Wrat uh the CEO at the time
[50:21] (3021.36s)
and then for most of GitHub's journey
[50:22] (3022.64s)
until the acquisition um was one of the
[50:25] (3025.52s)
you know core maintainers of the Alen
[50:28] (3028.00s)
project and um and so I think about CEO
[50:32] (3032.16s)
being a core maintainer a lot of that
[50:34] (3034.08s)
was about the passion of of the people
[50:35] (3035.84s)
working there. I don't know exactly the
[50:37] (3037.44s)
history of desktop but my assumption
[50:39] (3039.20s)
there would be that uh they saw a need
[50:41] (3041.44s)
to expand the people that can use GitHub
[50:44] (3044.64s)
uh without knowing all the intricacies
[50:46] (3046.64s)
of of git. Um in many ways you know the
[50:49] (3049.36s)
GitHub user interface on github.com also
[50:52] (3052.08s)
serve that purpose. If you think for
[50:54] (3054.16s)
example about blame uh views um blame on
[50:57] (3057.20s)
g.com is just clicking a button see who
[50:59] (3059.52s)
modified which file which line in the
[51:02] (3062.08s)
file. while if you do get blame on the
[51:03] (3063.76s)
comment line, it's um much much harder
[51:06] (3066.32s)
to to figure out what's what. Uh
[51:08] (3068.16s)
especially if you don't know a lot about
[51:10] (3070.16s)
software development. So, it's all about
[51:12] (3072.24s)
um growing the user base uh and
[51:14] (3074.08s)
expanding the people that um get get,
[51:16] (3076.64s)
you know, utility um out of I'll say
[51:18] (3078.80s)
that I I I use GitHub desktop a lot. I
[51:20] (3080.80s)
mean, every is different and I know how
[51:22] (3082.16s)
to use command line, but I just like
[51:23] (3083.84s)
that I don't have to think about it
[51:25] (3085.60s)
again. So, like I I I appreciate it when
[51:27] (3087.84s)
when it came out. I barely use it but uh
[51:30] (3090.08s)
I use you know the Git integration
[51:31] (3091.76s)
GitHub integration in VS code a lot um
[51:34] (3094.08s)
for the same purpose and so there's and
[51:36] (3096.16s)
I think even that you know git um as a
[51:39] (3099.04s)
protocol um with SSH access and HTTP
[51:41] (3101.76s)
access which also by the way wasn't
[51:43] (3103.68s)
something that was very prevalent in the
[51:46] (3106.64s)
early days of GitHub um and is now much
[51:49] (3109.12s)
more used um because it's easier to
[51:50] (3110.80s)
access through HTTP than than through
[51:52] (3112.80s)
SSH um I think all of these pieces you
[51:55] (3115.84s)
know they're ultimately helping you
[51:58] (3118.16s)
know, to create the developer experience
[51:59] (3119.52s)
that we now consider normal, but by no
[52:02] (3122.40s)
means was normal uh 20 years ago. So
[52:04] (3124.88s)
then we're getting to the Microsoft
[52:07] (3127.20s)
acquisition. So we've now passed 2015,
[52:09] (3129.76s)
it's now 2016 or or so. You were in the
[52:12] (3132.48s)
inside of Microsoft. You were already
[52:14] (3134.16s)
working there. How did this come about?
[52:16] (3136.40s)
What was Microsoft thinking? Why was
[52:18] (3138.88s)
even Microsoft interested in GitHub? And
[52:21] (3141.52s)
then, you know, how did the the purchase
[52:23] (3143.28s)
go from from your perspective? It was
[52:25] (3145.20s)
2018, early 2018. um that um back then N
[52:29] (3149.92s)
freeri my boss within Microsoft um CDP
[52:32] (3152.88s)
in a developer division doing mobile
[52:34] (3154.80s)
developer tools Nat came uh from from
[52:37] (3157.28s)
Zamarin so had joined uh Microsoft
[52:39] (3159.44s)
himself when acquisition I had joined
[52:40] (3160.96s)
for the hockey app acquisition so we
[52:42] (3162.64s)
were like a bit of a you know outside in
[52:45] (3165.60s)
team within Microsoft with lots of
[52:47] (3167.20s)
people coming from companies lots of um
[52:49] (3169.76s)
you know cloud native experience um a
[52:53] (3173.04s)
non-traditional stack for Microsoft but
[52:55] (3175.36s)
at the same time also Microsoft had
[52:57] (3177.20s)
changed. Um it was now about four years
[52:59] (3179.68s)
uh since Satya Nadella had become the
[53:01] (3181.92s)
CEO. Satya had very early on embraced
[53:04] (3184.96s)
open source. You know then then VS code
[53:07] (3187.52s)
uh was launched umn net became um open
[53:10] (3190.56s)
source. So a number of steps had
[53:12] (3192.64s)
happened where Microsoft changed um its
[53:15] (3195.28s)
fundamental position on how it views
[53:17] (3197.92s)
open source how it views you know uh the
[53:20] (3200.16s)
stack and and where the future is going.
[53:22] (3202.40s)
Uh you may remember this part of the
[53:24] (3204.40s)
strategy back then was cloud first,
[53:26] (3206.40s)
mobile first. Um and um you know in many
[53:30] (3210.24s)
ways that is still true today. We're not
[53:32] (3212.48s)
no longer saying um those those two
[53:34] (3214.96s)
things. You know if you think about how
[53:36] (3216.72s)
you interact with Microsoft products
[53:38] (3218.40s)
today,
[53:40] (3220.00s)
you know on every device um regardless
[53:42] (3222.16s)
of who makes the device, what operating
[53:44] (3224.00s)
system, this was not obvious then
[53:45] (3225.60s)
because it was still Windows first.
[53:47] (3227.04s)
There was still a feeling that Microsoft
[53:48] (3228.64s)
is only Windows and yeah and and I heard
[53:51] (3231.36s)
this was said everywhere and I think
[53:52] (3232.72s)
outside of we were skeptical honestly
[53:55] (3235.44s)
but you know then obviously the cloud
[53:57] (3237.44s)
stack the compute stack that that
[53:58] (3238.88s)
Microsoft offers today not only to its
[54:01] (3241.36s)
own products but to any company in the
[54:04] (3244.24s)
industry really one thing I learned
[54:05] (3245.92s)
early in my journey at Microsoft is that
[54:08] (3248.24s)
when you're a small startup you you
[54:10] (3250.96s)
consider you know other companies in the
[54:12] (3252.72s)
space competitors and they're you know
[54:14] (3254.72s)
quote unquote the enemy um At Microsoft
[54:17] (3257.60s)
competitors are at the same time also
[54:19] (3259.92s)
customers and often partners. We are
[54:22] (3262.32s)
providing you know if you take for
[54:23] (3263.60s)
example Azure IA foundry our inference
[54:26] (3266.40s)
stack for large language models we're
[54:28] (3268.16s)
providing those not only to our own uh
[54:30] (3270.00s)
co-pilots we're providing those to many
[54:31] (3271.76s)
other companies that may uh directly or
[54:34] (3274.24s)
indirectly compete uh uh uh with GitHub
[54:36] (3276.88s)
or with with other Microsoft products.
[54:38] (3278.32s)
Right? So and so 2018 the world view in
[54:41] (3281.20s)
Microsoft had changed. I think the
[54:42] (3282.64s)
reputation started to change. Um we at
[54:45] (3285.52s)
Microsoft started to believe that we
[54:47] (3287.60s)
could pull off an acquisition like
[54:49] (3289.52s)
GitHub where you you know make GitHub
[54:51] (3291.60s)
part of Microsoft and and and not lose
[54:53] (3293.92s)
all the open source maintainers because
[54:55] (3295.84s)
they like Microsoft you know is not
[54:58] (3298.72s)
going to be good steward um of GitHub
[55:01] (3301.12s)
and we set very early on clear
[55:03] (3303.52s)
principles of what that looks like and
[55:05] (3305.36s)
2018 was about two years after the
[55:07] (3307.20s)
LinkedIn acquisition a bit longer since
[55:09] (3309.44s)
the Minecraft acquisition so we had kind
[55:11] (3311.36s)
of like two examples of acquisitions
[55:13] (3313.52s)
where kept the brand and the platform uh
[55:16] (3316.64s)
independent. Um even even today when you
[55:19] (3319.20s)
go to to the LinkedIn homepage, you
[55:21] (3321.44s)
don't see a lot of Microsoft there. Um 7
[55:24] (3324.32s)
years after the GitHub acquisition, uh
[55:26] (3326.24s)
there's there's no Microsoft on the
[55:28] (3328.16s)
GitHub homepage. um unless you're using
[55:30] (3330.56s)
uh Entra ID um you know as your as your
[55:32] (3332.80s)
single sign on provider or of course we
[55:35] (3335.12s)
have blog posts where we talk about um
[55:36] (3336.96s)
you know copilot and and the Microsoft
[55:39] (3339.28s)
model and and things like that and
[55:41] (3341.52s)
Minecraft is you know many kids I think
[55:44] (3344.08s)
realize much later you know in their
[55:46] (3346.40s)
childhood that one of their favorite
[55:48] (3348.16s)
games is actually the same uh company
[55:50] (3350.40s)
that also produces the operating system
[55:52] (3352.40s)
and the professional network and and
[55:54] (3354.80s)
GitHub right but part of when you know
[55:57] (3357.20s)
when you look at those two acquisitions
[55:58] (3358.72s)
and then you see GitHub it it feels like
[56:00] (3360.72s)
a natural consequence like the natural
[56:03] (3363.28s)
next step for Microsoft to go down that
[56:05] (3365.84s)
path. Microsoft always has been a
[56:07] (3367.84s)
developer first company you know first
[56:10] (3370.64s)
product was basic for the alter and and
[56:12] (3372.48s)
you know here at the conference center I
[56:13] (3373.68s)
don't know if you 1975 experience where
[56:16] (3376.72s)
you work on a fake alter and uh and pass
[56:20] (3380.00s)
some coding tests um you know then that
[56:22] (3382.24s)
was basic for the Apple 2 and and and
[56:24] (3384.16s)
obviously Visual Studio in in 1990s uh I
[56:27] (3387.28s)
think my first version of Visual Studio
[56:28] (3388.96s)
was Visual C 1.0 zero came with a book
[56:32] (3392.00s)
uh and then had Visual J which was like
[56:34] (3394.08s)
Microsoft's Java clone and then then I
[56:36] (3396.32s)
bought like a full scale Visual Studio 7
[56:39] (3399.60s)
for way too much money uh back then uh
[56:42] (3402.64s)
at least you know for where I was as a
[56:44] (3404.24s)
as a high school student right obviously
[56:45] (3405.92s)
uh in today's world uh selling an IDE at
[56:49] (3409.20s)
a onetime price would be something that
[56:50] (3410.96s)
that is has no has no market fit anymore
[56:53] (3413.36s)
you know Microsoft lacked access to the
[56:55] (3415.60s)
open source uh ecosystem it it it didn't
[56:59] (3419.60s)
have, you know, the same attraction to
[57:02] (3422.16s)
cloud native developers.
[57:04] (3424.72s)
It was just being not trending at all.
[57:07] (3427.28s)
Yeah. And and and it was important from
[57:09] (3429.12s)
a business perspective to to have that
[57:11] (3431.04s)
ecosystem. It was important for us, you
[57:13] (3433.04s)
know, to put developers first again. And
[57:15] (3435.92s)
so that was actually the first principle
[57:17] (3437.68s)
um of of three principles. And we
[57:19] (3439.68s)
believed we can reacelerate GitHub
[57:22] (3442.08s)
because GitHub in 2018 had a bit of the
[57:24] (3444.72s)
reputation of not being able to innovate
[57:26] (3446.96s)
anymore for for various reasons and we
[57:29] (3449.76s)
can we can talk about that as more in
[57:31] (3451.52s)
detail but it was really important to
[57:33] (3453.44s)
think about this acquisition not a
[57:35] (3455.44s)
Microsoft gets a lot out of GitHub but
[57:37] (3457.68s)
Microsoft is willing to invest into
[57:39] (3459.44s)
GitHub. you know, GitHub in 2018 at the
[57:41] (3461.76s)
time you started the conversations with
[57:43] (3463.04s)
them was about 700 employees all up and
[57:46] (3466.48s)
you mentioned earlier it's now over
[57:47] (3467.92s)
3,000 employees. So that investment
[57:50] (3470.08s)
surely has happened and we have
[57:52] (3472.16s)
leveraged you know a lot of the
[57:53] (3473.36s)
Microsoft stack and copilot comes to
[57:55] (3475.20s)
mind where we're using Azure AI foundry
[57:57] (3477.12s)
and the relationship with open AI you
[57:59] (3479.12s)
know to to to build our our AI code
[58:02] (3482.16s)
generation product and then the last one
[58:03] (3483.60s)
was of course also Microsoft wanted
[58:05] (3485.44s)
something back and so GitHub accelerate
[58:07] (3487.12s)
Microsoft and the easy answer there is
[58:09] (3489.44s)
how did we achieve that by growing
[58:11] (3491.36s)
revenue um and um you know we announced
[58:13] (3493.92s)
last July um so about a year ago now
[58:16] (3496.64s)
that revenue has grown to over 2 billion
[58:19] (3499.36s)
annual recurring revenue run rate. uh
[58:21] (3501.84s)
and that you know keeps going and we're
[58:23] (3503.52s)
very happy with these business result
[58:25] (3505.20s)
you know contributing back to to
[58:26] (3506.64s)
Microsoft's earnings right but in that
[58:28] (3508.56s)
order right like developers first making
[58:30] (3510.56s)
great developer products accelerate
[58:32] (3512.08s)
GitHub and then eventually GitHub you
[58:34] (3514.16s)
know accelerating Microsoft and and
[58:35] (3515.92s)
giving back both on the product side
[58:37] (3517.36s)
with copilot or on the revenue side with
[58:39] (3519.04s)
with our results but I I think this is
[58:41] (3521.04s)
this last thing is just worth
[58:42] (3522.64s)
emphasizing in the sense that I think as
[58:44] (3524.56s)
a developer I I really like that I I
[58:47] (3527.20s)
like using products where I know they'll
[58:48] (3528.64s)
be around so you're saying that you know
[58:50] (3530.32s)
GitHub's revenue has been consistently
[58:52] (3532.16s)
going up. More enterprises, more more
[58:53] (3533.84s)
more companies, more more teams paying
[58:55] (3535.68s)
for sort of professional use cases,
[58:57] (3537.68s)
right, to help their work. If I remember
[58:59] (3539.04s)
correctly, 2017 uh was the last official
[59:02] (3542.56s)
revenue announcement that GitHub made
[59:04] (3544.16s)
before the acquisition and they were at
[59:05] (3545.84s)
about 200 million run rate and they
[59:08] (3548.16s)
announced at that time that they're
[59:10] (3550.00s)
looking for a new CEO. So Chris was was
[59:12] (3552.24s)
ready to step down and then that
[59:13] (3553.92s)
ultimately you know resulted in the
[59:15] (3555.84s)
acquisition then in June 2018 through an
[59:18] (3558.64s)
acquisition and a new CEO net net
[59:20] (3560.48s)
freman. Uh but like 2017 you know 200
[59:23] (3563.84s)
million to 2024 in seven years um
[59:27] (3567.28s)
revenue went up factor 10. Yeah. Well
[59:29] (3569.92s)
this is which is also it's kind of
[59:31] (3571.92s)
reassuring to hear that because there's
[59:34] (3574.08s)
always a risk like we know Microsoft is
[59:35] (3575.76s)
a for-profit company. It you know like
[59:38] (3578.24s)
such an adult report to shareholders.
[59:40] (3580.00s)
It's good to know that those those
[59:41] (3581.20s)
things are are going well as well. Well,
[59:42] (3582.96s)
and and I think you know the for a long
[59:45] (3585.04s)
time developer tools were not seen as a
[59:48] (3588.56s)
as a as a revenue driver in the in the
[59:51] (3591.04s)
industry. I think you know there were a
[59:52] (3592.48s)
few examples like companies in Jet
[59:55] (3595.04s)
Brains comes to mind or JROG there's a
[59:57] (3597.20s)
bunch of companies that you know we're
[59:59] (3599.04s)
focusing on developer tools but I think
[60:01] (3601.60s)
you know if you if you try time travel
[60:03] (3603.52s)
back five years uh or before that give
[60:06] (3606.24s)
let's say seven and a half years and we
[60:07] (3607.60s)
talk with venture capitalists about an
[60:09] (3609.12s)
idea that we have you and I about a
[60:10] (3610.96s)
developer tool startup they're going to
[60:12] (3612.24s)
tell you you need something else beyond
[60:14] (3614.48s)
just developer tools because that's
[60:16] (3616.08s)
where the big money is and today this
[60:18] (3618.16s)
world obviously has dramatically changed
[60:19] (3619.76s)
absolutely but as I was talking with
[60:21] (3621.28s)
Scott Guthrie. The interesting thing was
[60:22] (3622.80s)
that the last company that was able to
[60:24] (3624.56s)
make develop developers pay for
[60:26] (3626.48s)
developer tools a lot of money. We're
[60:28] (3628.00s)
talking thousands of dollars was
[60:29] (3629.52s)
Microsoft in the 2000s where this was
[60:32] (3632.32s)
pre when internet was small and
[60:33] (3633.92s)
developers didn't just pay for developer
[60:35] (3635.44s)
tools but they pay for MSD and
[60:36] (3636.88s)
documentation for access to the latest
[60:39] (3639.20s)
software and you know that time has
[60:41] (3641.20s)
passed and we were talking about Scott
[60:42] (3642.80s)
on on some of the learnings but it's
[60:44] (3644.16s)
interesting how Microsoft figured that
[60:45] (3645.76s)
out. I feel Microsoft is very good at
[60:47] (3647.68s)
figuring out this great mix where again
[60:50] (3650.32s)
back then and I I worked at a Hungarian
[60:52] (3652.64s)
company. We paid about $1,000 per
[60:54] (3654.48s)
developer in Hungary because it made us
[60:56] (3656.72s)
so much more productive. So we we'll get
[60:59] (3659.44s)
today I part on on this one but you
[61:01] (3661.60s)
mentioned something interesting which I
[61:03] (3663.28s)
also noticed. So I looking back and I
[61:05] (3665.12s)
remember back it's when GitHub when
[61:06] (3666.72s)
GitHub desk came out it was great. I
[61:08] (3668.64s)
think I started to use GitHub more but
[61:10] (3670.48s)
then from like 2015 nothing really
[61:12] (3672.80s)
happened. Microsoft bought GitHub.
[61:14] (3674.64s)
Great. And I remember on online forums
[61:16] (3676.88s)
as well, people were saying like GitHub
[61:18] (3678.64s)
is not doing anything. And then the next
[61:20] (3680.48s)
thing I looked at the change log and the
[61:22] (3682.24s)
only notable thing I've seen shipped it
[61:24] (3684.24s)
started in 2021. Then the GitHub
[61:26] (3686.16s)
sponsors came out, the package registry,
[61:28] (3688.32s)
C-pilot, code spaces. But what happened
[61:31] (3691.04s)
there from 2015 to 2020? It almost felt
[61:33] (3693.20s)
like from I'm I'm sure people were
[61:35] (3695.12s)
working, but from the outside it just
[61:36] (3696.48s)
looked like nothing, like bare land and
[61:38] (3698.72s)
more people being hired. And you alluded
[61:40] (3700.64s)
to this. what was going on behind the
[61:42] (3702.24s)
scenes. I mean, obviously the time
[61:44] (3704.24s)
before Microsoft, you know, 2015 to
[61:46] (3706.24s)
2018, I only have hearsay and a little
[61:48] (3708.64s)
bit of insight. I think a big problem
[61:51] (3711.44s)
that GitHub had um especially before the
[61:54] (3714.08s)
Microsoft acquisition and you know, for
[61:56] (3716.00s)
some time after that was that um the
[61:58] (3718.80s)
platform had grown so much um and so
[62:01] (3721.20s)
many people were relying on it being
[62:03] (3723.36s)
available and and not broken. Uh plus
[62:06] (3726.40s)
you know many developers did the big ben
[62:09] (3729.68s)
and still are very much in love with the
[62:12] (3732.24s)
brand like the the octoat you know
[62:14] (3734.80s)
internally we call it Mona how do you
[62:16] (3736.32s)
call it Mona like Mona Lisa you know
[62:18] (3738.96s)
Mona um is is something that is
[62:22] (3742.00s)
recognized you get you get asked about
[62:24] (3744.00s)
it on the street or like in a coffee
[62:25] (3745.84s)
shop or in the Lego store because
[62:27] (3747.28s)
obviously the employees there are often
[62:29] (3749.12s)
also college students and and have been
[62:30] (3750.80s)
in I mean I've been you know I had a you
[62:33] (3753.12s)
know on on an airplane the crew member
[62:35] (3755.36s)
asking about GitHub and I'm like how do
[62:36] (3756.72s)
you know GitHub and she's she was like
[62:38] (3758.48s)
well I you know used that it was that in
[62:40] (3760.40s)
college for for some you know computer
[62:42] (3762.32s)
science course that I took and and I
[62:44] (3764.08s)
think if you have something that is so
[62:46] (3766.72s)
beloved by the by the space that also
[62:48] (3768.88s)
means the expectations are really high
[62:50] (3770.64s)
like it's often that you know the
[62:51] (3771.92s)
disappointment is even bigger if you
[62:54] (3774.00s)
actually care about something while if
[62:55] (3775.76s)
you don't you know give a damn about
[62:57] (3777.52s)
this thing then whether it's up or down
[62:59] (3779.44s)
or whether it's broken doesn't really
[63:01] (3781.28s)
matter to you because you hate it anyway
[63:03] (3783.04s)
right and so I think those two things
[63:04] (3784.48s)
combined and led to, you know, people
[63:06] (3786.48s)
really being worried about shipping uh
[63:08] (3788.80s)
stuff because you would change something
[63:10] (3790.48s)
and the reaction from developers when
[63:12] (3792.72s)
you change something, whether it's the
[63:13] (3793.84s)
user interface or things work or hate
[63:16] (3796.08s)
limits and things like that is is often
[63:18] (3798.40s)
there's, you know, a loud minority
[63:21] (3801.76s)
yelling on the internet and and there's
[63:23] (3803.84s)
a silent majority that are actually fine
[63:25] (3805.60s)
with the change but don't say anything.
[63:27] (3807.04s)
And a small change might lead, you know,
[63:28] (3808.96s)
to an outage and then you're the one
[63:30] (3810.32s)
that made three languages of change in
[63:32] (3812.32s)
your first week and and you brought
[63:33] (3813.44s)
GitHub down. that's obviously not
[63:34] (3814.80s)
encouraging in your journey. So I think
[63:36] (3816.72s)
that you know created um an organization
[63:39] (3819.76s)
that um actually you still shipped a lot
[63:42] (3822.32s)
of things and what we call staff ship um
[63:44] (3824.16s)
what Microsoft called stock fooding.
[63:45] (3825.68s)
features that landed uh within the
[63:47] (3827.76s)
GitHub organization that that hubbers
[63:49] (3829.52s)
would see when they use you know one
[63:51] (3831.36s)
funny thing is um we have even today uh
[63:54] (3834.48s)
as we using GitHub every day I often
[63:56] (3836.80s)
actually don't know if that feature is
[63:59] (3839.20s)
available to you because I only see
[64:01] (3841.20s)
GitHub how a haba would see it and
[64:03] (3843.92s)
there's a way to disable all these
[64:05] (3845.28s)
features but how often well know I can
[64:08] (3848.40s)
hide the staff bar and then uh it
[64:10] (3850.40s)
disables the features that that you
[64:12] (3852.16s)
don't see but how often do you really do
[64:14] (3854.00s)
that and do you then remember that in a
[64:15] (3855.60s)
conversation that Ger doesn't have the
[64:17] (3857.44s)
feature but I have it and I I thought it
[64:19] (3859.44s)
already shipped but it is actually
[64:20] (3860.64s)
slated for next week. So I think that
[64:22] (3862.48s)
that created you know a culture whereas
[64:24] (3864.32s)
things were internally shipped um but
[64:26] (3866.24s)
but never made it uh you know to to
[64:28] (3868.48s)
public uh because everybody's worried is
[64:30] (3870.88s)
that is that good enough to to ship it
[64:32] (3872.96s)
you know CEO change uh uh was in flight
[64:35] (3875.28s)
there were a number of cultural issues
[64:36] (3876.64s)
and then uh as as we closed the deal and
[64:39] (3879.36s)
we came in u we made private repos uh uh
[64:41] (3881.92s)
public relatively fast. That that was a
[64:43] (3883.60s)
fast one. actually at that universe in
[64:46] (3886.00s)
in 2018 the first version of GitHub
[64:48] (3888.00s)
actions was announced. Uh that was even
[64:50] (3890.00s)
before the deal closed but it was you
[64:52] (3892.32s)
know hopefully the folks building it
[64:54] (3894.88s)
forgive me it was bit of a hack uh built
[64:57] (3897.20s)
on on top of containers in in uh in in
[65:00] (3900.08s)
Google cloud um and um we quickly saw
[65:02] (3902.80s)
from the data that the the product
[65:05] (3905.12s)
wasn't actually meeting the the
[65:06] (3906.80s)
requirements from developers many
[65:08] (3908.16s)
developers wanted full CI/CD while Git
[65:10] (3910.96s)
actions originally was designed was
[65:12] (3912.56s)
workflow automation and we kept that
[65:14] (3914.80s)
workflow automation part but evolved it
[65:16] (3916.72s)
into what it is now and over the course
[65:18] (3918.56s)
of 2019 19 at 2020. Sponsors was
[65:21] (3921.28s)
announced uh in mid 2019 at the last
[65:24] (3924.40s)
ever satellite conference in Berlin and
[65:26] (3926.64s)
then co came and that ruined kind of
[65:28] (3928.40s)
like the the plans that we had uh as we
[65:30] (3930.64s)
came back from it. You know, we were
[65:32] (3932.16s)
very careful with bringing back universe
[65:34] (3934.32s)
in a smaller scale. Um given that there
[65:36] (3936.48s)
was still lots of travel restrictions,
[65:37] (3937.92s)
but it took us a while, you know, to get
[65:40] (3940.00s)
the organization back into a state um
[65:42] (3942.96s)
where we could both innovate really fast
[65:45] (3945.44s)
and you know, keep uh the fundamentals
[65:47] (3947.68s)
in place. um keep security um
[65:49] (3949.92s)
availability um uh you know other things
[65:53] (3953.44s)
accessibility things that you might not
[65:55] (3955.12s)
actually see have changed um because you
[65:58] (3958.16s)
know if everything is working you don't
[65:59] (3959.84s)
notice it um but it you know created a
[66:02] (3962.48s)
lot of investment behind the scenes so
[66:03] (3963.92s)
we are we are feeling good about the
[66:05] (3965.92s)
pace of innovation that that we have
[66:07] (3967.60s)
today but yeah it to it took us a while
[66:09] (3969.44s)
to turn turn the ship around and you
[66:11] (3971.76s)
know even in a team of 700 people that
[66:13] (3973.60s)
takes a while and certainly with 3,000
[66:15] (3975.20s)
people that uh it is something that you
[66:17] (3977.28s)
know requires a lot of energy and and um
[66:20] (3980.00s)
and focus. I think it's just a good
[66:21] (3981.60s)
reminder from the outside a company that
[66:23] (3983.92s)
is doing great because GitHub I think
[66:25] (3985.60s)
all developers can agree from the
[66:27] (3987.04s)
outside it looked like is doing really
[66:28] (3988.80s)
good like yeah you can have some things
[66:31] (3991.04s)
that you need to work through right like
[66:32] (3992.48s)
like and growing too fast is is amazing
[66:34] (3994.96s)
I think the best problem for any team to
[66:36] (3996.64s)
have but it's still a problem right that
[66:38] (3998.72s)
that you need to solve and you get
[66:40] (4000.24s)
through it now co-pilot was the biggest
[66:43] (4003.68s)
flash that I can remember from the past
[66:45] (4005.84s)
few years clearly especially because
[66:47] (4007.52s)
when it came out it just felt so early
[66:49] (4009.20s)
was it was did the beta come out in 2022
[66:52] (4012.56s)
21 21 yes people came out 21 yeah beta
[66:55] (4015.12s)
came out in 2021 because it was built on
[66:57] (4017.76s)
an earlier model before Chad GPT
[67:00] (4020.48s)
launched it was on uh was it on GPT2 no
[67:03] (4023.92s)
it was um GP3 was the so GPD3 came out
[67:07] (4027.36s)
at the right after the build conference
[67:09] (4029.52s)
in 2020 which was obviously given given
[67:12] (4032.16s)
the pandemic uh fully remote uh but
[67:14] (4034.96s)
Kevin Scott uh and some ament did a
[67:16] (4036.96s)
session about transformers and Dutch
[67:18] (4038.48s)
language models and then after that GP3
[67:21] (4041.52s)
uh got into into the preview and and we
[67:23] (4043.68s)
got access to that and through the
[67:25] (4045.12s)
OpenAI Microsoft partnership and and we
[67:27] (4047.36s)
realized uh together with OpenAI that it
[67:29] (4049.92s)
was able to to write decent code um in
[67:32] (4052.80s)
different programming languages and and
[67:34] (4054.40s)
wouldn't not mix up the syntax between
[67:36] (4056.32s)
you know Python, Ruby and JavaScript
[67:38] (4058.64s)
which uh somebody asked me that earlier
[67:40] (4060.72s)
this week was my biggest surprise that
[67:42] (4062.48s)
it can do that even though it doesn't
[67:44] (4064.56s)
have a compiler built in right like it
[67:46] (4066.80s)
it's not able to validate the code it
[67:48] (4068.40s)
generates um it doesn't have the syntax
[67:50] (4070.32s)
that just knows it from the the training
[67:52] (4072.32s)
set and then openAI fine-tuned a model
[67:55] (4075.60s)
that uh uh was called codeex. Yes, that
[67:58] (4078.56s)
was spec specific for these coding
[68:00] (4080.40s)
scenarios and uh in so in 2020 in August
[68:04] (4084.16s)
we wrote a paper with three ideas we had
[68:06] (4086.16s)
text to code to text as in describing
[68:08] (4088.48s)
code and conversational coding is what
[68:10] (4090.48s)
we called it which then you know today
[68:11] (4091.92s)
is known as chat and those two letter
[68:13] (4093.76s)
scenarios didn't work well enough uh we
[68:16] (4096.00s)
you know we had a describe code and
[68:17] (4097.44s)
sometimes it worked and often times it
[68:19] (4099.04s)
was wrong and you know how it is uh when
[68:20] (4100.88s)
developers see that that the description
[68:22] (4102.56s)
is not actually what the code does you
[68:24] (4104.40s)
quickly you know detract and you get a
[68:26] (4106.64s)
little uh net promoter score or whatever
[68:29] (4109.36s)
you're you're measuring satisfaction
[68:30] (4110.64s)
with. But but uh text to code as in you
[68:33] (4113.44s)
know prompting the model uh within the
[68:35] (4115.92s)
editor and and ultimately building auto
[68:37] (4117.60s)
completion that worked so well that very
[68:40] (4120.48s)
quickly we saw our internal you know uh
[68:43] (4123.04s)
uh hubbers adopting the tool giving it
[68:45] (4125.52s)
really high scores um saying you know
[68:47] (4127.52s)
this is great I want to keep using this
[68:49] (4129.12s)
I it's not the typical management says
[68:52] (4132.00s)
you have to use it and you don't want to
[68:54] (4134.40s)
but ultimately writing uh you know in
[68:56] (4136.72s)
the early days 25% of the code in those
[68:59] (4139.04s)
files it was enabled and then shortly
[69:00] (4140.96s)
there after that number got got into the
[69:03] (4143.36s)
50% range or 46% I think early 2023 and
[69:06] (4146.88s)
so that was the early days of co-pilot
[69:09] (4149.36s)
then June 2021 we went into the public
[69:11] (4151.36s)
preview h and within you know a few
[69:14] (4154.16s)
months uh the debate this had grown to a
[69:16] (4156.40s)
million users you saw more and more
[69:17] (4157.84s)
folks on social media saying well I was
[69:20] (4160.24s)
skeptical that this could ever work but
[69:22] (4162.80s)
it actually is good enough that I don't
[69:24] (4164.40s)
want to work without it anymore yeah cuz
[69:26] (4166.16s)
the surprising thing for me is every
[69:28] (4168.24s)
most of us remember the launch of Chad
[69:30] (4170.48s)
at GPC in November 2022 and everything
[69:33] (4173.28s)
exploded from there. It it was the
[69:34] (4174.80s)
product that that made people go wow
[69:37] (4177.12s)
inside tech outside tech and a lot of AI
[69:39] (4179.20s)
startups start up and a lot of actually
[69:40] (4180.72s)
coding startups started after that. So
[69:43] (4183.04s)
like in early 2023 however by that time
[69:45] (4185.28s)
get GitHub copilot was already I think I
[69:48] (4188.24s)
think it was beta in 2021 right but in
[69:51] (4191.20s)
2022 I think it was it became public so
[69:53] (4193.68s)
it was GA already available was
[69:56] (4196.72s)
generally available in June 2022 and it
[69:59] (4199.20s)
started charging for us for it for
[70:00] (4200.88s)
individuals in August 2022 and then chat
[70:03] (4203.52s)
GPT actually had two moments but one of
[70:05] (4205.84s)
them was um uh not noticed by many um so
[70:09] (4209.20s)
um OpenAI showed at Microsoft Ignite
[70:11] (4211.76s)
conference which is fall event showed
[70:14] (4214.08s)
actually CHPT in the keynote. Um it it
[70:16] (4216.40s)
wasn't called CHP but they called like
[70:18] (4218.48s)
they showed like a similar scenario uh
[70:20] (4220.72s)
that is what what you see now the agent
[70:22] (4222.96s)
doing where you we ask it to to to write
[70:24] (4224.88s)
some code and make modifications to our
[70:26] (4226.24s)
code and then it launched uh in in late
[70:28] (4228.48s)
November and the world changed for us
[70:30] (4230.72s)
dramatically. um uh for once because we
[70:33] (4233.36s)
had a product on market uh that was
[70:36] (4236.08s)
really good for developers and so our
[70:37] (4237.92s)
customer conversations shifted from us
[70:40] (4240.48s)
having to convince customers that AI is
[70:42] (4242.56s)
actually something they should look into
[70:44] (4244.32s)
to customers asking us to come and talk
[70:47] (4247.36s)
about how we build copilot how it can
[70:49] (4249.20s)
help their developers the first you know
[70:51] (4251.92s)
user studies come in we were um the
[70:53] (4253.92s)
first money the first company comparing
[70:56] (4256.00s)
a group without copilot with a group
[70:57] (4257.52s)
with copilot and and 5% number is
[71:00] (4260.00s)
obviously you
[71:02] (4262.16s)
both well known and and and often used
[71:04] (4264.88s)
today as a productivity improvement
[71:07] (4267.76s)
which was never intended to be. It's a
[71:09] (4269.84s)
case study in that one scenario. It made
[71:12] (4272.08s)
the developers 55% faster, right?
[71:13] (4273.84s)
There's lots of other things that
[71:15] (4275.12s)
developers do day in day out where you
[71:18] (4278.16s)
don't get the copilot make you that much
[71:19] (4279.84s)
faster. But it was a very exciting time
[71:21] (4281.36s)
and then in 2023 we launched chat uh
[71:24] (4284.32s)
GPD4 bought it into the CLI voice came
[71:27] (4287.36s)
out right. is a lot of these things feel
[71:29] (4289.92s)
like they have been around forever, but
[71:31] (4291.28s)
it's only been a little bit over two
[71:33] (4293.28s)
years. Totally been. And in 2023, uh on
[71:36] (4296.24s)
on a on a post from GitHub, uh I'm not
[71:40] (4300.00s)
sure if it was you, so I don't want to
[71:40] (4300.88s)
misog you, but but it was written that
[71:42] (4302.48s)
that just as GitHub was founded on Git,
[71:44] (4304.24s)
today we are sorry. So it was you
[71:46] (4306.56s)
writing it that just as GitHub was
[71:47] (4307.84s)
founded on Git, today we are refounded
[71:49] (4309.52s)
on Copilot. This was in 2023 and copilot
[71:52] (4312.08s)
was clearly very strong. What what has
[71:54] (4314.24s)
this change meant since then? And now
[71:56] (4316.80s)
it's been two years. This was at GitHub
[71:58] (4318.80s)
Universe 2023. So I think in that year
[72:01] (4321.20s)
the conference was in early November. Um
[72:03] (4323.68s)
uh it is our biggest event of the year
[72:05] (4325.20s)
and it was one of the lines in the
[72:06] (4326.80s)
keynote and I think in the press release
[72:08] (4328.16s)
or blog post and we talked a lot about
[72:09] (4329.92s)
the early days of GitHub, right? The
[72:11] (4331.52s)
GitHub founders did not invent Git. Um
[72:14] (4334.32s)
Linos to did but they realized there's a
[72:17] (4337.44s)
new technology that changes how
[72:19] (4339.28s)
developers work. not only to version
[72:20] (4340.96s)
their call their code but how they
[72:23] (4343.36s)
collaborate right GitHub if if you think
[72:25] (4345.68s)
about it GitHub is designed for
[72:28] (4348.56s)
asynchronous collaboration of developers
[72:30] (4350.96s)
that what GitHub is really all about and
[72:33] (4353.28s)
with copilot repeated history because we
[72:35] (4355.92s)
didn't invent transformers we didn't
[72:37] (4357.52s)
invent large language models we didn't
[72:39] (4359.76s)
train GP2 or three or codecs but um we
[72:43] (4363.60s)
saw something that changes how
[72:45] (4365.44s)
developers work and you know if you're
[72:47] (4367.84s)
honest um we saw an opportunity for
[72:50] (4370.00s)
ourselves to accelerate. Uh is you know
[72:52] (4372.40s)
my backlog is endless. Um there's lots
[72:54] (4374.80s)
of GitHub issues in repositories that
[72:57] (4377.20s)
were filed where the issue is issue was
[72:58] (4378.88s)
filed in 2014 with customer feedback and
[73:01] (4381.52s)
you know every enterprise seller since
[73:03] (4383.44s)
then you know posted on it. I have the
[73:06] (4386.24s)
same problem and it's not like we don't
[73:07] (4387.76s)
want to get to that issue but it's like
[73:09] (4389.36s)
there's also a thousand other things
[73:10] (4390.88s)
that are also high priority and and you
[73:13] (4393.84s)
mentioned security issues and
[73:15] (4395.20s)
availability and all these things are
[73:16] (4396.64s)
also high priority. when we saw uh GP3
[73:19] (4399.68s)
and then codeex we saw an opportunity to
[73:21] (4401.92s)
bring the effort down for all for own
[73:23] (4403.92s)
developers and of course every developer
[73:25] (4405.92s)
on the planet to to get more done not
[73:29] (4409.60s)
that you know they actually get to an
[73:31] (4411.04s)
empty backlog because I don't believe
[73:32] (4412.40s)
that because Javon's paradox means more
[73:34] (4414.96s)
ideas will get stacked in fact now we
[73:36] (4416.48s)
have all the AI ideas you know if you
[73:39] (4419.12s)
will now GitHub and Microsoft are closer
[73:42] (4422.16s)
together from the sense that Microsoft's
[73:43] (4423.84s)
developer division uh you know has for
[73:46] (4426.08s)
over 25 years produced idees and and
[73:48] (4428.40s)
copilot started as an IDE feature and
[73:50] (4430.88s)
while GitHub was the developed platform
[73:52] (4432.72s)
now those are you know the ven diagram
[73:54] (4434.72s)
of GitHub and VS code and NVS is is much
[73:57] (4437.84s)
more overlapping and we see that here at
[73:59] (4439.44s)
the conference and we see that in our
[74:00] (4440.72s)
day-to-day interaction between GitHub
[74:02] (4442.56s)
and and DevD and just on build you know
[74:05] (4445.36s)
like two big announcements related to to
[74:07] (4447.92s)
GitHub one is open sourcing co-pilot
[74:10] (4450.56s)
extension why did you decide to to do
[74:13] (4453.36s)
that and and also like what's the what's
[74:16] (4456.56s)
the idea here because we we have seen
[74:18] (4458.24s)
open sourcing with with VS Code. In
[74:19] (4459.84s)
fact, open sourcing VS Code gave way to
[74:22] (4462.96s)
some of the the competing editors that
[74:25] (4465.36s)
are are also adopted you know
[74:27] (4467.28s)
Windinserve cursor I think there there's
[74:29] (4469.36s)
there's some smaller ones as well. What
[74:31] (4471.04s)
what is your hope with this move and and
[74:33] (4473.20s)
and why? You know, it it feels
[74:34] (4474.64s)
counterintuitive because copilot has has
[74:37] (4477.60s)
kind of been an edge for Microsoft,
[74:39] (4479.04s)
right? Isn't it isn't it funny that it's
[74:40] (4480.96s)
it's counterintuitive? We live in a
[74:43] (4483.04s)
world now where Microsoft is embracing
[74:46] (4486.16s)
open source and is open sourcing its
[74:47] (4487.92s)
part while startups are taking open
[74:50] (4490.00s)
source, forking it, and making it closed
[74:51] (4491.52s)
source. Like this is like if you had
[74:53] (4493.76s)
told me that 10 years ago, you would
[74:55] (4495.84s)
have said you'll have it backwards,
[74:57] (4497.04s)
buddy. This is true, right? Curves on
[74:58] (4498.72s)
not open source. is that's not you know
[75:00] (4500.48s)
um and look you know that's we we
[75:01] (4501.92s)
published VS Code in in in 2015 under
[75:05] (4505.12s)
the MIT license um so the license allows
[75:07] (4507.68s)
it and of course people uh can do with a
[75:09] (4509.84s)
VS codebase what they want that's that's
[75:11] (4511.76s)
fair game and so we're stepping into our
[75:14] (4514.08s)
footsteps into our own footsteps
[75:16] (4516.48s)
footsteps uh of of VS Code over the last
[75:19] (4519.36s)
10 years and we felt the time is right
[75:22] (4522.16s)
um to bring the the copilot extension
[75:24] (4524.24s)
into the main uh editor uh codebase and
[75:27] (4527.28s)
that means it needs to be open source Um
[75:30] (4530.32s)
because we we made a promise to the
[75:32] (4532.40s)
community when we published VS Code that
[75:34] (4534.24s)
we will keep it open source. You
[75:36] (4536.08s)
mentioned we um co-piloted in 2021 2022.
[75:39] (4539.76s)
It didn't take long until people reverse
[75:41] (4541.60s)
engineered the VS code extension. It's
[75:43] (4543.76s)
at the end of the day JavaScript. Uh we
[75:46] (4546.08s)
write in Typescript but it's delivered
[75:47] (4547.52s)
as offiscated JavaScript. And so there's
[75:49] (4549.84s)
you still can find those those blog
[75:51] (4551.68s)
posts of how we compose the prompt, how
[75:54] (4554.64s)
long the prompt context window is, you
[75:56] (4556.48s)
know that we're using adjacent tabs. All
[75:58] (4558.08s)
that information is already out there,
[75:59] (4559.84s)
but you couldn't take that information
[76:01] (4561.92s)
and contribute back um or, you know,
[76:04] (4564.32s)
look at the codebase, learn from it, or
[76:06] (4566.48s)
take, you know, copilot and its APIs and
[76:08] (4568.80s)
its system prompt and put that into,
[76:11] (4571.20s)
let's say, code.org or you know the
[76:13] (4573.28s)
interview tool you're building because
[76:14] (4574.64s)
you want your applicants to use a
[76:16] (4576.40s)
copilot and maybe even show how they can
[76:18] (4578.72s)
sign in with GitHub at the same time and
[76:20] (4580.80s)
not give them the full VS code
[76:22] (4582.16s)
experience. You want that you know scope
[76:23] (4583.52s)
experience for an interview loop. So I
[76:25] (4585.28s)
think from our perspective it follows
[76:26] (4586.96s)
exactly the idea of open source which is
[76:28] (4588.96s)
you can learn from it, you can
[76:30] (4590.24s)
contribute to it, you can fork it, you
[76:31] (4591.68s)
can do whatever you want with it. Um it
[76:34] (4594.00s)
it ultimately helps the the developer
[76:36] (4596.16s)
community to have that piece of client
[76:38] (4598.08s)
code available. And you know now you're
[76:40] (4600.96s)
going to ask uh or I'm going to ask
[76:42] (4602.80s)
myself the question so where's the value
[76:44] (4604.48s)
generated and and aren't we losing uh
[76:47] (4607.20s)
all the revenue and we believe that the
[76:49] (4609.52s)
ultimate value generation for these AI
[76:51] (4611.36s)
tools is in the platform whether it's
[76:53] (4613.04s)
the the compute or inference layer um
[76:55] (4615.60s)
whether it's the security or control
[76:57] (4617.68s)
layer right enterprises want control
[76:59] (4619.36s)
what what model is enabled who can use
[77:01] (4621.76s)
uh AI you know in which project you
[77:04] (4624.16s)
might use AI given that you might have
[77:05] (4625.92s)
signed you know legal terms with with
[77:08] (4628.40s)
whoever provided your source code that
[77:09] (4629.76s)
you aren't using certain technology and
[77:13] (4633.04s)
um uh inference layer, the the security
[77:16] (4636.08s)
layer and at the collaboration layer
[77:17] (4637.84s)
where where people collaborate and you
[77:19] (4639.44s)
see that uh with with humanto human
[77:21] (4641.76s)
collaboration uh and we were going to
[77:23] (4643.76s)
see that with human to agent
[77:24] (4644.80s)
collaboration with our new coding agent.
[77:26] (4646.72s)
We're bringing that agent into the G
[77:28] (4648.88s)
platform and and we're giving it certain
[77:30] (4650.56s)
permissions and we are uh protecting the
[77:33] (4653.12s)
agent from doing things that you might
[77:34] (4654.80s)
you know allowed for a human but you
[77:36] (4656.56s)
want control over that when when the
[77:37] (4657.92s)
agent does it. I I do like looking back
[77:39] (4659.44s)
at the history of Microsoft. I do
[77:40] (4660.80s)
appreciate that Microsoft has been open
[77:43] (4663.76s)
always to the idea of being a platform
[77:45] (4665.68s)
but a good platform. So, for example,
[77:47] (4667.28s)
Jet Brains, you know, they they might
[77:49] (4669.12s)
disagree with this, but I remember the
[77:51] (4671.04s)
first time I bought a JetBrains project
[77:52] (4672.80s)
for $200 a year was this extension
[77:55] (4675.28s)
called ReSharper. So, Microsoft opened
[77:57] (4677.76s)
up their IDE to allow extension points
[77:59] (4679.84s)
and JetBrains honestly wrote a way
[78:01] (4681.60s)
better autocomplete than Microsoft
[78:03] (4683.04s)
themselves had and they made a bunch of
[78:04] (4684.88s)
money off of it and I think this helped
[78:06] (4686.48s)
them spin out these things. But when I
[78:08] (4688.08s)
look at let's say Apple's Xcode, the
[78:09] (4689.84s)
reason I don't like it and I'm very
[78:11] (4691.20s)
vocal about it, there is no extensions.
[78:12] (4692.96s)
I'm stuck with what it is. I would
[78:14] (4694.80s)
sometimes pay money for someone I
[78:16] (4696.96s)
cannot. So I I I just really like like
[78:19] (4699.28s)
how Microsoft seems to be keeping this
[78:21] (4701.92s)
idea of like sometimes opening up the
[78:24] (4704.40s)
business so others can succeed, startups
[78:26] (4706.24s)
can do it. It it's better for everyone
[78:27] (4707.92s)
especially as for developers just want
[78:29] (4709.76s)
better tools. As you mentioned Xcode, we
[78:31] (4711.36s)
actually have a co-pilot extension for
[78:33] (4713.20s)
Xcode. It's a bit of you know hackery
[78:35] (4715.36s)
given the extensions given the
[78:36] (4716.64s)
limitations. It's not as but it does
[78:38] (4718.72s)
have auto completion. last chat and just
[78:40] (4720.88s)
uh this week also we ship agent mode as
[78:42] (4722.96s)
a preview into the Xcode extension. We
[78:45] (4725.28s)
have it in the jet planes uh uh
[78:46] (4726.96s)
extension as well across all the
[78:48] (4728.72s)
different jet planes IDE. Uh we even
[78:50] (4730.88s)
bring it to Eclipse um uh and and that
[78:53] (4733.04s)
is in preview now including agent mode
[78:54] (4734.88s)
because if you look into you know larger
[78:57] (4737.28s)
companies uh they have developers on all
[79:00] (4740.16s)
of these um and and probably you know
[79:02] (4742.00s)
another dozen of other editors that
[79:04] (4744.32s)
developers prefer and where the company
[79:05] (4745.84s)
doesn't want to prescribe which IDE to
[79:08] (4748.24s)
use. But it is important for companies
[79:10] (4750.08s)
to standardize their engineering system
[79:12] (4752.16s)
stack and to have certain approved
[79:14] (4754.24s)
tools. Maybe it's just those maybe it's
[79:15] (4755.92s)
multiple of those. Obviously if you
[79:18] (4758.08s)
think about for example artifactory or j
[79:20] (4760.48s)
um often companies have that in the
[79:22] (4762.08s)
stack together with github or or hashi
[79:24] (4764.24s)
cop terraform and of course you have a
[79:26] (4766.08s)
cloud and a key key store secret store
[79:28] (4768.80s)
and then key value store and whatnot.
[79:30] (4770.40s)
But it is uh important to have uh copite
[79:32] (4772.88s)
available across all these IES and our
[79:34] (4774.80s)
export codec extension is already open
[79:36] (4776.72s)
source um was open source before this
[79:38] (4778.56s)
week uh because an open source
[79:40] (4780.24s)
maintainer voted uh and then we did a
[79:42] (4782.88s)
commercial agreement with that open
[79:44] (4784.40s)
source maintainer course to take it over
[79:46] (4786.40s)
right so we you know the maintainer
[79:48] (4788.48s)
benefited from it we benefited from it
[79:50] (4790.40s)
but so that means the system prompt the
[79:52] (4792.16s)
APIs all that you can already find in
[79:54] (4794.16s)
Xcode extension and so now we're we're
[79:56] (4796.48s)
continuing that journey uh with VS Code
[79:58] (4798.32s)
and others well the the last question I
[80:00] (4800.08s)
I wanted to touch on this is agent a
[80:03] (4803.84s)
agent mode or or gif agents was also an
[80:06] (4806.80s)
announcement and the agents are are
[80:08] (4808.08s)
getting more and more autonomous now as
[80:10] (4810.80s)
developers there is a bit of this fear
[80:12] (4812.96s)
there's some not necessarily Microsoft
[80:15] (4815.04s)
but there's this like vision of in the
[80:16] (4816.48s)
future as a software engineer you will
[80:17] (4817.68s)
manage all these agents and you'll be
[80:19] (4819.12s)
more of a manager than a software
[80:20] (4820.56s)
engineer and there's you know two things
[80:22] (4822.08s)
here a a fear of like are they taking
[80:24] (4824.64s)
away the parts of the work that I like
[80:27] (4827.12s)
even if not my job I'll have a job but
[80:28] (4828.80s)
it'll just seems like a boring job to be
[80:30] (4830.96s)
a manager and then the the other thing
[80:32] (4832.96s)
is what will happen with what could
[80:34] (4834.88s)
happen with uh with software engineering
[80:36] (4836.56s)
job and then you said earlier that you
[80:38] (4838.08s)
believe this will increase actually just
[80:39] (4839.92s)
just recently and in public. So what
[80:41] (4841.76s)
what is your view on on Asians and what
[80:43] (4843.92s)
advice would you give to software
[80:45] (4845.20s)
engineers who are you know want to say
[80:47] (4847.04s)
software engineers but obviously want to
[80:49] (4849.28s)
up level like how should we look at this
[80:50] (4850.96s)
thing because it feels like a freaking
[80:52] (4852.08s)
big change. I don't like the term
[80:53] (4853.52s)
autonomous because I think autonomous at
[80:55] (4855.76s)
least in my understanding means the
[80:57] (4857.44s)
thing figures out itself what it should
[80:59] (4859.60s)
work on. That's not how these things
[81:02] (4862.00s)
work. they have a level of autonomy when
[81:04] (4864.40s)
you assign a task to them of how they're
[81:06] (4866.08s)
implementing the task or but even that
[81:07] (4867.92s)
autonomy is restricted by uh the MCP
[81:11] (4871.68s)
service model context protocol that you
[81:13] (4873.60s)
configure for it or the tools you allow
[81:15] (4875.12s)
it to use or you know the repository you
[81:18] (4878.24s)
give it access to because obviously as
[81:20] (4880.40s)
an engineer as a human engineer uh I can
[81:23] (4883.28s)
look beyond the one repository boundary
[81:26] (4886.08s)
and see what has been happen in other
[81:27] (4887.60s)
repositories uh while the agent needs to
[81:30] (4890.80s)
get permission to do Right.
[81:33] (4893.36s)
So it's we're definitely far away from
[81:36] (4896.16s)
full self-driving. Uh if you take cars
[81:38] (4898.72s)
as a metaphor here, we're certainly
[81:40] (4900.56s)
getting into more driver assistance
[81:42] (4902.24s)
systems. And as developers, we have
[81:44] (4904.16s)
always automated whatever we can
[81:46] (4906.16s)
automate, right? A compiler is is a tool
[81:49] (4909.12s)
that helps me to not write assembler.
[81:51] (4911.28s)
Instead, I can write a much nicer
[81:52] (4912.72s)
language. Thank god. And but you know
[81:54] (4914.96s)
like I'm sure you know when compilers
[81:56] (4916.80s)
and then languages like basic and others
[81:58] (4918.64s)
were introduced there were also skeptics
[82:00] (4920.48s)
saying you know I'm losing control over
[82:03] (4923.12s)
the instruction set uh and the
[82:05] (4925.04s)
optimizations that I can do and my my
[82:06] (4926.96s)
app is so much faster and I certainly
[82:08] (4928.96s)
remember you know my my Commodore 64
[82:11] (4931.44s)
days when there was a very active demo
[82:13] (4933.76s)
scene and you couldn't really have a a
[82:15] (4935.92s)
successful demo especially as and I
[82:18] (4938.08s)
think even nowadays it exists where the
[82:19] (4939.68s)
size was limited back then through
[82:21] (4941.68s)
physical limitations today it's
[82:22] (4942.96s)
artificial right? Like you're limiting
[82:24] (4944.48s)
it because it do you want to create a
[82:26] (4946.24s)
challenge but you could only win those
[82:27] (4947.52s)
demo challenges if you knew how to do
[82:29] (4949.36s)
assembler and and and and you couldn't
[82:31] (4951.36s)
you couldn't win that in basic so agents
[82:33] (4953.60s)
will you know work as one of the tools
[82:35] (4955.92s)
that have developers have available um
[82:38] (4958.88s)
just like we have compilers linkers
[82:40] (4960.40s)
llinters and whatnot they will pick up
[82:42] (4962.80s)
tasks that I don't want to do like
[82:44] (4964.08s)
writing test cases I don't know many
[82:46] (4966.08s)
developers that want to write test cases
[82:47] (4967.60s)
and certainly not more than they have
[82:49] (4969.84s)
already written right like test unit
[82:51] (4971.44s)
testing is always a how How many do I
[82:53] (4973.60s)
write until I can get away with it when
[82:56] (4976.24s)
I go into cotal view that because there
[82:58] (4978.16s)
isn't like a right answer. It's like not
[82:59] (4979.84s)
a dozen and you're good. It's like how
[83:01] (4981.60s)
many you need is actually very is a very
[83:03] (4983.92s)
subjective thing. And those that try to
[83:07] (4987.68s)
holistically test all the edge cases um
[83:09] (4989.84s)
they they're never shipping actual
[83:11] (4991.60s)
valuable software. writing
[83:12] (4992.80s)
documentation, uh fixing security
[83:15] (4995.04s)
vulnerabilities, finding these security
[83:16] (4996.72s)
vulnerabilities when I didn't see them
[83:18] (4998.08s)
because I had a long day and I I you
[83:20] (5000.08s)
know I have obviously always my own uh
[83:22] (5002.64s)
bias that you know the code that I'm
[83:24] (5004.48s)
writing it does exactly what I want it
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to be until you have even something
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simple like a pull request description
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right like have the AI describe the work
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that you have done and all of a sudden
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it shows well Thomas broke the behavior
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it won't say it like that but like you
[83:38] (5018.00s)
know you get the idea Thomas changed the
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behavior of of of the checkout flow
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program like wait a second I didn't
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touch the checkout flow why why is this
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no change right because when it
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describes the code changes it doesn't
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have the confirmation bias that you
[83:50] (5030.80s)
yourself had when you would write your
[83:52] (5032.40s)
own description so I think we're heading
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into that world and now you have these
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let's say I start four agent flows I
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think that's what uh Jessica Dean did in
[84:00] (5040.24s)
the day two keynote um well but also you
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have all this code generated by all
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these agents I'm the one now having to
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validate that what the agent did is
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actually the thing that I'm willing to
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merge into my codebase and We all know
[84:12] (5052.16s)
that this gets harder the more open pull
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requests you have in different branches
[84:15] (5055.92s)
that might have merge conflicts by the
[84:17] (5057.76s)
time you're merging those things. So you
[84:19] (5059.68s)
got to understand all that code. You got
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to understand how the system is
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designed. You need to know what the
[84:25] (5065.12s)
agent did to be have the level of
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confidence, trust, you know, we talked
[84:28] (5068.80s)
about security, availability, all these
[84:30] (5070.40s)
things earlier. Scale. Um at the end of
[84:32] (5072.64s)
the day, most companies are for-profit
[84:35] (5075.04s)
organizations and even those that are
[84:36] (5076.40s)
nonprofit operating under budget. And so
[84:38] (5078.56s)
you need the agent to write code that
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solves a business problem and still
[84:41] (5081.76s)
makes you a healthy margin. It sounds
[84:44] (5084.08s)
like keep an open mind and experiment
[84:46] (5086.72s)
and see how they can help you. Right?
[84:48] (5088.72s)
The other thing that you know is I think
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super important to this is that we
[84:52] (5092.16s)
already seeing this paradox because now
[84:54] (5094.32s)
we have all the AI requirements that
[84:57] (5097.36s)
come on top of what a full sec engineer
[84:59] (5099.36s)
does, right? like no longer just back
[85:00] (5100.88s)
end and database and infrastructure and
[85:02] (5102.80s)
front end and how the front end
[85:04] (5104.08s)
communicates with the back end and you
[85:06] (5106.00s)
know at GitHub to give you give you one
[85:08] (5108.16s)
last data point is we are seeing 120,000
[85:12] (5112.16s)
API requests per second on an average
[85:14] (5114.96s)
day. Oh wow. That's seven per minute.
[85:17] (5117.12s)
That's uh 430 million per hour or 10
[85:21] (5121.12s)
billion per day, right? And that's API
[85:23] (5123.68s)
requests. And now that doesn't say is it
[85:25] (5125.44s)
a cheap API like you know listing the
[85:27] (5127.68s)
first 10 repos that you have or is it a
[85:29] (5129.76s)
GraphQL API that can take you know lots
[85:33] (5133.04s)
of complex queries to actually render
[85:34] (5134.56s)
the result right and so if you just take
[85:36] (5136.40s)
that example like you got to have
[85:39] (5139.04s)
engineering skills you got to have
[85:40] (5140.96s)
developed craft. You need senior people
[85:42] (5142.96s)
that know how to build large scale
[85:44] (5144.48s)
systems. You need people that take large
[85:46] (5146.32s)
complex problems, take break them down
[85:48] (5148.16s)
into smaller problems. Maybe they use AI
[85:49] (5149.84s)
along the way and say what's, you know,
[85:51] (5151.44s)
a good, you know, no SQL database,
[85:53] (5153.52s)
what's a good infrastructure, how do I
[85:55] (5155.44s)
do data residency, how do I do GDPR?
[85:57] (5157.84s)
That their job is going to be break it
[85:59] (5159.36s)
down to the to this to the layer where
[86:01] (5161.28s)
they now know now I can sign it to the
[86:03] (5163.36s)
agent that will provide high quality
[86:04] (5164.88s)
code without me having to reprompt it 15
[86:07] (5167.84s)
times. And then I can merge that into my
[86:09] (5169.76s)
codebase and move to the next task.
[86:11] (5171.60s)
That's that's what engineering is all
[86:13] (5173.20s)
about. The the coding skill will be part
[86:15] (5175.04s)
of that engineering skill set. But
[86:16] (5176.48s)
ultimately engineering means I can build
[86:18] (5178.56s)
a really large complex system and then
[86:20] (5180.24s)
evolve that and into even larger larger
[86:22] (5182.48s)
system you know next week in today's
[86:24] (5184.56s)
world.
[86:26] (5186.24s)
Love this takeaway abstractions and and
[86:28] (5188.64s)
being able to take on more complexity.
[86:30] (5190.40s)
This was a really good conversation.
[86:31] (5191.84s)
Yeah. Awesome. Really great to meet you
[86:33] (5193.36s)
Greg in person and looking forward to
[86:35] (5195.04s)
stay in touch. Thanks very much to
[86:36] (5196.48s)
Thomas for this conversation. The thing
[86:38] (5198.72s)
that struck with me most is how despite
[86:40] (5200.80s)
GitHub building AI tools like Copilot,
[86:43] (5203.20s)
Thomas very strongly believes that
[86:45] (5205.28s)
there's a lot of value in hiring junior
[86:47] (5207.12s)
engineers and he thinks that the future
[86:49] (5209.12s)
of software engineering will not be
[86:50] (5210.72s)
about autonomous AI agents but software
[86:53] (5213.68s)
engineers directing AI agents on what
[86:56] (5216.08s)
kind of work to do and staying in charge
[86:58] (5218.08s)
of this work. For more practical reading
[87:00] (5220.00s)
and listening to on AI engineering,
[87:01] (5221.92s)
check out deep dives from the pragmatic
[87:03] (5223.60s)
engineer linked in the show notes below.
[87:05] (5225.68s)
If you enjoy the show, it would mean a
[87:07] (5227.20s)
lot if you left the rating on the show
[87:08] (5228.48s)
on your podcast player. This helps more
[87:10] (5230.64s)
people discover the show. Thanks and see
[87:12] (5232.96s)
you in the next one.