
When generation is free, knowing which AI…
MIT and Wharton data shows massive upstream code gains that fade before release. The highest-leverage move is killing bad agent diffs before they reach a human reviewer.

MIT and Wharton data shows massive upstream code gains that fade before release. The highest-leverage move is killing bad agent diffs before they reach a human reviewer.

DORA's 2025 survey of nearly 5,000 tech professionals shows universal AI adoption and persistent skepticism about generated code. Here is how I wire trust-but-verify without killing throughput.

Newsletter deep dives on AI coding bottlenecks all land on the same fix: move verification earlier. Here is how I wire test agents and CI loops so human review focuses on risk, not syntax.

Agents write at machine speed. Humans still own merge. An Agentic Development Lifecycle playbook: guardrails, test agents, review tiers, and what to discard before it hits your queue.

MIT and Wharton tracked 100,000+ GitHub developers through the full pipeline. Code volume explodes. Shipping barely moves. What the attenuation effect means if you run agents today.