The Huge List of AI Tools: What's Actually Worth Using in May 2025?

Building AI Cheatsheet Generator Live: Lessons from a Four-Hour Stream

I built an entire AI-powered app live, in front of an audience, in just four hours. Did I finish it? Not quite. Did I learn a huge amount? Absolutely. Here is what happened, what I learned, and why I will do it again.

The challenge was simple: could I build and launch a working AI cheatsheet generator, live on stream, using AI first coding and Kaijo¹ as my main tool?

Answer: almost! By the end of the session, the app could create editable AI cheatsheets, but it was not yet deployed. A few minutes of post-stream fixes later, it was live for everyone to try. (Next time, I will check deployment on every commit!)

Try the app here: aicheatsheetgenerator.com

AI: The New Dawn of Software Craft

AI is not the death knell for the software crafting movement. With the right architectural constraints, it might just be the catalyst for its rebirth.

The idea that AI could enable a new era of software quality and pride in craft is not as far-fetched as it sounds. I have seen the debate shift from fear of replacement to excitement about new possibilities. The industry is at a crossroads, and the choices we make now will define the next generation of software.

But there is a real danger: most AI coding assistants today do not embody the best practices of our craft. They generate code at speed, but almost never write tests unless explicitly told to. This is not a minor oversight. It is a fundamental flaw that risks undermining the very quality and maintainability we seek. If we do not demand better, we risk letting AI amplify our worst habits rather than our best.

This is the moment to ask whether AI will force us to rediscover what software crafting¹ truly means in the AI age.

Why Graph RAG is the Future

Standard RAG is like reading a book one sentence at a time, out of order. We need something new.

When you read a book, you do not jump randomly between paragraphs, hoping to piece together the story. Yet that is exactly what traditional Retrieval-Augmented Generation (RAG) systems do with your data. This approach is fundamentally broken if you care about real understanding.

Most RAG systems take your documents and chop them into tiny, isolated chunks. Each chunk lives in its own bubble. When you ask a question, the system retrieves a handful of these fragments and expects the AI to make sense of them. The result is a disconnected, context-poor answer that often misses the bigger picture.

This is like trying to understand a novel by reading a few random sentences from different chapters. You might get a sense of the topic, but you will never grasp the full story or the relationships between ideas.

Real understanding requires more than just finding relevant information. It demands context and the ability to see how pieces of knowledge relate to each other. This is where standard RAG falls short. It treats knowledge as a stack of random pages, not as a coherent whole.

Time for a totally new approach.

Introducing Kaijo: AI functions that just work

For months, I have wrestled with a problem that has consumed my thoughts and challenged everything I know about software development.

This week I wrote about building the future with AI agents. One of the key areas for me is moving beyond prompt engineering to something more reliable.

I have spent decades learning how to craft reliable software. Now I want to bring that reliability to AI development.

Today I am ready to share what I have been building in the background.

It started with a game. It ended with something that could change how we build AI applications forever.

Building the Future

Something has been on my mind for months. The rapid evolution of AI agents has opened up possibilities I cannot ignore.

We are witnessing the emergence of semi autonomous agents that will fundamentally reshape how we work and communicate. The opportunities in this space are extraordinary. I am diving deeper into this world of AI agent development and product creation.

My newsletter is evolving. Instead of dispensing tips from a position of authority, I invite you on a journey of discovery. I will document my experiences building with AI, how to apply my tech experience in a new world, and navigating the inevitable struggles and setbacks.

Read on for several key areas I am exploring.