Adam’s Advice to His Younger Self

In this final lesson, **Adam Ernst**, Software Engineer at **Meta**, reflects on his career journey and the advice he would give to aspiring engineers. Looking back, Adam believes he would not change the path he took because it aligned with his genuine interests and strengths. He emphasizes that long-term success comes from enjoying the work itself—especially the challenge of solving difficult problems—rather than chasing titles or following trends. By pursuing work that naturally fuels curiosity and motivation, engineers are more likely to sustain high performance and meaningful career growth.

- **Follow Work You Genuinely Enjoy:** Adam believes the best career decisions come from pursuing work that you find intrinsically rewarding. Passion creates the motivation needed to continually learn, improve, and produce high-quality work over the long term.
- **Love Solving Problems, Not Just Writing Code:** While not every task is enjoyable, Adam finds fulfillment in tackling challenging engineering problems. A genuine curiosity for problem-solving is what keeps difficult work engaging and ultimately leads to sustained success.
- **There's No Perfect Career Blueprint:** Rather than trying to optimize every career decision in hindsight, Adam's experience suggests that success comes from consistently following opportunities that align with your interests and strengths. When what you enjoy also meets the needs of the industry, you're in an ideal position to thrive.

Original podcast link: [**https://www.youtube.com/watch?v=YA_OYJF3Mmw**](https://www.youtube.com/watch?v=YA_OYJF3Mmw)

IC9 Expectations

In this lesson, **Adam Ernst**, Software Engineer at **Meta**, shares how his mindset evolved after reaching the highest levels of the Individual Contributor career path. Rather than obsessing over whether his work was "IC9-level," Adam explains why he stopped measuring success by job expectations and instead focused on solving meaningful problems. He discusses the importance of trusting feedback from managers, staying aligned with organizational priorities, and pursuing work that is both impactful and personally motivating.

- **Stop Chasing the Title, Start Solving Problems:** Adam believes that constantly worrying about whether your work is "senior enough" is counterproductive. Instead, focus on delivering meaningful solutions to the most important problems facing your organization.
- **Use Feedback as a Course Correction:** Regular check-ins with your manager help ensure you're investing your time in high-impact work. Honest performance feedback should be viewed as guidance to adjust direction—not as a measure of personal worth.
- **Do Work You Enjoy:** Adam attributes much of his long-term success to working on problems he genuinely enjoys. By aligning personal interests with organizational priorities, engineers can produce their best work without becoming consumed by the pressure of meeting a particular career level.

Original podcast link: [**https://www.youtube.com/watch?v=YA_OYJF3Mmw**](https://www.youtube.com/watch?v=YA_OYJF3Mmw)

Technical Depth vs Breadth

In this lesson, **Adam Ernst**, Software Engineer at **Meta**, shares his perspective on what it takes to reach the highest levels of the Individual Contributor (IC) career ladder. Rather than choosing between technical depth and breadth, Adam explains how he developed both by following curiosity and solving real engineering problems. He describes a practical approach to learning unfamiliar systems, collaborating effectively across teams, and continuously expanding his expertise through hands-on experience instead of formal study.

- **Develop Both Depth and Breadth:** Adam believes senior engineers benefit from deep expertise in their primary domain while gradually building knowledge across adjacent systems. This combination enables engineers to solve complex cross-functional problems and make a broader organizational impact.
- **Learn Through Real Problems:** Instead of studying technologies in isolation, Adam dives deeply into unfamiliar systems only when they become relevant to the problem at hand. Solving real engineering challenges creates meaningful learning opportunities and builds lasting expertise.
- **Become Self-Sufficient and Collaborative:** By investigating issues independently before asking for help, engineers not only reduce the burden on partner teams but also arrive with informed questions and potential solutions. This approach accelerates learning, builds credibility, and strengthens cross-team relationships.

Original podcast link: [**https://www.youtube.com/watch?v=YA_OYJF3Mmw**](https://www.youtube.com/watch?v=YA_OYJF3Mmw)

Thoughts On Management

In this lesson, **Adam Ernst**, Software Engineer at **Meta**, explains why he chose to remain on the **Individual Contributor (IC)** career path instead of transitioning into engineering management. He discusses how understanding his strengths, interests, and motivations helped shape his career, why deep technical expertise can be more valuable than constantly switching domains, and how long-term specialization enabled him to become a trusted expert within Meta's mobile engineering organization.

- **Know What Motivates You:** Adam chose to remain an Individual Contributor because his greatest passion is writing code and solving technical problems. He recognized that management requires a different skill set—such as organizational leadership, direction setting, and people management—that did not align with his strengths or interests.
- **Build Deep Expertise Over Constant Change:** Rather than frequently changing teams or technologies, Adam stayed within mobile engineering, allowing him to develop deep institutional knowledge and become an expert in the architecture, tooling, and infrastructure that powered Meta's iOS ecosystem.
- **Career Paths Should Match Your Strengths:** Adam emphasizes that there is no universally "correct" career path. While some engineers thrive by exploring new domains such as AI or AR/VR, others create greater impact by mastering a specific area. The key is aligning your career choices with the type of work you genuinely enjoy and excel at.

Original podcast link: [**https://www.youtube.com/watch?v=YA_OYJF3Mmw**](https://www.youtube.com/watch?v=YA_OYJF3Mmw)

Code Review is Undervalued

In this lesson, **Adam Ernst**, Software Engineer at **Meta**, explains why code reviews are one of the most powerful—and often overlooked—tools for influencing engineering culture. Drawing from his experience reviewing more than **1,600 code changes** in just 18 months, Adam shares his philosophy on giving constructive feedback, mentoring engineers through review comments, and creating lasting improvements across a codebase. He emphasizes that effective code reviews are not about enforcing preferences but about teaching, understanding context, and helping others grow.

- **Code Reviews Are a Leadership Tool:** Adam views code reviews as an opportunity to mentor engineers, share best practices, and influence technical decisions in a practical, one-on-one setting rather than through broad directives.
- **Explain the "Why," Not Just the "What":** Great review comments focus on the reasoning behind a suggestion instead of simply requesting changes. By explaining trade-offs and remaining open to missing context, reviewers encourage learning instead of compliance.
- **Create a Multiplier Effect:** Constructive feedback helps engineers improve not only their current code but also the way they review others' work. This creates a ripple effect where good engineering practices spread organically throughout the team.

Original podcast link: [**https://www.youtube.com/watch?v=YA_OYJF3Mmw**](https://www.youtube.com/watch?v=YA_OYJF3Mmw)

When Should I Actually Use AI During The Interview?

In this lesson we talk about when and how to use AI effectively during an AI-assisted coding interview.

- **Find the right balance with AI:** Learn how to avoid over-delegating core logic to AI or underusing it and running out of time, by aiming for the “middle path” that maximizes leverage while minimizing risk.
- **Accelerate typing, not thinking:** Discover why you should use AI for scaffolding, boilerplate, and clearly defined test cases—but retain ownership over algorithms, data structures, and key design decisions.
- **Optimize for easy verification:** Understand that AI is most helpful when you already know what needs to be built and can quickly verify the output, and least helpful when you’re still figuring out the correct approach.

How Am I Being Evaluated Now?

In this lesson we talk about how candidates are evaluated in AI-assisted coding interviews and how the scoring rubric has shifted.

- **Understand what still matters—and what matters more:** Learn how the core engineering method (problem exploration, solution design, implementation, and testing) remains the foundation, but with greater emphasis on deep problem exploration and structured thinking before coding.
- **Recognize why problem solving is now the primary signal:** Because AI handles much of the typing, interviewers focus more heavily on your ability to form a clear plan, choose the right algorithms and data structures, and articulate trade-offs.
- **Master delegation and verification with AI:** Discover how execution now means directing AI effectively—accelerating typing but not thinking—and how careful verification of AI-generated code is a major part of your evaluation.

Introducing The Active Users Problem

In this lesson we talk about a realistic example problem used throughout the course to simulate an AI-assisted coding interview.

- **Understand the problem context and deliverables:** Build the back-end logic for an active users metrics dashboard, including calculating daily unique active users and rolling 7-day active user counts from messy, real-world log data.
- **Work within a structured codebase:** Learn how to navigate starter code with helper functions (e.g., ID normalization, bot filtering) and focus on implementing two core functions while leveraging provided tests.
- **Set expectations for interview complexity:** Explore how AI-assisted interviews can range from simple LeetCode-style tasks to multi-file, production-like environments—and how this example reflects an average level of complexity.

The First Thing You Must Figure Out

Choosing the right company or team is hard because what’s “great” truly depends on our individual priorities.

Here are the core points from the lesson:

- We emphasize that people differ in life stage, location, responsibilities, and goals, which means there is no universal “best” company or team, only what is best for our personal priorities.
- We caution against blindly chasing FAANG or big tech, noting that while it can be optimal for some, it can be a poor match for others depending on what they value and need at this stage of their career.
- We outline the key first step: listing all potential priorities and stack-ranking them to create a clear, personalized hierarchy that guides the next career move.

Have A Conversation About Conversation

In this lesson, we explore how to set up a healthy, effective relationship with an engineering manager by having a “meta” conversation early—one that focuses not on tasks, but on how we want to work together.

- We introduce the idea of a personal “README file,” where we proactively explain our background, working style, motivations, and concerns so our EM understands how to support us.
- We emphasize sharing what energizes us and what drains us, giving our manager the context they need to advocate for us and assign work that helps us thrive.
- We suggest regularly reflecting on what’s going well and what isn’t—using 1:1s not just for status updates, but for deeper calibration on collaboration.
- We call out the importance of explicitly discussing how we prefer to receive (and give) feedback, whether direct and verbal or written and reflective.
- We highlight that starting the relationship with these meta conversations sets the foundation for a smoother, more aligned partnership with our EM.

How To Crack Any Interview

If you want direct interview support from Alex and Uzair, take their live Maven course with discount code **TARO10**: <https://maven.com/alex-kliotzkin/acing-em-interviews>

To ace any Engineering Manager (EM) interview, we need to go beyond memorized answers and demonstrate a deep, tailored understanding of the role, the company, and the people interviewing us. This final video recap ties together the core strategies we've learned throughout the course.

- **Deeply Understand the Role and the Interviewer**

  - We should thoroughly research the company's culture, the team’s business priorities, and even the interviewer’s background if possible.
  - This helps us anticipate questions and articulate the team’s pain points—making us stand out as someone who already thinks like an insider.

- **Focus on the Intent Behind the Questions**

  - Every question has an underlying purpose. We must listen for the *question behind the question* to understand what trait or leadership ability is being evaluated.
  - Once we’ve identified this, we lead our response with our **engineering management systems** and **leadership philosophies** to show intentionality and maturity.

- **Build and Customize Our Story Bank**

  - We should prepare core EM stories that demonstrate a range of leadership abilities and adverse situations.
  - The goal isn’t perfection but authenticity—sharing how we made decisions, what we learned, and how we’ve grown as a result.

- **Showcase Growth Through Adversity**

  - Most interview questions center around difficult moments. We should use these opportunities to demonstrate emotional maturity, resilience, and our ability to evolve—crucial traits for a leader.

- **Be Convincing and Confident**

  - At the end of the day, we’re not just answering questions—we’re telling a story about why we’re the best fit. We need to sell our value clearly and confidently, grounded in real experience and reflection.

Common Questions

If you want direct interview support from Alex and Uzair, take their live Maven course with discount code **TARO10**: <https://maven.com/alex-kliotzkin/acing-em-interviews>

In this video, we explore the behavioral side of engineering manager (EM) interviews, which focus heavily on leadership abilities. Each question is designed to assess core leadership competencies, and mastering these areas is critical for success.

- **Hiring & Growing Talent**: Interviewers look for evidence of managing underperformers, nurturing strong performers, and navigating hiring and talent review processes.
- **Delivery Under Pressure**: Candidates must demonstrate the ability to lead high-quality project deliveries on tight timelines, despite resource constraints or setbacks.
- **Stakeholder Management & Influence**: Expect to showcase how difficult feedback was delivered or how stakeholders were influenced for team benefit, often through challenging conversations.
- **Conflict Resolution & Judgment**: Questions will probe how candidates handle internal or external conflicts, as well as how strategic decisions were made with limited data.
- **Vision & Execution**: Interviewers want to hear about setting long-term vision, taking calculated risks, digging deep into complex problems, and operating effectively across all levels.

Leadership Bar

If you want direct interview support from Alex and Uzair, take their live Maven course with discount code **TARO10**: <https://maven.com/alex-kliotzkin/acing-em-interviews>

In this lesson, the instructor explains the core attributes that engineering manager (EM) interviewers, especially directors and above, look for when hiring. Unlike IC roles, EM hiring is predominantly trust-based and focused on leadership capabilities over technical depth.

- **Behavioral Over Technical**: 80% of the EM hiring decision is based on behavioral criteria like trustworthiness, resilience, and ownership, while only 20% is focused on technical competency such as architecture and system design.
- **Understand the Decision-Maker’s World**: Directors and VPs prioritize reliability, communication skills, and the ability to handle uncertainty and people problems over deep technical expertise.
- **Subjective Evaluation**: EM interviews aren’t about getting “right” answers. Instead, they're conversational and context-driven, evaluating fit with the team, culture, and leadership expectations.
- **Demonstrate Ownership and Initiative**: Candidates must show extreme ownership, proactive problem-solving, and the ability to deliver results, even outside formal responsibilities.
- **Adapt Communication**: EMs need to adjust messaging depending on the audience, from engineers to upper leadership, showing mastery in stakeholder communication.

Engineering Manager Misconceptions

If you want direct interview support from Alex and Uzair, take their live Maven course with discount code **TARO10**: <https://maven.com/alex-kliotzkin/acing-em-interviews>

This segment dispels a common myth in engineering leadership: that an engineering manager must be the most technically knowledgeable person on the team. Instead, it reframes technical leadership as an exercise in empowerment and strategic growth—both for the team and for the manager.

- **Technical mastery is not a requirement for effective engineering management.** The core responsibility is ensuring delivery, not being the smartest person in the room.
- **Empowering the team to deliver independently** fosters a stronger, more resilient team and allows individual contributors to grow.
- **A high-functioning team that performs well without direct intervention** is a strong reflection of a manager’s leadership, not a sign of irrelevance.
- **Delegating technical ownership frees the manager to focus on bigger-picture strategic initiatives**, technical direction, and organizational influence.
- **Letting go of ego is essential**—leaders grow by creating impact at scale, not by micromanaging every decision or technical detail.

EM vs. IC

If you want direct interview support from Alex and Uzair, take their live Maven course with discount code **TARO10**: <https://maven.com/alex-kliotzkin/acing-em-interviews>

This segment breaks down the fundamental differences between the roles of individual contributors (ICs) and engineering managers (EMs), using a structured view to clarify the contrast in scope, responsibility, and domain expertise. It emphasizes how transitioning from IC to EM is a **career shift**, not a promotion, due to the shift in focus from implementation to strategy and people leadership.

- **ICs focus deeply on implementation and domain expertise**, such as full-stack, cloud, embedded, or AI systems. They are vertical specialists with strong knowledge in their technical area.
- **ICs also operate within the software engineering realm**, applying practices like CI/CD, agile processes, and architecture—but mainly to support their implementation work.
- **EMs must be experts in software engineering best practices**, not just to implement them but to ensure sustainable development and product integrity across the team.
- **The core domain of EMs is technical leadership**, which includes stakeholder management, translating business needs into technical goals, strategic planning, communication, and team mentorship (i.e. areas ICs typically don't engage with).
- **Managing both delivery and team dynamics** makes the EM role distinctly broader, requiring versatility across both technical and people-focused domains.

Weekly Business Review

###### In this lesson, we introduce the **Weekly Business Review (WBR)** as Amazon’s core mechanism for consistently analyzing, improving, and controlling business performance. This structured, weekly ritual helped us align leadership around metrics, dive deep into customer experience, and create a culture of truth-seeking and operational rigor.

### Key Takeaways:

- **We used the WBR to bridge strategy and detail**: Contrary to conventional advice, we didn’t choose between high-level strategy and operational detail—we embraced both. The WBR let senior leaders dive deep while still steering big-picture strategy.
- **We built the WBR around the customer journey**: Our report flowed from financials to marketing, browsing, shopping, fulfillment, and customer support. Each department leader owned and explained their metrics—not analysts—ensuring accountability and depth.
- **We started before everything was perfect**: We launched the WBR even before our metrics were fully refined. By including many metrics upfront, we learned over time which ones provided signal and which were noise.
- **We continuously refined our metrics**: In each WBR meeting, we didn’t just review results—we asked whether we were measuring the right things and how to improve clarity and relevance of our metrics.
- **We made it a disciplined habit**: Reports were automated and delivered every Monday by 7 a.m., enabling prep ahead of the all-company WBR. This rhythm created organizational focus, enabled early issue detection, and aligned everyone around the brutal facts of performance.

The WBR was not just a meeting—it was a **weekly dose of operational truth** that made Amazon more customer-obsessed, data-informed, and execution-focused.

To dive deeper into Input Metrics Mastery and learn more from Bill and Colin, follow these links:

- Take the full course at their website: <https://workingbackwards.com/>
- Buy the book: <https://www.amazon.com/Working-Backwards-Insights-Stories-Secrets/dp/1250267595>
- Bill's LinkedIn: <https://www.linkedin.com/in/bill-carr/>
- Colin's LinkedIn: <https://www.linkedin.com/in/colinbryar/>

The Do's and Don'ts For Good Metrics

Here's the exercise worksheet: [Metrics Template and Worksheet Combined (B2C + B2B)](https://firebasestorage.googleapis.com/v0/b/tech-career-growth.appspot.com/o/courses%2Fslides%2FMetrics%20Template%20and%20Worksheet%20Combined%20\(B2C%20%2B%20B2B\).xlsx?alt=media&token=3951bfd7-ef9e-4c81-9245-80043a4973d0)

In this wrap-up, we assign a powerful, hands-on homework exercise: to generate a **comprehensive set of input and output metrics** that can answer three foundational business questions. This process, built on the tools and frameworks we've covered, is the first real step in building a metrics-driven, customer-obsessed organization.

### Key Takeaways:

- **We focus on three key questions**:

  1. How did our business do last week?

  2. What was the customer experience like last week?

  3. Are we on track to hit our goals?

- **We use four core methods to identify input metrics**:

  1. **Metrics Mapping** – Drill down from business goals to uncover metric drivers.

  2. **Customer Experience Mapping** – Map and measure every customer interaction.

  3. **Customers** – Mine support data and engage with end users directly.

  4. **Defects** – Use root cause analysis (like CoEs) to find and track preventable errors.

- **We cast a wide net—hundreds of metrics is a good start**: This is not about picking the “best” metrics yet. We brainstorm 200–300 across all functions without concern for whether they’re inputs or outputs, or even if they can be measured immediately.

- **We avoid vague or compound metrics**: Good metrics are discrete, observable, and repeatable by different people or systems. Avoid averages where possible—percentiles and RMS error are often better indicators of variation and performance.

- **We assign priorities and assess data readiness**: After brainstorming, we tag each metric as Priority 1, 2, or 3 and indicate whether the data is currently available. This helps build a phased implementation plan for metrics collection and review.

This assignment launches the foundational work needed to operationalize a **weekly business review (WBR)**. It sets the stage for measurement, analysis, improvement, and control—ensuring our teams are focused on the right inputs to drive the right outcomes.

To dive deeper into Input Metrics Mastery and learn more from Bill and Colin, follow these links:

- Take the full course at their website: <https://workingbackwards.com/>
- Buy the book: <https://www.amazon.com/Working-Backwards-Insights-Stories-Secrets/dp/1250267595>
- Bill's LinkedIn: <https://www.linkedin.com/in/bill-carr/>
- Colin's LinkedIn: <https://www.linkedin.com/in/colinbryar/>

Building A Metrics Map

In this lesson, we explore **practical techniques** for identifying the input metrics that matter most. Through methods like **metrics mapping** and **customer experience mapping**, we gain a clearer, more quantitative view of what drives our business forward—especially from the customer’s perspective.

### Key Takeaways:

- **We prioritize input metrics and customer interactions**: Too often, businesses rely heavily on output metrics. We recommend looking deeper into input metrics—particularly those tied to customer behavior and experience.
- **Metrics Mapping helps us discover drivers of key metrics**: We start with a business goal or known metric, then recursively ask what drives it and how we can measure those drivers. This technique reveals a broad and useful set of input metrics.
- **The process is recursive and comprehensive**: We drill down from each metric or goal until we can’t go any further, building an extensive network of quantifiable drivers. Repeating metrics across branches is fine—what matters is completeness.
- **The end goal is a flat, exhaustive list of metrics**: While the mapping exercise may begin as a hierarchy, we ultimately compile all the discovered metrics into a single, non-hierarchical list for practical use and monitoring.
- **Finding input metrics is an ongoing process**: This isn’t a one-time task. We continuously revisit and expand our metric set as our business, goals, and customer needs evolve.

To dive deeper into Input Metrics Mastery and learn more from Bill and Colin, follow these links:

- Take the full course at their website: <https://workingbackwards.com/>
- Buy the book: <https://www.amazon.com/Working-Backwards-Insights-Stories-Secrets/dp/1250267595>
- Bill's LinkedIn: <https://www.linkedin.com/in/bill-carr/>
- Colin's LinkedIn: <https://www.linkedin.com/in/colinbryar/>

Improve

In the Improve phase, we focus on **deploying resources and initiatives** that shift our input metrics in the right direction, knowing that this in turn drives our desired output results. Improvement at Amazon has always been a cycle of innovation, experimentation, and rigorous measurement.

### Key Takeaways:

- **We prioritize inputs to drive results**: We align our teams, projects, and resources around improving leading indicators—our input metrics—which ultimately influence lagging outputs like sales and customer retention.
- **Click to Deliver Time became a key input metric**: We tracked every step of the fulfillment process and launched targeted initiatives to speed up delivery, knowing it directly impacted customer satisfaction and engagement.
- **We scaled operations through iterative improvements**: Over two decades, we grew our global delivery infrastructure—fulfillment centers, delivery stations, air cargo, and driver networks—through thousands of iterative changes, many of which were experiments that included both successes and failures.
- **We formalized improvement with the Working Backwards PR/FAQ process**: This mechanism ensures we innovate from customer needs, forcing teams to start with a press release and FAQ to define how a proposed improvement solves real problems.
- **Improvement and analysis form a feedback loop**: Every improvement is followed by measurement and analysis. This iterative cycle lets us reinforce what works and eliminate what doesn’t, ensuring continuous refinement of our systems.

To dive deeper into Input Metrics Mastery and learn more from Bill and Colin, follow these links:

- Take the full course at their website: <https://workingbackwards.com/>
- Buy the book: <https://www.amazon.com/Working-Backwards-Insights-Stories-Secrets/dp/1250267595>
- Bill's LinkedIn: <https://www.linkedin.com/in/bill-carr/>
- Colin's LinkedIn: <https://www.linkedin.com/in/colinbryar/>

Master the Art of Receiving Quality Feedback (from an ex-Meta Staff Researcher)

In this time of uncertainty in the workplace and job market, what’s one skill you can develop that would **yield disproportionate rewards**?

It’s hard to pinpoint *the one* skill, but I believe the **ability to ask for, receive, and iterate on feedback** is incredibly important. Adaptability is what helps us not just survive, but thrive—and adaptability begins with how well we take in and work with feedback.

When you learn to process feedback effectively, **you develop a kind of likability and professional superpower** that organizations and leaders find hard to ignore.

We hear feedback all the time, so what exactly are we trying to get better at? Most of the feedback we receive is vague and hard to act on. Think about examples like “improve your communication” or “increase your coding speed”—where do you even start? The **key is in asking for feedback** proactively, clarifying and chunking it down into something actionable, working on it, and then circling back to check if you’ve understood and implemented it well.

In this talk, we’ll learn how to do exactly that—a process I call “**exhausting the feedback process**,” a phrase I often use in my coaching practice. We’ll also explore how to handle feedback that’s just plain off the mark (spoiler: it’s rarely useful to say that outright to the person giving it).

Yogi on LinkedIn: <https://www.linkedin.com/in/yogi1/>

Tech Career Growth Videos

Our instructional videos provide software engineers with insights needed for career growth. Masterclasses go incredibly in-depth on a specific tech topic while case studies are real examples from established engineering leaders.