Why Human Developers Remain Essential in Coding: Insights on AI-Generated Code

In recent discussions about the future of software development, a key question arises: Can AI replace human programmers? While AI has made strides in many fields, when it comes to generating code, the reality is more nuanced. Here’s an analysis based on industry observations and expert insights.

The Current State of AI-Generated Code

Attempts to have AI write code autonomously have so far fallen short of expectations. Instead of streamlining development, AI-generated code often introduces more bugs and security vulnerabilities. The code tends to be bloated, making it difficult to validate and maintain. This presents a serious challenge because validating code is essential to ensure reliability, security, and performance.

The Role of Senior Developers

Senior developers are critical in the software lifecycle, especially when it comes to validating and maintaining complex codebases. However, there’s a growing trend of experienced developers retiring or stepping back from projects where constant validation is required for AI-generated code that changes unpredictably with each update. The instability and unpredictability of AI-generated code can lead to frustration and burnout among these valuable experts.

Safety-Critical and Performance-Critical Code Needs Human Expertise

AI-generated code is particularly unsuitable for safety-critical and performance-critical applications. These areas demand rigorous testing, precision, and a deep understanding of the underlying systems—qualities that current AI tools cannot reliably deliver. In these domains, human oversight is not just beneficial but essential.

The Majority of Code vs. The Critical Minority

While it’s true that 70-80% of the world’s code may not fall into the highly critical category, the remaining 10-20%—which includes safety and performance-critical systems—is where the most attention and care are needed. This minority of code is often the backbone of essential services and infrastructure, underscoring the ongoing importance of skilled human developers.

Natural Language as a Programming Language: A Controversial Idea

Some proponents have suggested using natural language as a programming language to simplify coding. However, notable voices like Dyster have criticized this idea as “idiotic,” emphasizing that natural language lacks the precision and unambiguity required for programming.

Conclusion

While AI can assist and augment coding tasks, it is not ready to replace human developers, especially for critical systems. The complexity, safety requirements, and need for meticulous validation mean that human expertise remains indispensable. As the industry evolves, a collaborative approach where AI tools support—but do not supplant—experienced developers is likely to be the most effective path forward.

Key Takeaways:

• AI-generated code currently tends to be buggy, insecure, and bloated.
• Senior developers play a vital role in validating and maintaining code, particularly in critical applications.
• Safety-critical and performance-critical code requires human oversight.
• Natural language programming is not a viable replacement for traditional programming languages.
• The future of coding lies in human-AI collaboration, not substitution.

This perspective encourages a balanced view of AI’s role in software development—one that values human expertise while embracing technological advancements.

The Two Philosophies of Conducting Great Research: Structure vs. Freedom

In the world of research and innovation, there are fundamentally two contrasting philosophies on how to achieve meaningful and impactful results.

1. The Structured Approach
This philosophy revolves around careful planning and management oversight. A project is meticulously designed, goals are clearly defined, and a dedicated team—often comprising 20 to 30 people—is assigned to solve the problem. The process is systematic and controlled, emphasizing coordination and alignment with organizational objectives.

2. The Freedom-Driven Approach
On the other end of the spectrum lies a more anarchic, freedom-centered philosophy. Instead of dictating what to do, organizations hire the best minds they can find and simply tell them: “Do something interesting.” Researchers are given the autonomy to explore any idea or direction they find compelling, without rigid guidelines or predefined goals.

One remarkable example of this approach is a role described as follows: Researchers are tasked with doing something interesting over the course of a year. At the end of the year, they must report their findings—but with a twist. The report must be concise, fitting on a single sheet of paper, written in a 9-point font or larger. The rationale? If someone cannot succinctly explain what they accomplished, it’s likely the work wasn’t significant or clear enough.

This unconventional method fosters creativity, independence, and clarity of thought. And interestingly, it has been observed that on average, this “fairly anarchic” organization outperformed the more structured, well-organized teams.

Why Does Freedom Work?
- Encourages Innovation: Researchers aren’t confined by preset objectives and can pursue novel ideas.
- Attracts Top Talent: Giving autonomy appeals to highly skilled individuals who thrive on intellectual freedom.
- Promotes Clear Communication: The requirement to summarize work briefly ensures focus and clarity.
- Reduces Bureaucracy: Less management overhead allows researchers to spend more time on actual discovery.

Balancing Both Approaches
While structure can be essential for certain projects requiring coordination and specific outcomes, embracing freedom can unlock unexpected breakthroughs and foster a culture of innovation.

Final Thoughts
Organizations aiming for breakthrough research might do well to reconsider overly rigid structures and instead empower their best people with the freedom to explore, paired with clear and concise reporting standards. Sometimes, giving talented individuals space and trust can lead to results that surpass even the most carefully planned efforts.

Inside Meta’s Engineering Culture: Insights from John Miles White

John Miles White, former Director of Engineering on PyTorch and Meta’s Machine Learning Systems Lab (MSL), recently shared candid reflections on the tech giant’s evolving engineering culture, career dynamics, and the broader Silicon Valley landscape. Having stepped away from Meta, his insider perspective sheds light on the complexities and contradictions faced by engineers navigating today’s big tech environment.

The Changing Landscape for Engineers at Meta and Silicon Valley

John paints a nuanced picture of Meta as a company well-run from a business perspective but increasingly challenging as a workplace for employees who do not hold significant equity. He distinguishes between the experience of senior staff, who are often stockholders, and other employees who rely mostly on cash compensation.

A key shift he highlights is the labor market dynamic: unlike earlier years when engineering talent was scarce, today there is a perceived oversupply of engineers—except in niche areas like frontier AI research. This surplus reduces employee leverage, leading companies to scale back perks, reduce employee voice, and adopt a less accommodating culture. John notes this is not unique to Meta but reflects a broader Silicon Valley trend.

The consequences? More stressful work environments, a greater tolerance among employees for layoffs, and subtle shifts in organizational decisions such as reorganizations and talent retention strategies. The priority has tilted more toward business efficiency and less toward employee satisfaction.

The Promotion-Driven Culture and Its Discontents

One of the most striking revelations is the intense focus on promotions as the primary driver of motivation within teams, particularly in AI infrastructure. John observed that nearly every engineer's foremost goal was securing a promotion, which overshadowed genuine engagement with the work itself. This contrasts sharply with earlier Meta days, where career growth was less of an obsession.

This "promotion rat race" led to dysfunctional behaviors: teams shipping features they didn’t believe in simply to meet promotion criteria, and engineers prioritizing short-term wins over building clean, maintainable systems. Paradoxically, the skills that genuinely benefit one’s long-term career became decoupled from the promotion process.

John stresses that while the promotion-focused culture was highly prevalent, some teams like PyTorch bucked the trend by fostering a love of engineering for its own sake, holding a higher bar for promotions, and emphasizing craftsmanship over quick career advancement. This approach attracted engineers passionate about their craft, even if it meant slower promotions and lower compensation.

Lessons from PyTorch: Quality and Culture over Quick Promotions

PyTorch’s reputation for rigor and high standards made it a unique haven within Meta. Engineers there were often under-leveled compared to their true capabilities, but the credibility of PyTorch’s high bar helped them receive recognition when moving externally.

John reflects on his own experience managing PyTorch, where the culture prioritized sustainable success and healthy environments over rapid promotions. Although compensation might have been lower by about 20%, many chose this path out of pride and a desire to do meaningful engineering work.

Early Career and Impactful Work on Experimentation Tools

Before PyTorch, John contributed significantly to Meta’s data and experimentation tools, particularly the development of "Deltoid," Meta’s A/B testing framework. This work had a profound impact on how Meta conducted experiments to improve product decisions.

He recounts a pivotal career moment when many senior engineers left, thrusting him into a leadership role that accelerated his growth. The experience underscored how unexpected opportunities often arise from organizational churn, a common theme in tech careers.

John also notes the trend of successful tech startups emerging from products originally developed inside big tech—like Airflow and Optimizely—and reflects on missed entrepreneurial opportunities.

Programming Languages and the Julia Story

Before Meta, John was deeply involved in the Julia programming language, which aimed to combine the ease of high-level languages like Python and R with the speed of low-level languages like C. Julia’s niche was to offer high performance without sacrificing expressiveness, addressing frustrations with R’s slow execution and Python’s limitations.

He explains why R’s design leads to performance issues—due to dynamic features like overridable operators and lazy evaluation—which add runtime overhead. Julia’s approach challenged the assumption that high-level languages must be slow, but despite its merits, Julia remains less mainstream than Python or R.

Reflections on Academia vs. Industry

John expresses frustration with the misconception among many grad students and postdocs that industry is a fallback option if academic careers don’t pan out. He shares anecdotes of highly educated candidates struggling with basic programming tasks during interviews, illustrating the gap between academic research and practical engineering skills.

He encourages a mindset that values industry roles as challenging and rewarding careers in their own right, not as safety nets.

The Importance of Statistical Rigor in Tech

John is passionate about statistics, emphasizing the field’s tension between rigorous mathematical theory and practical application. He recommends the works of Larry Wasserman and Peter Arino for their honesty and rigor, contrasting them with more cavalier approaches common in the field.

He illustrates how misunderstandings of statistics can lead to problematic business decisions, such as misinterpreting A/B test results or setting goals that incentivize shipping code destined for deletion—a practice he finds counterproductive.

Career Advice and Leadership Lessons

Looking back, John regrets not taking advantage of leadership office hours offered by his skip-level manager early in his career, recognizing it as a missed opportunity for growth and connection. He advises junior engineers to seize chances to engage with leaders, as this can be invaluable.

His biggest piece of advice to his younger self? Be more confident and ambitious. John believes many talented people underestimate their potential and avoid risk due to self-doubt. He encourages embracing bigger challenges with discipline and optimism.

Final Thoughts

John Miles White’s reflections provide a candid and insightful look into the realities of working at a major tech company during a time of rapid change. His observations about labor dynamics, promotion culture, engineering craftsmanship, and career growth resonate beyond Meta, offering lessons for engineers and managers throughout the tech industry.

For those navigating big tech careers or interested in the intersection of engineering culture and business, John’s experiences underscore the importance of agency, choosing the right team culture, and balancing ambition with integrity.

Thank you for reading! If you enjoyed these insights, stay tuned for more conversations with industry insiders and deep dives into the evolving world of technology and engineering culture.

Cracking Senior Engineering Interviews: Insider Tips from Meta’s Austin McDonald

Landing a senior engineering role at top tech companies like Meta, OpenAI, or Anthropic is an intense process that goes far beyond coding skills. Austin McDonald, a former Meta hiring committee member who led mobile recruiting across the company, offers invaluable insights into what really happens behind the scenes during hiring and leveling decisions. Drawing from his extensive experience conducting hundreds of interviews, Austin sheds light on how to avoid common pitfalls, the critical role of behavioral interviews, and how to tailor your approach for today’s most competitive companies.

Understanding the Hiring Process: Who’s Who?

When you apply for a senior engineering role, several key players influence your journey:

• Sourcer: The initial recruiter who identifies and contacts candidates based on resumes, years of experience, and previous titles. They often make a gut-level call to decide if you’re worth pursuing.

• Recruiter: Takes over after initial screening, organizing interview loops, advocating for you in hiring committees, and guiding you through the process.

• Interviewers: Engineers and managers who evaluate your technical and behavioral skills through various interviews.

• Hiring Committee: Composed of senior engineers and managers who review your interview feedback, assess your level, and decide whether to move forward.

• Engineering Directors: Make the final hiring and leveling decisions, often based on recommendations from the hiring committee.

The Critical Role of Behavioral Interviews in Senior Hiring

While coding interviews are important, Austin emphasizes that behavioral interviews often play the most significant role in determining your level and hireability—especially at senior levels. Hiring committees look closely at behavioral interviews to assess:

• Your scope of impact: What size problems have you solved? How many teams or people have you influenced?

• Your level of ambiguity handled: Can you navigate complex, undefined problems?

• Your communication and leadership skills: How effectively do you collaborate, mentor, and resolve conflicts?

• Your organizational insight: How well do you understand and contribute to the broader company mission?

Austin notes that at Meta, for example, a staff-level hire must pass two system design interviews and behavioral interviews carry substantial weight in showing your organizational impact.

Avoiding Downleveling: How to Demonstrate the Right Seniority

One common challenge candidates face is being downleveled, where your experience is considered less senior than you expect. This often happens when:

• Recruiters rely heavily on years of experience and previous titles, which can vary widely in meaning across companies.

• Candidates come from smaller companies or non-FAANG firms where titles may be inflated.

Austin advises:

• Clearly communicate the scope and complexity of your work from the very first conversation with a recruiter.

• Use quantifiable impact metrics and describe projects that involve cross-team leadership, ambiguity, and organizational influence.

• Choose behavioral stories that highlight large-scale impact, leadership, and mentorship, not just technical accomplishments.

• Prepare to “anchor” every conversation at your desired level, emphasizing senior-level responsibilities consistently.

Behavioral Interview Best Practices: Choose, Structure, and Deliver Your Stories

1. Choose Stories with the Right Scope

• Prioritize stories that demonstrate broad organizational impact over small or narrowly focused tasks.

• Examples:

• Senior Engineer: Leading a project with multiple features involving several engineers.
• Staff Engineer: Owning multiple projects that affect entire teams or departments.
• Principal Engineer: Influencing company-wide strategies or industry-level initiatives.

2. Structure Your Stories Effectively

• Use frameworks like STAR (Situation, Task, Action, Result) or Austin’s preferred CALR (Context, Actions, Results, Learnings).

• Include:

• Context: Why the project was important.
• Actions: What you specifically did.
• Results: The measurable impact of your work.
• Learnings: What you took away and how you improved.

3. Deliver with Clarity and Engagement

• Keep your stories concise but rich in relevant detail.

• Avoid excessive technical jargon or unrelated context.

• Manage your time by reading interviewer cues—some may interrupt frequently, others may prefer longer explanations.

• Practice pivoting stories to better fit the interviewer's questions and highlight your strengths.

Tailoring Your Approach to Company Values: OpenAI & Anthropic Case Study

Understanding a company's unique values is essential for behavioral interviews:

• OpenAI values humility and optimism about AI's potential. Candidates should emphasize growth mindset and enthusiasm for AI’s positive impact.

• Anthropic focuses on “holding light and shade”, meaning recognizing both positive and negative implications of AI. Candidates should discuss ethical considerations and responsible AI development.

Austin recommends researching company values thoroughly and shaping your stories to demonstrate alignment with those values, especially for cutting-edge AI companies.

Common Behavioral Interview Mistakes for Senior Engineers

• Choosing stories with insufficient scope or impact.

• Over-talking or providing too much irrelevant detail.

• Failing to anticipate negative interpretations of your stories (e.g., owning technical debt without context).

• Neglecting non-technical leadership aspects such as mentoring, cross-team collaboration, and conflict resolution.

• Poor story organization, leading to long, unfocused answers.

The Power of Referrals

Referrals can make a significant difference, especially when you’re on the hiring "bubble." A strong referral from a senior leader who knows your work well can:

• Advocate for follow-up interviews if your initial performance was lukewarm.

• Help tip the hiring committee’s decision in your favor.

Austin stresses providing your referrer with detailed information to craft a powerful recommendation.

Interview Preparation: Balancing Coding, System Design, and Behavioral

• Junior engineers should prioritize technical skills but still prepare for behavioral questions.

• Mid-level engineers need a balanced focus, as behavioral skills increasingly matter.

• For senior engineers and above, behavioral interviews often determine the final hiring and leveling decisions.

Austin advises starting behavioral preparation early, practicing storytelling, and seeking feedback—ideally from calibrated insiders.

Handling Interview Subjectivity and Making a Strong Impression

• Interviewers assess both substance and presence at senior levels.

• Confidence, clarity, and cultural fit matter.

• Adjust your energy and style to match your interviewer, whether they prefer a formal or conversational tone.

• First impressions are crucial; decisions are often made within the first 10–15 minutes.

• Ending strong with thoughtful, relevant questions shows engagement and leaves a lasting positive impression.

Final Words of Wisdom from Austin McDonald

• Create scope proactively in your work to advance your career—don’t wait for opportunities; build them.

• Be honest with yourself about your values and priorities; career growth often involves trade-offs.

• Don’t let fear or impostor syndrome hold you back from pursuing your goals.

• Prepare thoroughly for behavioral interviews—they showcase your potential impact and leadership in ways technical tests cannot.

Resources to Help You Prepare

Austin highlights resources like Hello Interview, which offers free materials for system design and behavioral interview prep, especially useful for candidates targeting top AI labs.

Conclusion

Mastering senior engineering interviews requires more than coding prowess—it demands strategic storytelling, deep understanding of organizational impact, and cultural alignment. By learning how hiring committees evaluate candidates behind the scenes and preparing accordingly, you can avoid common pitfalls like downleveling and position yourself as the senior engineer companies are eager to hire.

For anyone aspiring to land roles at companies like Meta, OpenAI, or Anthropic, Austin McDonald’s insights provide a clear roadmap to not only survive but thrive in one of the most challenging hiring landscapes.

If you found this guide helpful, share it with your network and check out additional interview prep resources mentioned above. Good luck on your journey to your next senior engineering role!

The Journey of Bryan Cantrill: Insights from a Legendary Engineer on Career, Leadership, and Innovation

Bryan Cantrill, a distinguished engineer with a 30-year career starting at Sun Microsystems, offers a wealth of wisdom and candid reflections on technology, leadership, and personal growth. From the early days of operating systems to founding his own company Oxide, Bryan’s journey is a compelling story of passion, perseverance, and purpose. Here’s a deep dive into his experiences and lessons learned.

Early Days at Sun Microsystems: A Different Era of Computing

Bryan’s career began in the mid-1990s, a time when Microsoft dominated the tech landscape but was far from the polished giant it is today. Reflecting on those days, Bryan recalls the frustrations of working with early Microsoft operating systems like DOS and Windows, which lacked fundamental features like memory protection, leading to frequent crashes and lost work. In contrast, his first exposure to Unix systems at university was a revelation — the ability to multitask seamlessly was “mind-bending.”

Sun Microsystems, where Bryan eventually found his professional home, was a rare company still deeply invested in operating system innovation during Unix’s “darkest hour.” His initial reluctance to join Sun turned into enthusiasm after meeting passionate engineers like Kevin Clark and Jeff Bonwick, whose vision for building “beautiful code” aligned with Bryan’s own.

Navigating the Career Ladder: Focus on Meaning Over Titles

Bryan’s rise at Sun followed a traditional engineering ladder: Member of Technical Staff (MTS), Staff Engineer, Senior Staff Engineer, and Distinguished Engineer (DE). However, he emphasizes that promotions were not his focus. Instead, he concentrated on solving important problems and contributing meaningful work.

He critiques formal performance reviews as being more about measurement than improvement, often filled with bureaucratic frustrations and political processes, especially at higher levels like DE promotions. Notably, Bryan advises young engineers against fixating on titles or external validation. Instead, he encourages them to pursue work that genuinely motivates and fulfills them, warning that chasing status alone can lead to dissatisfaction and a midlife crisis.

The Toxicity of Stack Ranking and the Importance of Team Culture

One of Bryan’s strongest stances is against stack ranking — the practice of ranking employees relative to each other to identify low performers for termination. Calling it “organizational cancer,” he explains how it fosters mistrust and adversarial dynamics within teams. At Sun, this practice led to perverse incentives where managers might keep underperformers as “fodder” to protect their own ratings, undermining team cohesion.

For Bryan, the team is the fundamental unit of success. He believes that extraordinary achievements come from teams where members complement each other’s skills and work collaboratively, not compete internally.

The Tumultuous Years: Sun’s Decline and Oracle Acquisition

The late 1990s and early 2000s were difficult times for Sun. After the dot-com bubble burst, Sun’s stock plummeted by 98%, and the company endured over 30 rounds of layoffs. Bryan recounts how the leadership’s hesitation to lay off employees early on worsened the situation. Despite these challenges, Sun fostered a culture of technical boldness and customer trust, producing seminal technologies like Solaris, Java, and SPARC.

However, when Oracle acquired Sun, the culture shifted dramatically. Oracle’s business approach, focused on profitability often at the expense of customer trust, clashed with Sun’s ethos. Bryan found this environment incompatible with his values and left the company shortly after. He describes feeling ashamed to work for Oracle, contrasting it with the pride he felt at Sun.

Competing with Amazon: Lessons from Joyent

After Sun, Bryan joined Joyent, a cloud computing company competing with AWS. He admires Jeff Bezos as the “apex predator” of capitalism — relentless in execution, continuously innovating, and strategically cutting prices to dominate the market. Amazon Web Services’ early and aggressive moves created a high bar that was “brutal” competition for others.

Bryan’s role evolved from VP of Engineering to CTO, focusing on engineering leadership and customer engagement. His experience at Joyent highlighted the challenges of innovating in a market dominated by a giant with near-monopoly power.

Founding Oxide: Following the Heart Despite the Odds

In 2019, Bryan co-founded Oxide with his colleague Steve, driven by a shared vision to build the computer they always wished existed — a rack-scale machine designed from first principles with deep hardware-software co-design. Despite skepticism from venture capitalists, who often see hardware startups as “suicide missions,” Bryan and Steve pursued their passion.

Oxide focuses on general-purpose CPUs instead of GPUs, partly due to the proprietary nature of dominant GPU vendors like Nvidia, and the desire to build transparent, open systems. Bryan explains that building from scratch allows them to innovate in ways traditional hardware companies have not.

Reflections on Leadership, Career, and Meaning

Throughout his career, Bryan emphasizes intrinsic motivation and fulfillment over external rewards like promotions or financial gain. He warns against defining success narrowly and encourages engineers to find meaning in their work and teams.

He acknowledges mistakes, including a notably poor hiring decision at Joyent that led to overhauling his approach to recruitment, ultimately benefiting Oxide’s team-building efforts.

When asked what advice he’d give his younger self, Bryan simply says, “Don’t it up,” underscoring the value of learning and trusting one’s instincts without overthinking.

Final Thoughts: The Power of Teams and Purpose

Bryan’s happiest moments have come from working on challenging problems with exceptional teams, where collective effort turns the impossible into reality. His vision for Oxide is deeply rooted in building such a team culture.

He candidly critiques industry practices like stack ranking and toxic leadership while sharing optimistic views on innovation and resilience amid market cycles. His story is a testament to pursuing work that matters, embracing failure as a teacher, and valuing the people alongside the technology.

Bonus: Bryan’s Passion Project

Outside of his engineering and entrepreneurial work, Bryan is developing an ultra-low-profile ergonomic keyboard — a personal project born from the desire for better tools, reflecting his hands-on, problem-solving spirit.

Stay Connected

If Bryan’s insights resonate with you, consider exploring his work and projects further. Whether you’re an engineer, leader, or entrepreneur, his journey offers valuable lessons on navigating technology’s evolving landscape with integrity and passion.

This post is inspired by an in-depth conversation with Bryan Cantrill, capturing his unique perspective on a career dedicated to meaningful innovation and leadership.

Navigating the Transition from First-Time Manager to Manager of Managers: Key Insights and Challenges

Stepping up from being a first-time manager (M1) to managing other managers (M2) is a significant leap, filled with unique challenges that many new leaders might not anticipate. Drawing from a recent insightful conversation with an experienced leader, we explore the common skill gaps, subtle pitfalls, and the nuanced differences between individual contributor (IC) and management career growth.

The Biggest Skill Gaps When Moving from M1 to M2

One of the most critical challenges for new M2s is learning how to add credible value to the managers who report to them. Unlike managing individual contributors directly, an M2 must navigate a more complex layer of leadership where direct interaction with team members is limited or filtered through the managers they oversee.

A common misstep involves failing to understand the “restrictions” or boundaries on how to interact with teams indirectly. For example, a new M2 might try to gather candid feedback by setting up skip-level meetings with their indirect reports. While well-intentioned, this can inadvertently undermine the authority of the direct manager, demotivate team members, and create friction within the leadership chain.

These small behavioral nuances — such as how and when to communicate with indirect reports — carry magnified effects in larger organizational structures. Unfortunately, many new M2s only learn these lessons through trial and error or deep introspection over time.

Why These Mistakes Happen and What to Expect

The transition from M1 to M2 is full of subtle pitfalls largely because the role requires a different mindset and skill set than managing individual contributors. Just as moving from an IC role to a first-time manager involves a steep learning curve, stepping up to managing managers comes with its own natural learning process.

Expectations are set accordingly: new M2s are likely to make mistakes early on. Leadership teams often watch closely to provide support or intervene if necessary, but much of the learning is experiential. Success in these early weeks hinges on mastering small behavioral skills like communication protocols, influence without direct authority, and strategic delegation.

Comparing Career Growth: Individual Contributor vs. Management

The conversation also touched on the perennial question: Is career growth more meritocratic for ICs or managers?

• At senior levels, both paths become somewhat opaque. It can be difficult to attribute success directly to an individual, whether they are ICs or managers.
• Senior ICs may "talk a big game" about their accomplishments, but evidence can be hard to discern without deep involvement.
• Similarly, evaluating managers, especially those at higher levels, can be challenging due to the indirect nature of their impact.
• Over time, long tenures with consistent success help clarify a leader’s effectiveness, but on a case-by-case basis, assessments can feel arbitrary or unfair.
• This lack of clear accountability at upper management levels can be frustrating and feels less transparent compared to IC roles, where deliverables and outcomes might be more tangible.

Final Thoughts: The Reality of Leadership Growth

Leadership growth is complex and multifaceted. The jump from managing individuals to managing managers requires a careful balance of influence, trust, and strategic insight. Organizations can better support these transitions by recognizing the common pitfalls and providing guidance on the subtle behaviors that matter most.

For aspiring leaders, understanding that mistakes are part of the journey can help alleviate some of the pressure. Meanwhile, those evaluating leaders should remain aware of the inherent challenges in assessing leadership performance, especially at senior levels.

If you found these insights valuable, this discussion is part of a longer conversation available on YouTube. Feel free to join the conversation and share your thoughts — every comment is read and appreciated!

From Fired Twice to Amazon VP: Leadership Lessons and Career Insights with Ethan Evans

Ethan Evans’ career journey is a compelling story of resilience, growth, and strategic leadership. From being fired twice during the dot-com bust to becoming a Vice President at Amazon, leading over 800 engineers, his experience offers invaluable lessons for professionals navigating the tech industry and corporate leadership.

Early Career: Embracing High Growth Startups

Ethan's career began with a clear passion for engineering, spurred by the early days of home computing. Despite not getting into MIT, he pursued a master's degree at Purdue and dove into the startup world, largely influenced by friends and the allure of stock options. His early roles were diverse, ranging from networking startups to internet search and streaming audio, with most of these ventures ultimately failing or flaring out during the dot-com crash.

He attributes his initial setbacks—including two layoffs—to his abrasive personality and confrontational style. Ethan candidly describes himself as a "loose cannon," often clashing with peers and managers due to his combative approach and unwillingness to accept dissenting views.

The Power of Soft Skills and Strategic Annoyance

Ethan’s turning point came after his second layoff, when he took a hard look at himself and recognized that technical skills alone weren't enough. He began focusing heavily on soft skills—learning how to ask questions, listen, and build relationships rather than escalate conflicts. His concept of being "strategically annoying" emerged: maintaining a strong, clear opinion and pushing for what you believe in, but doing so in a way that invites collaboration rather than confrontation.

This shift was key to his later success, illustrating how combining technical expertise with emotional intelligence is critical in leadership.

Navigating Corporate Politics and Building Alliances

Ethan shares that one of his biggest mistakes early on was failing to build enough alliances within organizations. Being overly confrontational led some colleagues to exclude him from important conversations and even push for his removal. His advice to leaders and aspiring leaders is to focus not only on being right but also on cultivating relationships that foster mutual respect and inclusion.

Joining Amazon: Stability Meets Opportunity

Ethan’s move to Amazon came after he had been working at various startups, some struggling with funding and product-market fit. A prior role involving a partnership with Barnes & Noble exposed him to Amazon's innovative approach and competitive edge, making Amazon an attractive next step. Despite Amazon being much larger than his previous employers, it still felt like a high-growth, fast-moving company—an "escalator" that allowed him to grow as the company expanded exponentially.

Climbing the Leadership Ladder: Risk and Relationship Management

Ethan’s promotions at Amazon—from senior manager to director and eventually VP—were fueled by a combination of demonstrated leadership, taking calculated risks, and strategic communication with his superiors. He shares a telling story about pushing forward a high-risk project despite management’s reservations, which ultimately succeeded and became a pivotal point in his promotion.

He emphasizes the importance of "the magic loop"—a partnership between a leader and their manager where the leader commits to delivering exceptional results, and the manager commits to advocating for their advancement.

Managing Promotions and the Reality of Corporate Life

Ethan is refreshingly honest about the realities of promotions and performance management. He acknowledges that sometimes, those who advocate for themselves and "threaten to leave" get promoted over quieter, collaborative employees. While it may seem unfair, this reflects the pragmatic challenges managers face balancing team dynamics and organizational goals.

He also recounts a painful lesson when a promising engineer on his team missed a promotion due to his own ignorance of Amazon’s formal promotion cycles—a reminder that understanding and navigating corporate processes is crucial for career advancement.

Leading Through Integration: The Twitch Acquisition Experience

As the integration liaison for Amazon’s $970 million acquisition of Twitch, Ethan faced the unique challenge of influencing a young, fast-growing company without direct authority. His role required diplomacy, patience, and soft skills to align Twitch’s culture and priorities with Amazon’s expectations, especially around profitability—a concept initially foreign to Twitch’s venture-funded mindset.

Insights on Leadership Styles: Jeff Bezos vs. Andy Jassy

Having worked with both Jeff Bezos and Andy Jassy, Ethan notes distinct leadership styles:

• Jeff Bezos: The founder’s style is bold and risk-taking. Bezos viewed the company as his "toy," willing to gamble resources aggressively. He was emotionally supportive of leaders and inspiring, often pushing boundaries with confidence.

• Andy Jassy: More traditional and measured, Jassy focuses on partnership and accountability, expecting leaders to own their plans and deliver results without as much emotional backing. Ethan describes this style as less inspiring but pragmatic.

Performance Management and the Harsh Realities of PIPs

Ethan offers a candid critique of Amazon’s performance management system, particularly the use of stack ranking and Performance Improvement Plans (PIPs). He explains how the pressure to meet attrition goals forces managers to put underperformers on PIPs, often with a predetermined outcome of termination. Despite good intentions in some cases, the system is psychologically biased and difficult to overcome.

He warns employees that once on a PIP, the best strategy is often to start looking for a new job, given the low success rate of recovery.

The Power (and Risk) of Managerial Authority

One of the more sobering revelations Ethan shares is that managers at Amazon can effectively end an employee’s career with little intervention from HR. Since managers frame the narrative about an employee’s performance, they hold significant power, which can be abused or misused. Employees must navigate this reality carefully, building relationships and avoiding conflicts with vindictive bosses.

Final Career Advice: Growth, Relationships, and Reputation

Looking back, Ethan would advise his younger self to:

• Prioritize high-growth environments: Being part of rapidly expanding companies accelerates career progression.

• Invest in relationships and soft skills: Technical expertise is necessary but insufficient without the ability to connect and influence others.

• Build a reputation proactively: Use tools like LinkedIn to establish your professional brand and network, even if you are an introvert.

Closing Thoughts

Ethan Evans’ story is a testament to the complex interplay between technical skill, interpersonal savvy, risk-taking, and political navigation in building a successful tech leadership career. His transparency about failures, personality flaws, and the realities of corporate life provides a rare and valuable window into what it takes to thrive at the highest levels of companies like Amazon.

For more insights and guidance on leadership and career growth, Ethan can be found on LinkedIn as Ethan EvansVP or at his website, EthanEvans.com, where he offers coaching and courses on career advancement.

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From Intern to Fellow: Career Lessons from a Cybersecurity Pioneer

How Carrie Notchenberg built an extraordinary tech career by focusing on impact over intelligence

In the fast-moving world of tech careers, few stories are as instructive as Carrie Notchenberg's journey from Norton's first intern to becoming a Fellow at Symantec—the company's highest technical role. His path through cybersecurity, Google X, autonomous vehicles, and academia offers invaluable insights for engineers at every stage of their careers.

The Foundation: Starting at the Bottom

Notchenberg's story begins in 1992 as an intern at Peter Norton Group (later acquired by Symantec), where he literally worked at a test computer because they didn't even have a desk for him. This humble beginning would eventually lead to him becoming Symantec's most senior engineer—a 24-year journey that demonstrates the power of long-term growth within an organization.

"I got to work on whatever I wanted for my entire career at Symantec," Notchenberg reflects. This unusual freedom came from proving himself early and consistently delivering impactful projects.

The Secret to Reaching Fellow Level: Impact Over Intelligence

When asked what set him apart from other engineers, Notchenberg's answer is revealing: "I look for things with big business impact. I look where there were gaps."

His promotion to Fellow wasn't based on completing increasingly difficult technical challenges assigned by others. Instead, he developed what he calls "project taste"—the ability to identify problems that truly matter to the business and tackle them independently.

Key Examples of High-Impact Projects:

• Polymorphic Virus Detection: When traditional antivirus methods took six months to handle new threats, he developed algorithms that could detect self-mutating malware variants in real-time
• Technology Strategy: Defined company-wide technology strategy that aligned all divisions
• Research Transfers: Successfully moved multiple research prototypes into shipping products

The Intelligence Myth: Why Smart Isn't Enough

One of Notchenberg's most counterintuitive insights challenges the tech industry's obsession with raw intelligence:

"I don't think I'm a really intelligent person. I take forever to learn new things... You don't need that much intelligence to be successful, but enough."

He witnessed this firsthand at Google, where he met someone with clearly over 200 IQ who remained at L4 due to poor communication skills and lack of business impact focus.

What Actually Drives Career Growth:

1. Communication Skills: "People will think you're intelligent and give you more credit based on your ability to communicate"
2. Collaboration: Learning to work with others without alienating them
3. Outcome Focus: Understanding what matters to your company, division, and customers
4. Project Selection: Choosing work that moves important metrics

Overcoming Imposter Syndrome at the Highest Levels

Despite his success, Notchenberg struggled with imposter syndrome throughout his career: "I always worried... what if I'm not good enough for Google or Meta?"

This fear kept him at Symantec longer than ideal, even when he wasn't growing anymore. His breakthrough came when Google X directly recruited him, forcing him to confront his fears: "I said, 'Well, I'm probably going to fail this interview. I'm sure I'm not good enough, but I'm going to do it.'"

The lesson: Sometimes you need external validation to overcome internal doubts, even at the highest levels of technical achievement.

The High-Level Interview Process

For senior roles, the interview process looks dramatically different:

• No coding problems: Focus shifts to design problems and leadership scenarios
• Behavioral emphasis: Questions about solving hard problems and handling conflicts
• Sales pitches: Companies actively recruit rather than just evaluate
• Strategic discussions: Conversations about industry direction and vision

"It was really about going through the motions of having interviews and selling me on the role," Notchenberg explains about his Google X interview process.

Navigating Big Tech Culture

Moving from Symantec to Google revealed significant cultural differences:

What Was Different:

• Talent density: "Really, really, really smart people" everywhere
• Engineering culture: More structured processes and higher standards
• Expectations: "When you get to senior levels, there are very high expectations"

What Remained the Same:

• Project taste issues: Even brilliant people often lacked good judgment about which problems to solve
• Political dynamics: Senior levels still involved meetings, debates, and "a lot of garbage"

The Future of Software Engineering in the AI Era

As both an industry veteran and current UCLA professor, Notchenberg has a unique perspective on how AI will reshape software engineering careers:

Near-term Reality:

"Someone is going to have to go and look at that code and understand the mission of the company... and make sure it's doing the right thing. That requires real thinking."

Long-term Vision:

If we reach AGI-level programming capabilities, the focus will shift entirely: "The greatest engineers will be people who really understand a problem they're trying to solve for a customer... and figuring out how to clearly communicate to an LLM those requirements."

Academic Insights: Teaching and Learning

Notchenberg's transition to teaching at UCLA (which began with a frantic call two weeks before classes started) has given him insights into both education and communication:

Teaching Philosophy:

• Teach to the middle: "I try to design lectures for what I think is one of the lower common denominators, which is myself"
• Student empathy: "I try to put myself in their shoes and ask what would they know?"
• Make it enjoyable: "I want them to learn and enjoy. I want them to come to class"

AI in Education:

His experience allowing students to use LLMs revealed concerning trends: "They were using it in ways that hindered learning." He's now restricting AI use to concept clarification rather than project completion.

Career Advice: The Essential Framework

Looking back on his career, Notchenberg offers several key pieces of advice:

When to Stay vs. Leave:

Stay as long as you're learning: "You should stay in a job as long as you are learning new things and building new skills"
Leave when you're stagnant: "When you get to that point where you can just wake up and have some nice coffee... it's time to leave"

Overcoming Fear:

"Don't let fear of failure hold you back. You probably can do more than you think you can do."

Focus on Outcomes:

"Think about who's going to use it, what do they care about, how do they measure success, and then optimize for that."

Find Good Management:

"A manager can make or break your career and your life and your happiness."

The Long View: Building a Meaningful Career

Notchenberg's story demonstrates that extraordinary careers aren't built on genius alone, but on consistently choosing impactful work, developing strong communication skills, and maintaining the courage to grow beyond your comfort zone.

His journey from intern to Fellow, from cybersecurity expert to autonomous vehicle architect, from industry veteran to beloved professor, shows that the most rewarding careers are built on continuous learning, genuine impact, and the wisdom to know when it's time for the next challenge.

For engineers at any stage, his career offers a roadmap: focus on outcomes over output, communication over complexity, and impact over intelligence. The technology may change, but these fundamentals remain constant in building a career that truly matters.

This interview reveals the often-hidden dynamics of senior technical careers and offers practical wisdom for engineers looking to make their mark in an increasingly complex industry. Whether you're just starting out or looking to reach the next level, Notchenberg's insights provide a valuable framework for sustainable career growth.

Overview

This video is an in-depth interview with Michael Novati, a former senior staff engineer (IC7) at Facebook/Meta, who shares his experiences joining the company early on, insights into its engineering culture, his growth journey to becoming a top engineer, and thoughts on how emerging AI tools like large language models (LLMs) might impact software development.

Main Topics Covered

• Michael Novati’s early experience joining Facebook (Meta) as an intern
• The engineering culture and technical environment at Facebook pre- and post-IPO
• The IPO experience and its impact on employees
• Michael’s internal newsletter and openness within the company
• Working directly with Mark Zuckerberg and early engineering stories
• Types of engineers that impressed Michael and what defines a “coding machine”
• The potential impact of AI and LLMs on software engineering roles
• Michael’s approach to career growth, productivity, and working as an IC7
• Common traits among IC7+ engineers and advice on landing code faster
• Reasons for leaving Meta and reflections on talent, hard work, and luck
• Advice to his younger self and lessons on feedback and improvement

Key Takeaways & Insights

• Facebook’s early engineering culture empowered engineers heavily, fostering rapid innovation with tools and codebases built largely from scratch.
• The “move fast and break things” culture was about breaking norms and innovating quickly, not reckless coding.
• Post-IPO, the company matured with a stronger focus on stability and financial impact, changing engineering dynamics.
• Michael positioned himself as a “coding machine” by being highly productive, taking initiative on cross-org projects beyond his immediate team, and building strong credibility and trust.
• Taste and judgment—knowing which problems to solve and how to minimize impact when changing code—are critical skills that develop over time and separate top engineers.
• LLMs and AI tools are currently productivity enhancers rather than replacements but could fundamentally change the nature of coding in the future.
• High-performing IC7+ engineers share traits like extreme diligence, sharpness, conscientiousness, and high attention to detail.
• Rapid iteration with high-quality feedback is essential to grow as a software engineer.
• Luck (e.g., timing and company fit) and talent both play large roles in career trajectory, but hard work remains the most controllable factor.
• Receiving feedback as a way to improve rather than as judgment or approval is crucial for growth.

Actionable Strategies

• Start writing code early and often; don’t overthink before acting.
• Seek feedback from experienced and high-taste mentors, not peers at the same level.
• Actively incorporate feedback and iterate rapidly to compound improvement.
• Build credibility by minimizing bugs, communicating effectively, and understanding the broader impact of your code changes.
• Focus on problems where you have clear solutions in mind to maintain productivity, but gradually push into more ambitious projects to grow.
• Manage meetings carefully to protect deep work time; push back on unnecessary ones with manager support.
• Build relationships across your team and organization, especially with those responsible for code deployment and maintenance.
• Use AI tools and LLMs as productivity aids to speed up coding and routine tasks, while continuing to develop your judgment and domain knowledge.
• Reflect on your feedback as guidance to improve rather than as a pass/fail test to reduce pressure and grow faster.

Specific Details & Examples

• Michael joined Facebook in 2009 when there were about 200 engineers, primarily working in PHP (later evolved to Hack).
• He merged two internal task tools within a week early on without telling anyone, demonstrating initiative but learning about the importance of communication and impact.
• He once single-handedly removed thousands of legacy “preparable” classes from the codebase over several months.
• Michael worked with Mark Zuckerberg during a 2009 hackathon on the idea of emoji reactions to posts, which later became a standard feature.
• Facebook’s IPO in 2012 was a rational event internally, celebrated but grounded; stock vesting happened six months later, with many employees holding their shares long term.
• An internal newsletter Michael wrote sparked conversations but also friction with HR and executives, illustrating the risks and benefits of transparency.
• “Clown Town” was an internal humorous term for engineers who introduced silly bugs; Evan Priestley was a prolific engineer and role model.
• Michael described LLM adoption as akin to evolving from Vim to VS Code, with potential for even more transformative agentic AI workflows.
• He reported spending about 30% of his time on his team’s work and 70% on broader org-wide initiatives.
• An example of judgment was building trust with deployment teams so he could push code rapidly and confidently, even risking resignation if he caused a production failure.

Warnings & Common Mistakes

• Writing a lot of code without incorporating feedback or improving style and quality can frustrate reviewers and slow growth.
• Rushing big changes without considering other teams’ ongoing work or the impact on users can cause friction and bugs.
• Taking feedback as judgment or approval instead of constructive input can hinder learning and improvement.
• Overcommitting to meetings can destroy deep work time and reduce productivity.
• Being too rigid in prioritization (only working on tasks you immediately know how to solve) can limit career growth.
• Being openly critical or controversial internally can cause unintended political friction, even when motivated by transparency.
• Relying too heavily on stock price or compensation fluctuations rather than fit and performance can be a risky career approach.

Resources & Next Steps

• Michael mentioned internal tools at Meta like TBGS (code search), internal blogging via Notes, and continuous integration systems.
• He recommended seeking out senior engineers, skip-level managers, or widely respected people within your org for mentorship and guidance.
• For those interested in interview preparation and career development, Michael is involved with formation, a platform aimed at helping engineers improve and prepare.
• Viewers are encouraged to subscribe to the channel and follow Michael on LinkedIn, Reddit, or other platforms for follow-up discussions and advice.
• Embracing AI tools and continuously experimenting with prompts and workflows is suggested to stay ahead in productivity.
• Reflecting on feedback and adopting a growth mindset is emphasized as a personal development approach.

From New Grad to Staff Engineer in 3 Years: The Meta Success Story

How Simon achieved the highest performance ratings and built a rocket ship career through ownership, curiosity, and exceptional mentorship

The Remarkable Journey

Simon's career trajectory at Meta reads like a Silicon Valley fairy tale. Starting as a new graduate (IC3), he reached Staff Engineer (IC6) in just three years—a feat that typically takes 5-7 years. Along the way, he earned two "Redefines Expectations" (RE) ratings, Meta's highest and rarest performance rating that most engineers never achieve even once in their entire careers.

But this isn't just a story about promotions and ratings. It's about the strategic decisions, mindset shifts, and key relationships that accelerate career growth in big tech.

The Foundation: Early Momentum Matters

Strategic Preparation Before Day One

Simon's success began before he even started full-time. As a former Meta intern, he had already learned the internal tools—a crucial advantage that saved him "4-8 weeks of ramp-up time." But more importantly, he spent time before joining learning technologies like React and exploring different programming patterns.

Key Insight: "We're pattern matching machines. The more patterns we've seen, the easier it is to apply them." Even if you haven't used Meta's internal JavaScript type checker Flow, having TypeScript experience makes the transition seamless.

The Power of the Right Manager

Perhaps the most critical factor in Simon's success was his manager, Bala. When Simon expressed his ambitious goal of reaching IC5 in three years, Bala didn't dismiss it—he drew up a plan on the whiteboard. This manager had made a similar journey himself and knew it was possible.

Bala's impact extended far beyond technical guidance:
- Deep technical mentorship (he was a recently converted IC6 to manager)
- Product strategy and roadmap setting
- Communication coaching
- Experiment design and execution

The relationship lasted 5.5 years—an eternity at a company known for frequent reorganizations.

The Secret to "Redefines Expectations" Ratings

First RE Rating: The Power of Impact

Simon's first RE rating came from driving projects that exceeded the team's half-year revenue goal by multiple times. But it wasn't just about the numbers—it was about the behaviors:

1. End-to-end ownership: When experiments showed neutral results, Simon didn't stop there. He dug deep with data scientists to understand why, iterated on targeting, and worked with designers to improve the experience.

2. Technical breadth: He reviewed code across Android, iOS, JavaScript, and PHP—helping uplevel both the codebase and his colleagues through thoughtful code reviews.

3. People development: He took responsibility for recruiting and onboarding new team members, growing the team from 2 to 8 people.

Second RE Rating: Scaling Through Others

The second RE rating demonstrated a crucial transition from individual contributor to force multiplier. Simon began leading "pods" of engineers, taking responsibility not just for his own output but for project success and team member growth.

The key behavioral shift: Moving from "I hope this person gets it done" to "I am responsible for the outcome, regardless of who executes it."

The Promotion Progression: Behavioral Evolution

IC3 to IC4 (6 months): Task Completion to Project Ownership

• Before: Complete assigned tasks
• After: Drive projects to completion and identify follow-up opportunities
• Key behavior: Taking ownership of project outcomes, not just individual deliverables

IC4 to IC5 (3 halves): Individual Impact to Team Leadership

• Before: Responsible for your own success
• After: Responsible for others' success and project outcomes
• Key behavior: Leading pods of engineers, mentoring, and ensuring team success

IC5 to IC6 (2 halves): Team Leadership to Organizational Impact

• Before: Managing people and projects directly
• After: Scaling yourself through systems and delegation
• Key behavior: Creating processes that catch problems early, delegating effectively while maintaining accountability

The Management Detour: Lessons Learned

Despite his IC success, Simon tried management for nearly a year. The transition was challenging for several reasons:

1. Identity crisis: "Will I just become a middle manager who's lost all technical abilities?"
2. Bad timing: His mentor manager had an accident, his skip-level was on leave, and he had to relocate from London
3. Over-promising: Trying to get two people promoted from IC5 to IC6 simultaneously on the same team
4. Technical attachment: Struggling to let go of hands-on technical work

When his director asked, "Simon, do you want to go back to IC?" his gut response was immediate: "Yes, yes I do."

The realization: As an IC6 who enjoys mentoring, he could pick and choose coaching opportunities as a "bonus" rather than having it be his primary evaluation criteria. This provided more flexibility and aligned better with his interests.

The Communication Multiplier

One of Simon's manager's key teachings was that many people are held back not by their technical abilities, but by their inability to communicate their impact effectively.

The 5-Second Rule for Written Communication

Simon's framework for effective workplace communication:
- Assume 5-10 seconds of attention: Make it incredibly parseable at a glance
- Lead with TL;DR: Include numbers and concrete outcomes
- Structure for different audiences: High-level impact for leadership, technical details for fellow engineers
- Stay above the fold: Critical information should be visible without expanding the post

The Meta Internal Forum Strategy

At Meta, a single workplace post can reach thousands of people. Simon learned to write updates that clearly communicated:
1. What was accomplished (with numbers)
2. Why it mattered to the business
3. What the next steps were
4. Technical details for those who wanted to go deeper

The Hidden Rewards: Discretionary Equity

High performers at Meta can receive "Additional Equity" (AE)—discretionary stock grants that only directors can approve. Simon received this twice:

1. First AE: After his IC5 to IC6 promotion, likely to address equity compensation gaps from starting as a new grad
2. Second AE: After successfully shipping a company priority product ahead of schedule while transitioning to management

These grants can significantly impact total compensation beyond standard promotion cycles.

The Intern Success Formula

Having managed interns and served as an intern director, Simon identified the key differentiators:

What Makes Great Interns

1. Velocity above all: The primary measure is project completion
2. Ask questions early: Use the first few weeks when expectations are zero
3. 30-minute rule: If stuck for more than 30 minutes, ask for help
4. Leverage peer network: Don't rely solely on your manager for support
5. Build relationships: Peer feedback is crucial for final evaluations

The Sustainable Pace

Simon averaged about 50 hours per week during his growth phase, but emphasized that sustainability comes from interest and passion. When he lost enthusiasm for his work, the same hours felt like a grind, prompting his team switch.

Universal Principles for Career Growth

The Ownership Mindset

"Nothing at Meta is someone else's problem." When blocked, don't wait—read the code, understand the decisions, propose solutions. This curiosity-driven ownership was Simon's primary growth driver.

The Technical vs. Non-Technical Balance

Simon estimates you can reach IC5 with just baseline technical skills if you excel at:
- Cross-functional collaboration
- Communication and influence
- People development
- Project management
- Strategic thinking

Technical brilliance can be a differentiator, but soft skills are often the limiting factor for rapid career growth.

The Meta Advantage

What kept Simon at Meta for his entire career:
- People: Empathetic, technically excellent colleagues
- Flexibility: Global mobility and internal transfer opportunities
- Growth opportunities: Ability to switch teams when losing motivation
- Scale: Impact potential across billions of users

The Takeaway

Simon's journey from new grad to Staff Engineer in three years wasn't about working 80-hour weeks or having exceptional technical talent. It was about:

1. Strategic preparation before starting
2. Finding exceptional mentorship and maintaining that relationship
3. Taking ownership beyond your immediate responsibilities
4. Scaling impact through others as you grow
5. Communicating effectively to amplify your contributions
6. Being curious and treating problems as puzzles to solve

The most powerful insight? Career acceleration comes from expanding your circle of ownership—from tasks to projects to teams to organizations. Each promotion represents a fundamental shift in how you create value, not just doing more of the same work.

For ambitious engineers early in their careers, Simon's story provides a concrete roadmap: focus on ownership and curiosity, find great mentors, and remember that your technical skills are just the foundation—your impact on others and the organization is what drives exponential career growth.