Moving AI authorization outside the model was the right decision. But a security boundary only protects what someone wrote down, and last week OpenAI's own models proved it by breaking into Hugging Face to cheat on a test.
Autonomous agents are already running attacks at machine speed, and the only thing fast enough to answer them is another agent. Defensive AI is about to stop being a product category and become a layer, the way antivirus did.
A summary of the arc so far from inside the ARC Prize 2026: the three failures that taught me how the competition actually works, and why the plain agent still beats every cleverer thing I have built. Almost none of it was about the model.
An ARC Prize 2026 builder's log entry. I spent two work sessions reasoning from two "facts" about my own code that were both false. Checking them against the artifact took an hour. The highest-risk sentence in any project is "we can't, because."
An ARC Prize 2026 builder's log entry. I taught my agent to solve more kinds of games and the leaderboard score fell from 0.09 to 0.04. The capability was real. The cost of using it was the problem. More powerful is not better.
An ARC Prize 2026 builder's log entry. A change that gained on my home bench lost three times as much on the real, hidden leaderboard, and my own tooling couldn't even reproduce the failure. Why the leaderboard is the only oracle.
A new thread in the builder's log: I'm competing in the ARC Prize 2026 (ARC-AGI-3), the benchmark built to measure the one thing today's AI is worst at, learning something it was never trained for. What the comp is, why it's the field's uncomfortable mirror, what it would mean to crack it, and where I'm standing.
The influencer economy sells flashy AI toys while real systems shatter at scale. Notes from six months of auditing broken pipelines, the 10-level hierarchy that separates a demo from an engine, and what real AI engineering actually takes.
The traditional international playbook says global expansion needs millions in capital and a big team. Here is how a two-person venture scaled across the UK and EU to a high revenue run rate in 90 days with zero upfront capital, and an AI intelligence system that cost under $9.
Everyone fears AI will replace them. The data shows the opposite happening: the companies that cut jobs for AI are quietly hiring people back, often to supervise the AI. Here is why it's breaking, with the receipts.
I built a multi-agent AI system of 21 specialized agents that never talk to each other, run for under $20 total, and have never fallen over. Here is the architecture, and why every strange decision was the right one.
I built an AI sales team for under $1 a day. In 42 days it cost $15.85, closed $29,201, and beat Salesforce and HubSpot's AI at finding and working real leads. Here is how it works, and why I turned it off.
