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.

The Onus Is On You

In this lesson, we focus on how to approach the engineering manager (EM) relationship effectively, emphasizing that our success depends heavily on how we engage, not on our manager doing everything for us.

- We stress that the responsibility for our career growth lies with us, not with our EM; they’re busy, context-switching across many reports, and can’t automatically know our needs or struggles.
- We explain that EMs need clear direction from us—without input, they can’t create opportunities, remove blockers, or advocate on our behalf.
- We compare managers to an API: they won’t initiate action on their own, but when we “call” them with the right inputs, they can be incredibly valuable resources.
- We reinforce that good managers will support us deeply if we engage correctly, but it’s our job to plug in and guide that support.
- We highlight that initiative is one of the most appreciated traits: EMs love working with engineers who proactively identify problems, propose ideas, and seek impact without needing to be pulled along.

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/>

Taking Things Further

In Part 4 of the course, we focus on how to **embed "thinking in deltas" as a daily leadership habit**. This final module emphasizes how to continuously spot and create positive, sustainable change as a manager—not just react to problems.

- **We build the habit by journaling our daily deltas**, capturing the tangible changes we influence, however small.
- **We use the journal to reframe how we think**, making it easier over time to spot opportunities for impact in individuals, teams, and systems.
- **We improve our mental well-being as managers** by recognizing our contributions and wins in a role where feedback loops are long and ambiguous.
- **We measure our success not just by outputs, but by meaningful changes we've catalyzed**—deltas we can point to as outcomes of our leadership.

Creating a daily "delta journal" isn’t just about reflection—it’s how we grow our impact and resilience as leaders.

If you want to learn more from Gilad, he shares free leadership advice daily on [LinkedIn](https://www.linkedin.com/in/giladnaor/?utm_source=taro&utm_medium=course&utm_campaign=cta) and weekly on the[ δeltas newsletter](https://posts.managementdeltas.com/?utm_source=taro&utm_medium=course&utm_campaign=cta)

Gilad’s Take: Burnt Out and Behind

In Part 3 of the course, we explored how to apply the core lesson from Part 2—creating positive and sustainable change in organizational performance—through four practical exercises. Each scenario challenged us to identify the **"deltas"** we can introduce as managers to increase impact at the individual, team, or systems level.

- **We learned to recognize that not all growth is credited to us**, and we must focus on the growth that happens *because* of our involvement—not despite it.
- **We explored supporting high performers** by making their growth more efficient (faster) and effective (more aligned with goals), rather than just letting it happen passively.
- **We tackled underperformance** by identifying root causes, offering tailored support, and protecting teammates from negative ripple effects.
- **We addressed silent group dynamics** by recognizing the power of culture and investing in small, consistent changes to build psychological safety and lasting team habits.
- **We emphasized ruthless prioritization** as a powerful delta: helping teams focus on what truly matters, not just work harder—transforming effort into sustainable outcomes.

Now, we’re ready to take this impact to the next level in Part 4.

If you want to learn more from Gilad, he shares free leadership advice daily on [LinkedIn](https://www.linkedin.com/in/giladnaor/?utm_source=taro&utm_medium=course&utm_campaign=cta) and weekly on the[ δeltas newsletter](https://posts.managementdeltas.com/?utm_source=taro&utm_medium=course&utm_campaign=cta)

Burnt Out and Behind

In this final exercise, we confront a situation where a team is putting in extra hours but still failing to meet deadlines. This signals systemic issues that go beyond individual effort—and calls for thoughtful intervention.

- We recognize that **unsustainable effort without results is a red flag**—it shows that working harder isn't the solution.
- We can introduce deltas by **investigating root causes**: Are goals unrealistic? Are priorities misaligned? Is there a process breakdown?
- It’s our responsibility to **shift focus from intensity to effectiveness**—fixing the system so performance improves without burnout.
- We look at **team norms, project planning habits, and cross-functional dependencies** to identify leverage points for change.
- Our role is to help the team **recover sustainably**, improving delivery while preserving morale and long-term capacity.

If you want to learn more from Gilad, he shares free leadership advice daily on [LinkedIn](https://www.linkedin.com/in/giladnaor/?utm_source=taro&utm_medium=course&utm_campaign=cta) and weekly on the[ δeltas newsletter](https://posts.managementdeltas.com/?utm_source=taro&utm_medium=course&utm_campaign=cta)

Gilad’s Take: System Design Meeting Non-Participation

In this reflection on team participation during design reviews, we explored how group dynamics can have a powerful influence beyond the individuals themselves. The challenge highlights the importance of managing team culture and fostering an environment where all voices are heard.

- We acknowledge that **group behaviors can persist even as individual team members change**—a reminder that team culture is distinct and durable.
- Our role is to **introduce small, consistent deltas** that collectively improve psychological safety and encourage open participation.
- We focus on **building psychological safety** by recognizing barriers to contribution and intentionally working to lower them.
- Though these efforts may seem small or slow, **they compound into deep, sustainable cultural change** that supports long-term performance.
- Strong team cultures—like ones where everyone contributes—require persistent effort, but the payoff is a **resilient and high-performing team**.

If you want to learn more from Gilad, he shares free leadership advice daily on [LinkedIn](https://www.linkedin.com/in/giladnaor/?utm_source=taro&utm_medium=course&utm_campaign=cta) and weekly on the[ δeltas newsletter](https://posts.managementdeltas.com/?utm_source=taro&utm_medium=course&utm_campaign=cta)

Notebook Interview Example: Ad Click Prediction

In this final part of the section, we bring all the core concepts together through a realistic, end-to-end ML interview example. The walkthrough demonstrates how to apply best practices across the entire notebook round—from EDA to model evaluation—with clarity, intention, and real-world relevance.

- In **EDA**, we go beyond surface checks by exploring unique value counts, visualizing target distribution, spotting class imbalance, and identifying trends like CTR by device type—ensuring every insight informs downstream modeling.
- In **feature engineering**, we thoughtfully create new features (e.g., age buckets, time-of-day flags), handle multicollinearity, and tailor transformations based on domain intuition, not just standard recipes.
- During **model training**, we justify our choice of random forest for its robustness and interpretability, apply cross-validation and stratified splits, and run grid search for tuning—demonstrating intention behind every step.
- In **evaluation**, we use metrics that align with the problem (precision, recall, F1, AUC-ROC, confusion matrix) and interpret results in context, showing we understand the real-world stakes of false positives and negatives.
- For **follow-up questions**, we proactively discuss improvements (e.g., deeper models, richer features), production monitoring (CTR by segment, drift detection), and handling class imbalance—proving we think like end-to-end ML practitioners, not just coders.

This example illustrates how to move from “checking boxes” to demonstrating thoughtful, production-aware problem-solving under real interview conditions.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

Foundational Ideas

In this key section of the course, we dive into the essential machine learning concepts that consistently appear across all types of ML interviews. This foundation prepares us to explain not just the “what,” but the “why” behind our choices—something interviewers value highly.

- We review core **ML paradigms** like supervised, unsupervised, and reinforcement learning, along with real-world examples to explain their use cases clearly.
- We explore **machine learning tasks** such as classification and regression, and when to apply specific evaluation metrics like precision, recall, or RMSE.
- We gain a deep understanding of **model performance** concepts—bias/variance trade-off, underfitting/overfitting—and how to recognize and address them.
- We cover **validation strategies**, data leakage prevention, and the right use of metrics beyond just accuracy, such as AUC-ROC and F1 score.
- We enhance our skills in **feature engineering**, **optimization algorithms** (like SGD and Adam), **model selection reasoning**, and **dimensionality reduction** techniques like PCA and UMAP.
- We also touch on **LLM fundamentals**—such as Transformers and encoder-decoder architectures—to stay current with emerging trends.
- Most importantly, we practice explaining all of this in a way that connects to real-world problems and highlights our decision-making skills.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

Course Roadmap

In this part of the course, we’re given a roadmap that outlines the full journey of preparing for machine learning interviews. Each section is designed to build our skills systematically and strategically, based on real-world experience and mentorship insights.

- We start with **essential ML concepts**, learning how to clearly explain high-frequency topics that appear in nearly every interview.
- We then move into **practical ML coding and modeling**, covering notebooks, EDA, model selection, feature engineering, and evaluation techniques.
- **Coding foundations** are reinforced to help us succeed in general algorithm rounds, with a focus on what companies expect from ML candidates.
- We’ll tackle **ML algorithm coding**, where we may be asked to implement algorithms like decision trees or k-means from scratch.
- **ML system design** is emphasized for senior-level roles, with frameworks and examples for building scalable systems.
- Finally, we prepare for **project deep dives and behavioral interviews**, learning how to share impactful stories, followed by crafting a personalized **study plan** that fits our timeline and goals.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

You listened. But not to what mattered.

It’s possible to replay the entire meeting in your head and still miss the thing they needed you to hear.

This isn’t about listening better.\
It’s about listening for something else entirely.

**Want to go deeper?**

- Explore more tools and courses at [**Taha’s Method**](https://www.tahasmethod.com/) — from interview prep to leadership development.

- Follow me on [**LinkedIn**](https://www.linkedin.com/in/tahahussain/) and subscribe to my weekly newsletter, [**The Conscious Leader**](https://tahahussain.substack.com/), for more lessons like these.

- Get 30% off [**Top Tech Leader**](https://bit.ly/tarotopleader) with code **ILOVETARO** (exclusive for Taro members).

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.