75 Days of Generative AI

Embarking on a journey of getting better at building using LLMs

Photo by Diego PH on Unsplash

In the past 14+ years working in tech, I have seen multiple hype cycles around languages, frameworks (remember when NoSQL was going to replace relational DB?), and dare I say a lot of FADs. But for some reason, LLMs feel slightly different. Reason? AI has been here for as long as we can think of and yet it keeps making a comeback thanks to advancements in computing and the availability of huge amounts of data. It's a paradigm shift that's reshaping how we think about software, data, and problem-solving itself.

So, what's this 75 Days of Generative AI all about? For the next 75 days, I'll be exploring, experimenting, and yes, probably failing a few times as I navigate the complex world of generative AI. But that's the point. Real learning doesn't happen in your comfort zone.

What's the point of this?

Accountability. The biggest reason for announcing it to everyone is to remain accountable for the next 75 days and publish my learning every day.

Building a knowledge base from scratch. One of the most exciting aspects of this journey is creating a comprehensive resource for others in the tech community. It's like building a team or a product from the ground up - you get to shape its growth and direction.

Helping someone planning to embark on a similar journey. This journey is as much about personal growth as it is about sharing knowledge. By documenting my experiences, I hope to create a valuable resource for fellow professionals navigating the AI revolution.

What to Expect

Throughout this series, you can anticipate:

• In-depth technical explanations

• Practical code examples and tutorials

• Insights into the architectural implications of AI integration

• Reflections on leadership challenges in the age of AI

• Ethical considerations and best practices

• Real-world case studies and project implementations

Join the Journey

Whether you're a seasoned tech leader, an aspiring architect, or simply curious about the future of AI in software development, this series has something for you. Follow along, share your thoughts, and let's learn together as we navigate the exciting world of generative AI.

Stay tuned for our first deep dive tomorrow, where we'll build our intuition about generative AI by exploring the revolutionary Transformers model and its evolution.

Links to day wise posts

• Day 1 - A beginners guide to LLMs ( and transformer architecture )

• Day 2- Making of a Personal Assistant ( Part 1 )

• Day 3 - Making of a Personal Assistant ( Part 2 )

• Day 4 - Running your first LLM

• Day 5 - Vector Databases

• Day 6 - Retrieval Augmented Generation - Basic Example

• Day 7 - Building your own LLM Twin

• Day 8,9 - Data Pipeline For Your LLM Twin

• Day 10-12 : Garbage In -> Garbage Out

• Day 13-15 : My LLMTwin Writes!

• Day 16 - Going beyond Basic RAG : Part 1

• Day 17 - Going beyond Basic RAG : Part 2

• Day 18 - Going beyond Basic RAG : Part 3

• Day 19 - Agents: Giving your LLM ability to run workflows

• Day 20- Knowledge Graphs: Enhancing your multi agent systems

• Day 21 - LLMOps

• Day 22 - Personal Finance via Multi-Agent LLM

• Day 23-26 – Feeding the Beast: From Bank/Credit Card Statements to Conversational Insights

• Day 27-30: From Lab to Production - Observability for Multi-Agent Systems with Opik

• Day 31-32 : Understanding Memory Types in LangGraph

• Day 33 : Why your AI product is just a prototype without proper evaluation