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Talented but stuck? Guidance changes everything.

Let me be honest with you.

Most engineers I've met are not stuck because they lack talent. They’re stuck because no one taught them how careers work. They don’t know how promotions are decided. They struggle to build influence without authority. They find it hard to navigate Big Tech politics. They also need to learn how to lead teams when the playbook runs out.

I spent 11+ years figuring that out the hard way. Now I want to shortcut that journey for you.

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IS THIS YOU?

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→ You're a talented engineer. Yet, you often miss out on leadership roles.

→ You just became a manager and nobody told you how different this game actually is

→ You're an EM who wants to grow to Director but can't see the path clearly

→ You're building a team and want to hire, retain, and lead A-players

→ You're driven. You know yourself. You're ready to take charge of your career.

If you nodded at even one of those — keep reading.

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WHAT THE GUIDED GROWTH IS

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This is not a course you'll forget about. It's not a community where content gets posted into a void. It's a lively space for real career talks, and I’m there in person.

As a member, you get:

→ Monthly Live Mentorship Sessions

Share your real situation. Are you aiming for a promotion? Facing a skip-level? Dealing with a team that's falling apart? We work through it live, together.

→ Career Coaching Frameworks That Actually Work

I help engineers find EM jobs at Google and Amazon. I use simple systems. These include positioning, storytelling, and managing stakeholders.

→ The Guided Growth Newsletter — Members First

Essays on engineering leadership. Insights on career strategy. Learn what makes great leaders different. You get it before anyone else.

→ A Peer Network Worth Having

Selected pros who want to grow. Talk with others in this community. It will boost your potential.

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WHY LISTEN TO ME?

──────────────────────

I'm Abhishek. Senior Engineering Manager at Walmart Global Tech. Former Engineering Manager at Google for 3.5 years. Stanford LEAD Alumni. ISB VC & PE cohort. Angel investor. India's #1 LinkedIn Creator with 167,000+ followers.

But here's what actually matters:

I've conducted 650+ interviews. I know exactly what separates the people who get the role from the people who don't. I've mentored more than 1,100 engineers. This includes ICs who want their first lead title. It also has senior managers taking on director roles. I've seen what helps careers. I’ve seen what holds them back. I’ve also noticed what people don’t talk about.

I share all of it — without the sugarcoating.

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A NOTE ON COMMUNITY SIZE

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I'm keeping this community intentionally small. A large community is easy to build. A high-quality one is hard. I’d prefer 200 members who truly care over 2,000 who just watch.

When you join, you're not a number. You're someone I actually want to see win.

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Each month, you handle your career alone. Someone else is getting ahead. They have similar skills but better guidance.

Your growth doesn't happen by accident. It happens by design.

I'll see you inside.

Abhishek Kumar

Free

1. Access to private peer network
2. Resume & job hunt resources
3. Recurring office hours
4. 20% off on all paid events

The Guided Growth Circle

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The Guided Growth

Brett Jordan

Most engineers do not fail system design because they lack intelligence.They fail because nobody ever taught them how to think about it. They read a few blog posts. They watch a video the night before. They memorise an architecture diagram for a URL shortener and hope the question is close enough.Then someone asks "why did you choose that database?" and the whole thing falls apart.This course fixes that.

Every system design answer starts with a trade-off you agreed to make.

This section covers the CAP theorem: why a distributed system cannot give you consistency, availability and partition tolerance at the same time, and what you are really choosing between when you pick one.

Get this wrong and every later decision is guesswork. Get it right and most design questions answer themselves.

L1 CAP Theorem

1. Foundations - The Core Trade-offs

The biggest section in the course, and the one that shows up in every interview.

We start with transactions and isolation levels, because you cannot judge NoSQL until you know what guarantees you are giving up. Then we go through the NoSQL families one at a time: document, key-value, in-memory, graph, time-series, and when each one is the right call.

The second half is scale. Vertical versus horizontal. Replication in all four shapes: leader-follower, multi-leader, leaderless, and how they compare. Then sharding and partitioning.

By the end you can pick a database and defend the choice.

L1 Transactions and Database Isolation Levels

L2 NoSQL - Document Databases

L3 NoSQL - Key-Value Databases

L4 NoSQL - In-Memory Databases

L5 NoSQL - Graph Databases

L6 NoSQL - Time-Series Databases

L7 Database Selection - Q and A

L8 Database Scaling - Vertical vs Horizontal

L9 Database Scaling - Replication Overview

L10 Replication - Leader-Follower

L11 Replication - Multi-Leader (Part 1)

L12 Replication - Multi-Leader (Part 2)

L13 Replication - Leaderless

L14 Replication - Methods Compared

L15 Sharding and Partitioning

2. Databases & Storage: Choosing, Scaling & Transactions

One server is easy. Ten servers is a routing problem.

This section covers what a load balancer actually does, the different types, and how session persistence works when a user's requests land on different machines. Then the algorithms: how traffic gets distributed, and what breaks with each approach.

We finish with consistent hashing. It looks like a small idea. It is the reason your cache and your shards survive a node going down.

L1 Load Balancer - Fundamentals

L2 Load Balancer - Types and Session Persistence

L3 Load Balancer - Algorithms

L4 Consistent Hashing

3. Absorbing Traffic: Scalability & Load Balancing

Caching is the cheapest performance win you will ever ship. It is also where most systems quietly go wrong.

We cover the foundations and the real use cases first. Then the decisions: write-through or write-back, and which eviction policy fits your traffic. Then how caches scale into a distributed cache.

The last part maps caching by location: CDN, database cache, remote cache, so you know which layer to reach for.

Two Q&A lessons cover the questions that come up again and again.

L1 Caching Foundation - Introduction

L2 Caching Foundation - Use Cases

L3 Cache Writing Policies

L4 Cache Writing - Q and A

L5 Cache Eviction Policies

L6 Cache Scaling and Storage - Distributed Cache Design

L7 Caching Levels

L8 Caching Levels - Q and A

L9 Cache Types by Location - CDN

L10 Cache Types by Location - Database Cache

L11 Cache Types by Location - Remote Cache

4. Making It Fast: Caching

Systems get fragile when everything talks to everything, right now, synchronously.

This section is about breaking that. Message queue fundamentals across two lessons, then Apache Kafka: what it is, how it works, and why it turned up in almost every architecture diagram of the last decade.

L1 Message Queue Fundamentals (Part 1)

L2 Message Queue Fundamentals (Part 2)

L3 Apache Kafka - Fundamentals

5. Decoupling at Scale: Messaging & Queues

One entry point in front of many services.

Routing, authentication, and the work you stop repeating in every service once a gateway sits at the front door.

L1 API Gateway - Fundamentals

6. The Front Door: API Gateway

Things fail. Good systems fail well.

We start with circuit breakers: how to stop one slow service from taking down everything behind it. Then rate limiting across three lessons: why you need it, where it sits, and how it protects you from traffic you did not plan for.

The section closes with the rate limiting algorithms themselves: token bucket, leaky bucket, and the rest, and the trade-offs between them.

L1 Fault Tolerance - Circuit Breaker

L2 Rate Limiting and Traffic Protection (Part 1)

L3 Rate Limiting and Traffic Protection (Part 2)

L4 Rate Limiting and Traffic Protection (Part 3)

L5 Rate Limiting - Algorithms

7. Staying Up: Reliability & Resilience

Before services can be designed, they have to talk.

Three lessons on how network communication actually works, and how to pick the right protocol for the job.

L1 Network Communication Fundamentals (Part 1)

L2 Network Communication Fundamentals (Part 2)

L3 Network Communication Fundamentals (Part 3)

8. How Services Talk: Communication Protocols

Sometimes "probably not" is a good enough answer, and it costs almost nothing.

Bloom filters let you check membership in a huge set using very little memory. They save your database from lookups that were never going to find anything.

L1 Bloom Filters

9. Bloom Filters

Everything above, applied.

We start with capacity estimation: the back-of-the-envelope maths that opens every design discussion. Then nine design problems worked end to end: BookMyShow, WhatsApp, a parking lot, ChatGPT, a flash sale system, a notification service, and a product listing system.

Each one is solved the way you would in the room. Requirements, constraints, the design, and the trade-offs behind every choice.

This section keeps growing. New problems get added as they are recorded.

System Design 101

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