Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases

Session led by [Dharin Shah](https://www.linkedin.com/in/dharinshah/)

In this session, we delve into the intricacies of Amazon Aurora, a high throughput, cloud-native relational database designed to meet the demanding scalability and performance requirements of modern applications without compromising on the simplicity of access via SQL. The paper presents a thorough examination of the design considerations that underpin Aurora's architecture, understanding how it achieves unparalleled levels of efficiency and reliability within the cloud. We will explore key concepts such as Aurora's distributed and decentralized approach, fault tolerance mechanisms, and the optimization of data storage and retrieval processes.

Taro Book Club: Designing Data Intensive Applications - Chapter 4 (Encoding And Evolution)

Session Led by: [Lax Meiyappan](https://www.linkedin.com/in/lakshmanan-meiyappan/)

Topic: Chapter 4 - Encoding And Evolution

In this #taro-bookclub discussion, we'll be talking about Chapter 4 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 4.
- There will also be time for any questions and answers you might have.

Please send your questions ahead of time to [**Lax Meiyappan**](https://www.linkedin.com/in/lakshmanan-meiyappan/) 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!

Taro Book Club: Designing Data Intensive Applications - Chapter 2 (Data Models and Query Languages)

Discussion led by: [Ankur Agrawal](https://www.linkedin.com/in/erankuragr/) & [Raj Shah](https://www.linkedin.com/in/therajshah/)

Topic: Chapter 2 - Data Models and Query Languages In this #taro-bookclub discussion, we'll go over Chapter 2 of the book "Designing Data-Intensive Applications" by Martin Kleppmann. This chapter is about Data Models and Query Languages and will provide good mental models to think about Relational vs Document Models, Graph Data Models and various types of Query Languages.

Here's the agenda: We’ll break down and discuss the key concepts from Chapter 2. There will also be time for any questions and answers you might have.

Get ready for our second session on this engaging and informative book! If you don't have a Taro Premium membership, you can get it at a discount with Ankur's special link here: <https://www.jointaro.com/r/eventu507/>

Event Link: <https://www.jointaro.com/event/taro-book-club-designing-data-intensive-applications-chapter-2-data-models-and-query-languages/>

Ace Your Tech Interview As A Software Engineer [Part 27] - Hiring Manager Round (Separate)

Congratulations, you went through the onsite loop and did well! But what's this - The engineering director behind the job you're interviewing for wants to talk? This lesson teaches you:

- When separate hiring manager rounds happen (and why that's a good thing)
- How to pass hiring manager rounds and what to expect from them

Paper Reading - Attention is All You Need

Paper Discussion led by [Mandar Deshpande](https://www.linkedin.com/in/mandardeshpande1995/)

"Attention is All You Need" is a seminal research paper published by researchers at Google in 2017, introducing the Transformer model. The paper revolutionized natural language processing and machine translation by proposing a new architecture that relies solely on self-attention mechanisms, eliminating the need for recurrent or convolutional layers.

This paper and the Transformer model it introduced are crucial in the context of Large Language Models (LLMs) for several reasons:

- Parallelization
- Long-Range Dependencies
- Efficient Attention
- Mechanism Pre-training and Transfer Learning

We will be discussing the internals of the Transformer architecture which will help guide our journey into the LLM space.

Paper link - <https://arxiv.org/abs/1706.03762?ref=blog.oxen.ai>\
Event link - <https://www.jointaro.com/event/paper-reading-attention-is-all-you-need/>

Paper Reading - Gemini: A Family of Highly Capable Multimodal Models

Paper Discussion led by: [Akshika Wijesundara PhD](https://www.linkedin.com/in/akshika/)

Abstract: Google researchers recently unveiled Gemini, a ground breaking family of multimodal AI models capable of understanding and reasoning across images, audio, video, and text. The largest Gemini model, Ultra, achieved human-expert performance on several benchmarks and advanced the state of the art across a range of multimodal tasks.

In this paper reading, we will discuss key details from Google's paper introducing Gemini models. Topics will include:

- The Gemini model architectures and how they achieve cross-modal understanding
- Performance benchmarks and state-of-the-art results across text, image, audio, and video tasks
- Applications and use cases enabled by Gemini's multimodal reasoning
- Approaches to responsible deployment of large language models like Gemini

This paper provides a comprehensive overview of the exciting new capabilities of Google's Gemini project. Whether you're an AI researcher, engineer, or simply curious about the state of the art in multimodal AI, join us for an in-depth look at this new model family.\
\
Paper link: [**https://arxiv.org/abs/2312.11805**](https://arxiv.org/abs/2312.11805)\
Event link:  **[https://www.jointaro.com/event/paper-reading-gemini-a-family-of-highly-capable-multimodal-models/](https://www.jointaro.com/event/paper-reading-gemini-a-family-of-highly-capable-multimodal-models/)**

Are you a PIP risk? The Ultimate Guide To Navigating A PIP

The most obvious way to identify if you’re at risk for a PIP is if you’ve received poor ratings in prior performance review cycles. But this is a **lagging indicator**, so it may be too late to do anything at this point. Ideally, we’d like a **leading indicator** so you can take steps to avoid a PIP by discovering the warning signs early enough. 

The best leading indicators are: 

- Check-in with your peers and managers and get feedback
- Compare markers of progress: code output, design docs, and updates on tickets of projects. 

On the topics of ratings, you should understand the breakdown of what percent of employees get each rating. Companies may not reveal this info directly, so you can ask your manager or look up internal documentation.

If your manager and teammates start ignoring you or removing your scope, that’s an unhealthy sign.

Why Companies Do PIPs: The Ultimate Guide To Navigating A PIP

A PIP can seem cruel, but there’s a clear reason that companies use them year after year. Let’s start with the top priority for a manager: ensure the optimal performance of the team. For a manager, getting their reports promoted or singing their praises is important, but only insofar as it’s in service of the optimal performance of the team.

Another detail to realize is that the high performers on any team do an outsized amount of work. This is especially true in jobs that have tremendous leverage for the most skilled workers, such as software engineering (thus the famed “10x engineer”). When a company is large enough, a “bell curve” of performance will emerge. A PIP is focused on the employees who are deemed as low performers, typically the bottom 10% of the bell curve.

So, returning back to the original question: the reason why companies do PIPs is to **ensure optimal productivity and impact** for the overall employee base. If high performers sense that poor performance is not being addressed, they may leave the team. So a PIP is a way to push poor performers off the team.

The company also wants to push people out in a way that **minimizes the chance of a lawsuit**. Even though employment in the US is at-will, there’s still a chance of getting sued if the employee argues that they were fired for an illegal reason (e.g. due to a protected characteristic).

The company or manager may claim that the PIP is designed to help you, but that’s almost never the case. They’re more concerned about minimizing the negative impact on the broader team.

Finally, PIPs are often “weaponized” to fire people under the guise of performance when the company doesn’t want to call it a layoff. This is especially relevant now in the current economy as companies may enter an age of austerity.

PIP Stereotypes - The Ultimate Guide To Navigating A PIP

Given the secrecy and consequences of PIPs, you've probably a bunch of stereotypes about PIPs. This is a non-exhaustive list of beliefs that are simply not true:

- *"You must be incompetent or lazy"*
- *"Your manager or company must be horrible"*
- *"It’s impossible to keep your job on a PIP"*
- *"You'll no longer be employable"*

This thinking is reductive and will lead to more harm than good. A better way to think about a PIP is not to cast blame on one party or another. Instead, a PIP means **there was a mismatch in expectation between employee and employer**. 

The reality is that there are many potential reasons why you may receive a PIP, ranging from lack of support, poor management, lack of motivation, shifting company needs, etc.

Throughout the PIP process, one of the most difficult parts is that you’ll feel zero (or negative) support from key people around you. In order to find success at your job, and more broadly in your career, **you need to be an advocate for yourself**. Have the confidence that you are valuable. Too many engineers are their own worst critic, which exacerbates the negative spiral of performance.

Leaving An Executive Role To Become A Teacher

[**Ethan Evans**](https://www.linkedin.com/in/ethanevansvp/) is a retired Amazon VP who now teaches managers how to break into executive levels. He was at Amazon for 15 years, and he became a VP in 2013 until he left in 2020.

Ethan could have spent several more decades in high-powered engineering leadership roles, but he chose to leave his lucrative career at Amazon to focuse on personal development coaching and teaching.

**Reason for leaving Amazon:**

- Ethan found more satisfaction in helping people develop than building things. He actually wanted to scale his impact beyond at Amazon with the role of upgrading the whole eng team.
- Amazon wasn't receptive to his ideas for talent development initiatives. they told him the best bet was for him to become the VP of Eng for the HR products.

**Today, Ethan is focused on** teaching individuals for career development. He creates and shares free content (e.g., daily writing on LinkedIn) and then offers paid coaching and training programs for high-potential individuals.

**Motivation for charging for some services:**

- Belief that people value paid services more than free ones.
- Desire to focus limited time on highly motivated clients.
- Money is not the primary driver but it is important for reaching a wider audience and sustaining the work.
- Charging for high-value services from those who can afford it is ethical and practical.

Ethan is now pursuing his passion to help people grow and achieve their career goals. He's adopted a hybrid approach of free and paid services to maximize their impact and reach.

More to explore: 

- [\[Case Study\] Building An Engineering Brand - Why And How (LinkedIn, YouTube, Twitter, Substack)](https://www.jointaro.com/lesson/t06NajpS2kSCk98IEmQm/case-study-building-an-engineering-brand-why-and-how-linkedin-youtube-twitter-substack/)
- [When does it make sense to leave big tech?](https://www.jointaro.com/question/v6GBLlfXb1ugNobkEm7w/when-does-it-make-sense-to-leave-big-tech/)
- [I'm Greg, Ex-Google/Netflix current Director at Disney. AMA!](https://www.jointaro.com/question/CdPjNOXvU882180yzs6R/im-greg-ex-googlenetflix-current-director-at-disney-ama/?a=X1zCA1EgxqdSBELHLfkO)

The Sales Engineering Career Path (And How To Become One)

The sales engineering role combines technical expertise with sales skills as an alternative career path. Even if you don't want to become a full-time sales engineer, many of the skills that are essential for sales engineers are directly applicable for strong software engineers.

🛠️ **Learn Why Engineers are in the Best Position to Sell:**

- Explore the intersection of coding and client interaction that defines the Sales Engineering role.
- Learn why Sales Engineering might be the ideal choice for software engineers looking to blend their technical prowess with business dealings.

💡 PRO TIP: **Sales Presentation and Demo Flow For the Best Outcomes:**

- Gain insights into the advantages of pursuing a career in Sales Engineering, from enhanced earning potential to dynamic job roles.
- Understand how your unique skill set can significantly impact client-facing roles within the technology industry.

🔍 **Explore What Career Options Exist in Sales Engineering:**

- Explore different career paths within Sales Engineering and understand the growth potential.
- Learn about real-world success stories from software engineers who have transitioned into Sales Engineering roles.

Taro member discount is available for the [**2-week cohort-based course**](https://maven.com/techsales/sales-for-software-engineers?promoCode=TARO).

Course conducted by: [**https://www.linkedin.com/in/kbalachandran/**](https://www.linkedin.com/in/kbalachandran/)

Explore more on Taro: 

- [Should I become a sales engineer?](https://www.jointaro.com/question/CZdBlFzIDk4rxaLJ1jzu/should-i-become-a-sales-engineer/)
- [How do you "sell" your work and show impact as an aspiring Staff Engineer?](https://www.jointaro.com/question/Zr5koQ1TGgx8GzSAquwG/how-do-you-sell-your-work-and-show-impact-as-an-aspiring-staff-engineer/)

This Is What A Good Promotion Plan Looks Like

One of the most crucial ingredients for a successful promotion is a clear plan. However, the engineering career matrix that most big companies have isn't nearly enough. This video covers what a quality promotion plan looks like.

Here are the core points from the video:

- **Show the delta** - Just giving someone a concept isn't enough. Growth comes when you progress from a lower state to a higher one. To best facilitate that, you must outline exactly what that lower state and higher state are so people can understand the difference and work towards bridging the gap.
- Here's an example showing what it means to outline the delta when growing a mid-level engineer on their code review axis:
  - **Bad promotion plan:** *"Have a bigger influence in code review"*
  - **Good promotion plan:**
    - E4 (mid-level): *"You are extremely thorough catching issues within your own domain, finding architectural issues (sometimes challenging the entire diff/diff stack), performance problems, and several edge case misses."*
    - E5 (senior): *"Instead of mainly reviewing stack-specific diffs within product domains you have worked on, you review diffs across the entire stack for your org (M2+ scope). You are able to review diffs for areas that you have never worked with before, quickly absorbing the context of the diff and its surrounding ecosystem to leave genuinely insightful feedback in a relatively short period of time.”*

Related resources:

- [\[Taro Top 10\] Software Engineer To Engineering Manager (IC -&gt; M Track)](https://www.jointaro.com/playlist/oz0mnJvHHgM8NfVF7rgp/)
- [\[Masterclass\] What Software Engineers Should Look For In Their Engineering Manager](https://www.jointaro.com/lesson/oeY7ncZhzJ5NO6dij5e7/masterclass-what-software-engineers-should-look-for-in-their-engineering-manager/)
- [\[Taro Top 10\] Getting Promoted Faster In Tech](https://www.jointaro.com/playlist/eZOEUatYEe7BBAZByuha/)

What Does An Engineering Manager Actually Do?

In order to work together optimally with your engineering manager (EMs), you should have a great understanding of their perspective and incentives.

Here are the core points from the video:
- **Engineering managers shouldn't do technical work** - They need to influence the code of the team without writing it, reviewing it, or designing it. This is an extremely hard job.
- **So what specifically do EMs do?** - Ultimately the EM's goal is to make the team land impact, and this can manifest in many different ways (some of which engineers don't want to hear about). If you are a good performer, it's in the manager's best interest to foster your talent and grow you. If you aren't (i.e. you're dragging the team down), it's possible the manager believes firing you to be the best choice for the team. Outside of managing performance, there are tasks like removing non-technical blockers and making people work better together that EMs do to keep the impact engine going.

Related resources:
- [[Taro Top 10] Software Engineer To Engineering Manager (IC -> M Track)](https://www.jointaro.com/playlist/oz0mnJvHHgM8NfVF7rgp/)
- [[Masterclass] What Software Engineers Should Look For In Their Engineering Manager](https://www.jointaro.com/lesson/oeY7ncZhzJ5NO6dij5e7/masterclass-what-software-engineers-should-look-for-in-their-engineering-manager/)

How Rahul Accidentally Got 70k Installs On An Android App

### The Story
- Before 2021, Rahul's YouTube channel was focused on Android tutorials.
- One of the tutorials he made was a simple Android app that let you set your status as an emoji. It was a pretty basic example of using Firebase.
- To make the output of the tutorial accessible, Rahul published the completed app to Google Play.
- What he didn't realize is that the app would be discovered by tens of thousands of users. After the past couple years, it has gotten 70,000+ installs with near-0 effort from Rahul.

### Learnings
- *Always publish* - So many people make projects that they then abandon or declare victory after the GitHub has gotten to a good state (even sharing this on their resume). Your code will pretty much never matter until it's fully out there in the world - If you're looking for your projects to help with job searching, recruiters are not going to care how clean the GitHub is.
- *Android distribution is extremely powerful* - Android has over 2.5 billion active users, and that number continues to grow. Due to the sheer volume of people, Android is one of the easiest platforms, if not **the** easiest platform, to publish something that gets a ton of users. There are far fewer Android apps compared to websites, so it's easier competing for Google Play search traffic vs. Google website search traffic. You only need to pay a 1-time $25 fee to publish an infinite amount of apps.

If you want to learn how to build your own side projects that get a ton of users:
- [In-depth Session On How To Come Up With Side Projects That Can Get 100k+ Users](https://link.jointaro.com/4m3CpQGgvkN3Xuem9)
- [In-depth Session On How To Grow Side Projects To 500k+ Users](https://link.jointaro.com/8QPgCkexjUjR9AA29)

The Cardinal Sin Of Management: Micromanaging

This segment outlines why micromanagement is a hallmark of poor engineering leadership and how effective managers empower their teams instead of controlling them. It offers a comprehensive look at how hands-off, trust-based leadership enables better team performance and growth.

- **Micromanagement is a red flag**: Hovering over engineers’ work or constantly asking for status updates wastes time, erodes trust, and stifles ownership.
- **Effective managers lead through trust and empowerment**: Autonomy allows engineers to make decisions and own outcomes, with structured check-ins (e.g., weekly or bi-weekly) to stay aligned.
- **Staying out of technical weeds is critical**: A manager's role should focus on people, not code reviews, engineering meetings, or day-to-day task assignments—those should be handled by tech leads or the engineers themselves.
- **Micromanagement creates systemic risks**: It builds dependency, slows down team velocity, and makes the manager a single point of failure. If the manager leaves, the team may lack the tools or confidence to function independently.
- **Lack of trust leads to poor career growth**: Engineers under micromanagement are less likely to take initiative or learn leadership skills, hindering their path to promotion and long-term development.

Understanding The $$$ Behind Stock Options - Hypothetical Startup Example

This video uses a hypothetical example from Carta to illustrate how startup stock options can lead to financial gain—or loss—depending on the company’s trajectory. It highlights both the upside potential of a successful IPO and the downside risk if the company underperforms.

- A fictional employee joins a startup, *Meatly*, in January 2020 and receives 16,000 stock options at a $1 strike price. After two years, 8,000 options (50%) have vested.
- When the company IPOs at $5/share, the employee exercises the options, spending $8,000 for shares now worth $40,000—a **$32,000 profit**.
- Alternatively, if the employee exercises at departure and the company later sells for only $0.75/share, the same $8,000 purchase yields **just $6,000 in value**, resulting in a **$2,000 loss**, not including taxes.
- This example underscores that **stock options carry real financial risk**, unlike RSUs, which are granted outright and do not require upfront payment.
- Employees need to carefully consider market performance and timing before exercising options to avoid losses.

ESPP Explainer With Tips On How To Navigate It

This section explains the **Employee Stock Purchase Plan (ESPP)**, a more traditional and common form of stock-based compensation compared to RSUs. ESPPs are typically found at companies outside the top-tier tech firms and offer employees a way to invest in their employer's stock at a discount.

- **What ESPP Is:** ESPP allows employees to purchase company stock at a discounted rate—usually 10% to 15% off the market price—using a portion of their base salary.
- **How It Works:** Employees allocate up to 10% of their salary into a fund, which is periodically used to buy company shares. Unlike RSUs, employees pay to acquire the shares.
- **Tax Implications:** The discount is considered taxable income because it's effectively a financial gain (e.g., buying $100 stock for $85 means $15 in taxable benefit).
- **Differences from RSUs:** RSUs grant a fixed number of shares, regardless of stock price fluctuations, while ESPP is tied to monetary investment and stock price dynamics, often using an average price over time.
- **General Advice:** Though the gains may be smaller and the system slightly more complex, ESPP is considered “free money” and is worth maximizing when financially feasible.

How You Can Supercharge Your Team - Discovering Synergies

What's Changing With AI-Assisted Coding Interviews?

In this lesson we talk about the rise of AI-assisted coding interviews and how they are changing the technical interview landscape.

- **Understand the new AI-assisted coding interview format:** Learn how modern interviews place you in a lightweight codebase (not a blank file) with existing helper functions, tests, and to-dos—plus an integrated AI chat panel that can access and assist with your code.
- **Navigate increased problem complexity:** Explore how today’s interviews include more substantial starter code, realistic product requirements (e.g., time zones), and sometimes more advanced algorithms and data structures—reflecting real engineering work.
- **Collaborate effectively with AI while staying in control:** Discover best practices for using the built-in AI strategically, communicating your thinking clearly, and maintaining ownership of the solution in a rapidly evolving interview landscape.

The AI Frontier: Get Paid To Build Smarter LLMs

The future of AI is being built by a handful of companies: OpenAI, Anthropic, and DeepMind, among others. One of the core ingredients for improving the performance of LLMs is the use of reinforcement learning from human feedback (RLHF).

Join us for a live conversation with Mercor's cofounder and CTO, [**Adarsh Hiremath**](https://www.linkedin.com/in/adarsh-h-623941204) hosted by Taro's cofounder and CEO, [**Rahul Pandey**](https://www.linkedin.com/in/rpandey1234/). Mercor is a key partner to enable RLHF for many frontier model companies. As part of this, Mercor offers 1000s of part-time, remote-friendly roles with competitive compensation.

This is a new type of white-collar work that involves debugging, validating, and creating scenarios for LLMs. As the capabilities of models improve, the expertise required to train models keeps increasing. One of the highest-priority areas is around coding, which means Software Engineers have a special role to play in this type of work.

This event explains the pros and cons of AI lab gig work, what exactly the work entails, and how much you can earn.

Some topics we’ll cover:

- Typical hourly rates and the compensation model
- Project-to-project variability
- Unique challenges of remote collaboration in this type of work
- What does the day-to-day look like with this type of work?
- How does this work impact the development of LLMs and AI agents?
- How will this work evolve over the next 5 years?

There will also be time for open Q&A from the audience.

Mercor is an AI-powered recruiting platform that has become one of the largest sources for human labor for foundation model companies. Mercor has raised more than $100 million dollars and is located in San Francisco, CA. Explore [**relevant jobs on Mercor here**](https://work.mercor.com/?referralCode=91aab11f-ce55-40b3-9c2d-f74576cac28f) (100+ Software Engineering jobs available).

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.