Be Very Visible

In this lesson, we focus on the importance of visibility in the IC–manager relationship by making sure our EM always knows what we’re doing, where we’re succeeding, and where we need help.

- We emphasize assuming our EM has *no idea* what we’re working on; their schedule is chaotic, especially for high-performing managers, so visibility must come from us.
- We recommend over-communicating: CCing them on major updates, posting milestones publicly, and adding them as optional attendees to key meetings so they can see our impact firsthand.
- We note that joining high-stakes meetings (like SEV investigations) gives managers direct visibility into our leadership, problem-solving, and alignment skills.
- We highlight that 1:1s are the most valuable channel for surfacing wins, blockers, and complex problems that require “manager API powers.”
- We reinforce that visibility builds organizational reputation and that one of the traits managers value most is strong communication, where bad news early is fine, but surprising bad news is not.

Amazon Behavioral Interview [Part 19] - Taking An Unpopular Stance (Answer)

This video segment describes a situation where the interviewee took an unpopular stance in a meeting with leadership.

- **Identified the Conflict:** The interviewee disagreed with the company's decision to significantly shift resources from the US to India for customer support, primarily driven by cost-cutting measures.
- **Presented an Alternative Solution:** Despite the potential for backlash, the interviewee proposed an alternative solution:
  - While acknowledging the cost-effectiveness of hiring in India, they suggested leveraging the "Year Up" program to hire underrepresented talent in the US, aligning with the company's diversity and inclusion goals.
- **Faced Opposition:** The interviewee faced strong opposition from the CFO, who was primarily focused on cost-cutting measures and reacted negatively to the alternative proposal.
- **Continued to Advocate:** Despite the initial setback and lack of immediate recognition, the interviewee continued to advocate for the inclusion of the "Year Up" program.
- **Achieved Partial Success:** While the initial proposal was largely dismissed, the company eventually implemented a limited version of the "Year Up" program, demonstrating the long-term impact of the interviewee's advocacy.

This example highlights the interviewee's: ***Proactive Approach:*** *They identified a potential solution that aligned with company values.* **Courage and Persistence:** They were willing to express their dissenting opinion despite potential negative consequences. ***Focus on Long-Term Impact:*** *They demonstrated a commitment to long-term goals, such as diversity and inclusion, even when faced with immediate pressures.* **Ability to Learn and Adapt:** They acknowledged the limitations of their initial approach and demonstrated a willingness to adapt and find alternative solutions.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

How Managers Hire Great Engineers [Part 25] - Conclusion

Congratulations on making it to the end of the course! Please go and hire awesome people now :) 

Connect with John Egan on LinkedIn: <https://www.linkedin.com/in/jwegan/>

Amazon Behavioral Interview [Part 18] - Handling Unclear Expectations From Leadership (Evaluation)

This video segment provides feedback on an individual's response to a behavioral interview question about navigating conflicting priorities.

- **Strengths:**

  - **Acknowledged the Challenge:** The interviewee effectively described the challenging situation of balancing conflicting demands from leadership: driving customer satisfaction while maintaining employee engagement.
  - **Highlighted Key Actions:** They mentioned implementing strategies to improve customer satisfaction, such as focusing on key metrics like CSAT and time to resolution.
  - **Acknowledged Limitations:** The interviewee honestly acknowledged the limitations of their efforts, such as the loss of a valuable employee due to the challenging work environment.

- **Areas for Improvement:**

  - **Focus on Employee Engagement:** While the interviewee mentioned some efforts to improve employee morale, such as virtual happy hours, they could have further emphasized their proactive steps to address employee concerns and improve engagement.
    - This could include:
      - Implementing regular feedback mechanisms (e.g., surveys, one-on-one meetings).
      - Advocating for employee well-being initiatives.
      - Proactively addressing employee concerns and seeking solutions.
  - **Quantify Impact:** Instead of stating that they were "semi-successful," the interviewee could have quantified their impact by:
    - Describing specific improvements in employee engagement scores.
    - Highlighting successful initiatives that improved both customer satisfaction and employee morale.
  - **Demonstrate Proactive Problem-Solving:** The interviewee could have further emphasized their proactive problem-solving skills by:
    - Describing how they identified the root cause of the conflicting demands.
    - Explaining how they developed and implemented innovative solutions to address the challenges.
    - Highlighting how their actions led to positive and lasting change within the team and organization.

- **Overall:** The interviewee provided a solid foundation for their response. By incorporating the suggested improvements, they can further enhance their ability to effectively communicate their accomplishments and demonstrate their leadership, problem-solving, and results-oriented approach in a job interview setting.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Q&A: Acing Tech Interviews In A Bad Job Market

Check out the full 4.5+ hour course diving even deeper into this session's concepts: [\[Course\] Ace Your Tech Interview And Get A Job As A Software Engineer](https://www.jointaro.com/course/ace-your-tech-interview-and-get-a-job-as-a-software-engineer/)

Get Taro Premium at a discount with our special link here: <https://www.jointaro.com/r/achiou15/>

As a Taro Premium community member, you can get personalized advice from proven tech leads like Alex and Rahul at any time by starting career discussions in our forum and joining [Group Office Hours](https://www.jointaro.com/event/group-office-hours-with-alex-career-direction-company-offer-evaluation-jan19/). 

This is the Q&A portion of the 1-hour session we did about finding interview success in a bad job market. You can watch that session here: [Acing Tech Interviews In A Bad Job Market](https://www.jointaro.com/lesson/Vz4jXfFIeQSSSzonpvH0/acing-tech-interviews-in-a-bad-job-market/)

Related resources for the questions in this video:

- [\[Masterclass\] How To Ace Your Big Tech Interview - Data Structures And Algorithms](https://www.jointaro.com/lesson/V4sTACzfOh22nMVcUV3w/masterclass-how-to-ace-your-big-tech-interview-data-structures-and-algorithms/)
- ["How can I get more internships?"](https://www.jointaro.com/question/k8TNvbobgU1R7ICDWKus/how-can-i-get-more-internships/)
- [\[Masterclass\] How To Choose A Good Company And Team As A Software Engineer](https://www.jointaro.com/lesson/0WEmTNZOMIh8xAdfO3JH/masterclass-how-to-choose-a-good-company-and-team-as-a-software-engineer/)

Why He Built (And Shut Down) A Meta Internal Tool for Pseudonymous Communication

Lack of Control

Engineers at Big Tech often experience a deep lack of control over their work, compensation, and long-term impact. Here are the core points from the lesson:

- Politics and top-down decision making mean engineers can invest heavily in projects only to have leadership reject ideas or directions with no recourse
- Compensation elements like company multipliers are tied to overall corporate performance, which individual engineers have virtually no influence over
- Constant reorgs, shifting org charts, and manager reshuffling create instability and make teams feel like they’re moving for reasons that aren’t always merit-based
- Big Tech frequently kills projects, even promising or widely used ones, because they don’t meet multibillion-dollar expectations, leaving engineers demoralized and powerless over product fate

The How of the Engineering Career Ladder: Five Essential Foundations for Advancement

Session led by [Shine Garg](https://www.linkedin.com/in/shinegarg/)

Engineering career ladders lay out the “what” of the software engineering career path—what competencies and behaviors are needed at each milestone. However, they often lack guidance on the “how.”

Understanding how—and how quickly—you can acquire and exhibit these competencies significantly impacts your career trajectory, financial future, and sense of fulfillment in life.

This talk demystifies the process of climbing the engineering career ladder. Join us to learn the five essential foundations for advancing your career and achieving your goals.

So What Do Engineering Managers Do?

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>

An engineering manager’s role extends far beyond attending meetings or writing reports—it centers on one core responsibility: *Ensuring the team delivers*. This requires balancing accountability, leadership, and adaptability across multiple domains.

- **Facilitate Decision-Making and Own Processes:** EMs don’t always make every decision, but they must facilitate the decision-making process and ensure team adherence to defined practices like quality standards or definitions of done.
- **Own Delivery Outcomes:** Regardless of who does what on the team, the EM is ultimately responsible for all deliverables—both successes and failures.
- **Bridge Business and Engineering:** EMs connect the technical team with the broader business, helping engineers understand customer needs, product lifecycles, and why building the *right* thing is more important than just building it right.
- **Ensure Product Integrity and Fill Gaps:** Maintaining consistent product quality across releases is part of the EM's responsibility. They must also step into roles as needed—whether that’s scrum master, product owner, or project manager—to remove blockers and enable progress.
- **Represent the Team and Grow Talent:** EMs act as the external face of the team to stakeholders and leadership while also coaching and developing individual engineers to help them grow in their careers.

Ship & Grow 500k+ User Side Projects [Part 13] - Observe Your Users

If you're at this point in the course, you now deeply understand why feedback is great. However, the vast majority of users simply won't provide you with feedback. This lesson teaches you:

- How most end-users will behave with your side project (and any product really)
- What you should do proactively to extract signal from as many users as possible
- Important metrics to track when observing your users
- A great free tool you can use to see exactly how users are interfacing with your product

You can try PostHog here: <https://posthog.com/>

Algorithms You Must Master

In this section, we get a clear roadmap of the **core algorithms** we need to master for ML algorithm coding interviews. These are foundational models that balance simplicity with depth—perfect for testing both theory and implementation skills under time pressure.

- For **clustering**, we should be able to implement **k-means from scratch**, including centroid initialization, assignment, recomputation, and convergence checks. We should also understand evaluation metrics like inertia and silhouette score.
- For **linear models**, we must code **linear and logistic regression** with gradient descent, using proper loss functions and optionally adding **L1/L2 regularization**.
- For **tree-based methods**, we should implement a **basic decision tree**, and if time allows, understand how **random forests** build on it using bagging and bootstrapping.
- In **k-nearest neighbors**, we focus on **distance calculations** (Euclidean vs. cosine) and how to retrieve the top-k neighbors for a query point.
- Lastly, for **neural networks**, we should know how to build a **simple feedforward network** with one or two hidden layers and train it using **backpropagation**, including activation functions like ReLU and sigmoid, along with their gradients.

By preparing these specific algorithms, we’ll be equipped to handle most ML algorithm coding interviews with confidence and precision.

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**](https://calendly.com/your-friend-yayun/1on1)
- Follow her on LinkedIn: [**https://www.linkedin.com/in/yayunjin/**](https://www.linkedin.com/in/yayunjin/)

How Managers Hire Great Engineers [Part 23] - Building Relationships

Social capital is incredibly important when hiring. From this lesson, you will:

- Learn about the importance of building relationships in recruitment, similar to how VCs generate deal flow
- Discover the strategy used by Benjamin Nazad, who leveraged academic directories to network with potential contacts in the VC industry
- Understand that cultivating relationships with each candidate can significantly enhance the likelihood of closing them during the hiring process
- Recognize the long-term value of maintaining relationships even when there are no immediate job openings, facilitating quicker recruitment when positions become available

Connect with John Egan on LinkedIn: <https://www.linkedin.com/in/jwegan/>

Live AMA with Casey Dai - Former Head of Engineering & Founder of Expanded Skills

[Casey Dai](https://www.linkedin.com/in/caseydai/) is a career switcher, Head of Engineering, and entrepreneur based in Canada. After getting a finance degree, he worked in consulting before switching to engineering and quickly climbed the ranks to become the Head of Engineering at Capgemini, a multi-billion dollar IT company. 

Topics covered in this Ask Me Anything (AMA):

- What are the most underrated skills for SWEs and EMs?
- How do I future-proof my skills to stay competitive in the tech industry when things are constantly changing?
- Why are there a lot of bad managers? Is there anything that can be done to prevent that?
- How do I identify opportunities to scale my impact?
- How do I become a better decision-maker when faced with uncertainty?
- What are some ways to grow aside from the company career ladder?

Casey will go **in-depth on these topics in [his upcoming course](https://www.jointaro.com/event/operate-like-an-engineering-leader-cohort-based-course/)** starting Jan 16th.

Enroll in Casey's cohort-based course Operate Like An Engineering Leader and receive a free 1:1 coaching session: [**https://www.jointaro.com/event/operate-like-an-engineering-leader-cohort-based-course/**](https://www.jointaro.com/event/operate-like-an-engineering-leader-cohort-based-course/)

Ethical Concerns

Working at Big Tech can expose engineers to ethical dilemmas and reputational challenges, especially as these companies grow in size and societal influence. Here are the core points from the lesson:

- **Ethical baggage and public scrutiny** - Every large tech company accumulates controversy over time, from privacy scandals to monopolistic behavior. Employees often face external judgment and may feel conflicted about the company’s broader impact, such as gentrification and social displacement caused by high salaries and rapid expansion.
- **Disconnect between purpose and individual contribution** - Engineers may feel demoralized realizing their role (e.g., being engineer #80,532 at Google) probably won't meaningfully contribute to making the world a better place - especially for those motivated by social impact or purpose-driven work.
- **Reputation can shift dramatically** - Facebook was once viewed positively (e.g., in the late 2000s), but public perception reversed dramatically after scandals like Cambridge Analytica. Engineers went from proudly wearing company swag to avoiding brand affiliation in public. Similar sentiment shifts can hit any big company, even well-intentioned ones.
- **Moral complexity of innovation and market power** - As companies grow in influence and value, their innovations may disrupt other industries, leading to job loss or social backlash. While sometimes justified in capitalist terms, the ethical line becomes murkier when dominance is maintained through questionable means.

Taro Book Club: Designing Data Intensive Applications - Chapter 7 (Transactions)

Topic: Chapter 7 - Transactions

Session lead by [**Raj Shah**](https://www.linkedin.com/in/therajshah/), [**Raghu Kalyan**](https://www.linkedin.com/in/graghukalyan/), and [**Kevin Wu**](https://www.linkedin.com/in/wkevn/) 

In this #taro-bookclub discussion, we're having a session about Chapter 7 of [**"Designing Data-Intensive Applications"**](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321) by Martin Kleppmann.

Here's the agenda:

- We’ll break down and discuss the key concepts from Chapter 7
- There will also be time for any questions and answers you might have

Get ready for another engaging and informative session!

Ship & Grow 500k+ User Side Projects [Part 16] - Word Of Mouth

The most organic source of traffic is happy users simply telling their network how awesome your product is. This lesson teaches you:

- The main metric to understand when it comes to your word of mouth
- 2 product mechanisms you can add to juice up your word of mouth
- How to make an effective sharing flow, explained with an in-depth example
- How to make a compelling referral flow, shown with famous examples

Airbnb blog post about how they sharply refined their sharing flow (an oldie but a goodie): <https://medium.com/airbnb-engineering/growth-at-scale-getting-to-product-sharing-fit-ccb4b501ecf>

Taro Book Club: Designing Data Intensive Applications - Chapter 5 (Replication)

Topic: Chapter 5 - Replication

Session led by: [Rohit Katyal](https://www.linkedin.com/in/rohitkatyal/)

In this #taro-bookclub discussion, we'll be talking about Chapter 5 of [**"Designing Data-Intensive Applications"**](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321) by Martin Kleppmann.

Here's the agenda:

- Let’s get to know each other with some quick introductions.
- We’ll break down and discuss the key concepts from Chapter 5.
- There will also be time for any questions and answers you might have.

Please send your questions ahead of time to [**Rohit Katyal**](https://www.linkedin.com/in/rohitkatyal/) in the [**Taro Premium**](https://www.jointaro.com/membership/) Slack, so that they can be included in the discussion.

Get ready for another engaging and informative session!

What Are Advanced Concepts I Should Know?

In this lesson we talk about how to effectively prepare for AI-assisted coding interviews, with a focus on shifting your study habits to match what these interviews actually test.

- **Learn the "why" before the "how"** — rather than drilling implementations, focus on understanding the canonical problem each data structure solves and practice explaining it in one sentence out loud; with AI handling the code, being unable to independently identify the right approach is now much harder to hide or compensate for.
- **Know the common gotchas for each pattern** — every classic structure has a specific edge case trap (e.g. the `is_end` flag in a trie, recency updates in an LRU cache, off-by-one errors in sliding windows); getting familiar with these upfront dramatically speeds up your ability to verify AI-generated output during the interview.
- **Practice reading code, not just writing it** — since interviews now involve more time spent reading starter code and verifying AI output than typing from scratch, deliberately train yourself to mentally trace logic quickly by reading existing solutions online or having AI generate code for problems you already understand, then tracing through them by hand.

How To Debug Effectively with AI As My Partner?

In this lesson we talk about how to debug effectively with AI as a partner during a coding interview, and when to use it versus when to rely on your own judgment.

- **Use AI to generate more test cases, but step through code yourself** — AI can rapidly produce test cases that would take much longer to write manually, but since it predicts words rather than executing code, it can reproduce the same bugs it originally introduced, making it unreliable for tracing logic line by line.
- **Avoid leaning on AI for debugging, but use it strategically when stuck** — rather than asking AI to find or fix a bug directly, prompt it to brainstorm multiple possible causes, which keeps you in the driver's seat, surfaces hypotheses for you to validate with your own judgment, and reduces the risk of confidently wrong AI suggestions.
- **Always rerun all tests after a fix, not just the failing one** — thorough test coverage lets passing tests serve as reliable verification; if your test suite is thin, compensate with more manual code inspection to avoid introducing regressions you won't have time to track down later.

Amazon Behavioral Interview [Part 25] - Working Outside Of Your Domain (Answer)

This video segment describes a situation where the interviewee took on a project outside their core responsibilities to improve employee engagement at Google.

- **Identified a Problem:** The interviewee noticed that employee engagement scores were low, particularly regarding the perception of fair and transparent promotions.
- **Took Initiative:** The interviewee proactively identified this issue and proposed a solution: creating an anonymous feedback system to gather data on employee perceptions of promotion fairness.
- **Implemented a Solution:** The interviewee worked with HR to develop and implement the "Perfolution" system, which collected anonymous feedback from employees on promotion decisions.
- **Achieved Positive Results:** The system successfully gathered valuable data, which was then used to identify areas for improvement in promotion processes. This resulted in a significant improvement in employee engagement scores related to promotion fairness.
- **Demonstrated Initiative and Collaboration:** This example demonstrates the interviewee's initiative, problem-solving skills, and ability to collaborate effectively with other teams (HR) to achieve a positive impact.

This example effectively demonstrates the interviewee's: 

- ***Proactive approach:*** *Identifying a critical issue and taking the initiative to address it.* 
- **Problem-solving skills:** Developing and implementing a creative solution to gather data and identify areas for improvement. 
- ***Collaboration and teamwork:*** *Effectively collaborating with HR to implement the solution and address the identified issues.* 
- **Focus on employee engagement:** Demonstrating a commitment to improving employee satisfaction and well-being. 
- **Ability to drive positive change:** Successfully implementing the solution and achieving a significant improvement in employee engagement scores.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

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.