Actionable AI help, without the hype.
AI is changing everything, but most of what you hear is noise. If you are a CTO, engineering manager, or technical founder and feel pressure to deliver AI results, you are not alone. New AI products appear every day, and it is hard to know what is real and what is hype.
I have spent years as a founder and CTO. I’ve tested many AI tools and techniques, and learned what actually works now. I use AI every day to speed up my work, and I can help your team do the same.
For more view my services or join my newsletter below:
Hi, I’m Chris.
- I co-founded Cherrypick, a VC-backed AI startup in food retail.
- I bootstrapped a software agency to $1M ARR as CEO, hiring a team of 12. The company became internationally known for great software practices.
- I scaled Gower Street, a film data analytics company, as CTO from a handful of people to over 50 staff.
- I have shipped two LLM-based AI systems to production, complete with evals.
“Fantastic at building self-sufficient teams and giving them what they need.” – Tadas T
“If you’re looking for someone to help build a great team, or you need someone experienced to help develop a sound tech strategy, I would thoroughly recommend Chris.” – Roisi P
“Chris has clearly learned a lot about the world of being a delivery-focused CTO” – Ian O
The Huge List of AI Tools: What's Actually Worth Using in May 2025?
There are way too many AI tools out there now. Every week brings another dozen “revolutionary” AI products promising to transform how you work. It’s overwhelming trying to figure out what’s actually useful versus what’s just hype.
So I’ve put together this major comparison of all the major AI tools as of May 2025. No fluff, no marketing speak - just a straightforward look at what each tool actually does and who it’s best for. Whether you’re looking for coding help, content creation, or just want to chat with an AI, this should help you cut through the noise and find what you need.
Read moreUnlocking Real Leverage with AI Delegation
Starting to delegate to AI feels awkward. It is a lot like hiring your first contractor: you know there is leverage on the other side, but the first steps are messy and uncertain. The myth of the perfect plan holds many people back, but the reality is you just need to begin.
The payoff is real, but the start is always a little rough.
Here is how I do it.
Read moreHow I Make Complex AI Changes
Most technical leaders know the pain. You get partway into an ambitious AI project, then hit a wall. You are not sure how to start, or you get so far and then stall out, lost in the noise of options and half-finished experiments.
Recently I tackled this head on. I did this live, in front of an audience. I used a framework that finally made the difference.
The challenge: could I take a complex change, break it down, and actually finish it, live on stream? My answer: yes, with the right approach. Here is exactly how I did it.
Read moreBuilding 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.
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I use the term “software craft” to refer to the software craftsmanship movement that emerged from the Agile Manifesto and was formalised in the Software Craftsmanship Manifesto of 2009. The movement emphasises well-crafted software, steady value delivery, professional community, and productive partnerships. I prefer the terms “crafting” and “craft” to avoid gender assumptions. ↩
Hiring Startup Engineers: a field manual
Hiring engineers is the most important part of building your startup. It requires significant attention and a systematic approach. A good process combined with clear evaluation criteria will set you up for success.
This field manual covers the essential aspects of hiring your first few crucial engineering roles.
Read moreWhy 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.
Read moreIntroducing 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.
Read moreBuilding 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.
Read moreThe Reality of AI Power Usage
AI power usage generates significant controversy. Headlines paint it as an environmental catastrophe waiting to happen. The reality proves more nuanced and potentially more optimistic than these dire warnings suggest.
A ChatGPT query uses 10 times more energy than a Google search. This sounds alarming until one realises it equates to running your hairdryer for six seconds. The entire data centre industry, including all AI operations, accounts for just 1.5% of global electricity consumption.
Here is a rundown of the more pressing issues with AI power usage.
Read moreSee the Archive for more articles. You can also find me on BlueSky, X and LinkedIn. Subscribe with RSS to keep up with the latest.