Cut Through The AI Chaos

I help leaders leverage AI to transform their teams
and dodge the chaotic hype that wastes time and money

Chris Parsons

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"I joined Chris's webinar on using Claude skills to run parts of his business and it genuinely blew my mind. I spent the entire weekend trying to get AI to run my life as well."

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More About Chris

Chris Parsons

I've been a CTO and founder. I've scaled companies whilst building production AI systems and transformed delivery using AI tools.

5
Startups Founded
2
Startups VC-backed
$1M+
ARR Bootstrapped
4
AI Systems Shipped to Production

Experienced Tech Founder

Scaled teams from 5-50. Built agencies, B2B, and B2C startups. VC-backed and bootstrapped experience.

AI Systems Expert

Production AI systems with full evaluation frameworks, not demos. Real systems serving 500K+ users.

Delivers Fast

25 years in tech leadership. I go into organisations and deliver value fast, for leaders who need results now.

What Leaders Say

"Fantastic at building self-sufficient teams and giving them what they need."

"Chris has a wealth of experience on both the CTO side and the AI-enablement side. He's fun to work with, thoughtful and sitting at the cutting edge."

"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."

"Chris has helped me and my teams stay up to date and re-imagine what is possible. He's demonstrated novel ways to get the most out of the new technology on many occasions."

"Chris is an invaluable part of the UK AI ecosystem."

"Great person to go to to work out what really works and what doesn't in AI for software development and the wider business."

I learn in public and share everything I discover

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CTO Craft: March 2026

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Production AI Systems

Three evaluation frameworks built

From Cherrypick's meal generator to complex internal tools, I build systems with robust evaluation from day one

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Latest Articles

How I Use AI to Code

April 2026
How I Use AI to Code

If you are still tied to your IDE, whether Cursor or Copilot, you are working a year behind. Coding turned out to be AI’s home territory. The best tooling has moved out of the editor and onto the command line, and the senior engineer’s job is to train the AI, not review its output.

I wrote the previous version of this post in March 2025, updated it once in August, and it has been linked from almost everything I have written about AI engineering since. The fundamentals from that post still hold: keep changes small, build guardrails, document ruthlessly, and make sure every change gets verified before it ships. One thing has had to move with the volume. “Verified” used to mean “read by you”. With modern agent throughput, it has to mean “checked by tests, by type checkers, by automated gates, or by you where your judgement matters”. The check still happens; it just does not always happen in your head.

One distinction has hardened over the last year, and it matters for what follows: vibe coding and agentic engineering are different practices. Vibe coding, where you do not really check the results and just look at the output, is fine unless you are shipping. Agentic engineering is the other thing. It does not mean reading every diff. It means making a measured call about which diffs need your eyes and which do not. I tend to skim UI diffs. I read security and database diffs carefully.

That judgement, about where to spend your attention, is itself a senior skill and one worth getting good at. Every diff still gets checked; not always by you. Tests, type checkers, and automated gates pick up the rest, and you are training the agent so the diffs that do reach your eyes are the ones worth the attention. Conflating the two is how people end up shipping vibe-coded output into production and getting burned.

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Truman Would Have Taken Over AI by Now

April 2026
Truman Would Have Taken Over AI by Now

Anthropic announced the most powerful cyberweapon ever built last week and kept it, granting access to forty companies while the US government got a press release. Harry Truman, who nationalised atomic research inside three years, would not have stood for it.

Project Glasswing, Anthropic’s cyberdefence initiative, restricts Claude Mythos to a named coalition including AWS, Apple, Google, Microsoft, NVIDIA, and JPMorgan Chase, on the grounds that the model is too dangerous for public release.1 Mythos finds vulnerabilities in every major operating system and browser autonomously, and in doing so it has already discovered a 27-year-old flaw in OpenBSD, a 16-year-old bug in FFmpeg that five million automated tests had missed, and a chain of Linux kernel vulnerabilities that allowed complete privilege escalation, though the details have held up less well under external scrutiny than they did in the press release. Anthropic holds the knowledge of how to find more, and it has decided who gets access to it.

Eight days later Anthropic shipped Claude Opus 4.7 to everybody else, with the cyber capabilities deliberately reduced during training: same lineage, defanged.2 The dangerous version goes to the coalition, the distilled version goes to the paying public, and the gap closes as the capability diffuses. Anyone who read Kokotajlo’s AI 2027 forecast last year is watching it play out on schedule.3

Washington has responded by applying for access. Senator Coons called Project Glasswing “a landmark moment”, Senator Warner urged industry to patch faster, and Treasury Department staff ignored a standing ban on Anthropic products to queue up for Mythos access anyway.4 The picture is the same across the Atlantic, where the EU AI Act is in force and the UK AI Security Institute is active, but neither treats Glasswing as a challenge to state authority. Engagement, not confrontation, is the pattern on both sides, and it looks nothing like the response Truman gave to atomic research. He did not ask for a subscription.

  1. Project Glasswing launched with forty named coalition partners and $100 million in usage credits, plus $4 million in grants to open-source security projects. Anthropic has stated it does not plan to make Mythos Preview generally available. 

  2. Claude Opus 4.7 shipped on 16 April 2026. Anthropic’s system card confirms cyber capabilities were differentially reduced during training, framing Opus 4.7 as the vehicle for road-testing safeguards before any broader Mythos-class release. 

  3. AI 2027 is a scenario forecast published in April 2025 by Daniel Kokotajlo and collaborators, predicting rapid capability scaling inside private labs, cyber capability as an early flashpoint, coalition arrangements forming to manage dangerous release, and governance lagging the technology by a wide margin. The forecast is broadly tracking reality a year in. 

  4. Senator Coons praised Project Glasswing as a “landmark moment”; Senator Warner called on industry to accelerate patching; the White House confirmed it is engaging with AI companies on vulnerability remediation, even as federal agencies sought Mythos access despite a standing Anthropic product ban. Treasury Secretary Bessent and Fed Chair Powell convened Wall Street chief executives on cyber risk from the model. No committee hearings, no restrictions, no takeover signals. 

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Build An AI Knowledge Base From Scratch

April 2026
Build An AI Knowledge Base From Scratch

What if the AI already knew what you were working on? What if it remembered what you decided last week, what your board presentation covers, what your team structure looks like, because it had read your notes?

That is what happens when you put Claude Code in a folder. You do not need to know how to code, and you do not need a plan for what goes in the folder. You just need something on your mind, and about ten minutes.

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