Engineering the future of AI development
Insights on agent reliability, skills automation, token economics, and building systems that work.
A GTM lead, a senior dev reviewer, and Claude Code replaced a web agency. Here's the architecture behind Flowpad's website — and why the stack matters more than the tool.
Read article59.4% of tokens go to agents re-reading their own work. Demand for AI compute is outpacing supply, and prices are already climbing. The AI coding subsidy is ending. Here's what comes next.
512,000 lines of Claude Code accidentally went public. We checked every viral claim against the actual code - here's what was real, overstated, or invented.
Five real tests of Fable 5 on our own codebase: security, performance, QA, refactoring and async. The numbers, the wins, and the open problems.
30 minutes to demo, 3 years to production. Why prompt tweaking won't survive. How ML 2.0 reframes AI workflow development.
Developers have stopped writing code and started training developer models. A mental model for the brute-Dev era: programming by examples, edge cases, and the Three Zones of Supervision.
AI is not intelligence. It is a communication shift, a new paradigm to program machines simply by talking to them. Using this mental model will reframe how teams adapt, filter noise, and focus on what matters.
AI agents aren't a factory assembly line. Complexity theory explains why they keep breaking, and why observability beats control.