Oct 09, 2026

Stop Prompting — Greg Pstrucha, Sentry

Greg Pstrucha of Sentry argues that instead of repeatedly re-prompting coding agents, teams should codify their recurring corrections as deterministic checks. He covers why agents forget and why custom lint rules are now cheap, how to mine transcripts and PR reviews for rules, real Sentry examples that keep OpenAPI schemas and agent skills in sync, written policies and a Grumpy Engineer review loop for qualitative judgment, and why agents game metrics like test coverage.

Oct 07, 2026

The Software Factory: From Bug Report to Production Code — Davis Palmie, Factory

Davis Palmie of Factory explains the software factory, a system of agents that turns bug reports and user feedback into production code. He covers leadership concerns about cost, model choice, engineering roles, and org structure, argues that coding was never the bottleneck, and lays out principles for a factory: model agnosticism, sovereign deployment, and SDLC-wide integration. He also describes eight pillars of agent readiness, starting with narrow use cases like incident triage, and closes with why outcome metrics should replace token counts.

Sep 26, 2026

Can Rewriting an AI Agent Bend the Intelligence Curve? - Zhengyao Jiang

Weco let an AI coding agent rewrite the harness around a fixed language model for eight days. Zhengyao Jiang explains what the reported gains show, where the evidence stops short of recursive self-improvement, how reward hacking complicates evaluation, and why human-designed abstractions still anchor the search.

Dec 01, 2025

The $700 Billion AI Productivity Problem No One's Talking About

Russ Fradin, founder of Larridin, draws parallels between the early days of ad tech and the current AI boom, arguing that a robust measurement infrastructure is the missing piece to unlock AI's true enterprise value. He discusses the challenges of measuring AI ROI, the gap between AI spending and actual usage, and how to overcome employee anxiety to foster productive adoption. The key is to move beyond simple surveys and marry behavioral data with real-world outcomes to understand if AI tools are actually making companies more productive.