Tweet
Mar 8, 2026
AI at Work
Tweets, posts, and field notes on how people and companies are actually adopting AI at work.
-
-
Tweet
Mar 7, 2026
AI makes product judgment more important
The core claim is that AI reduces the cost of building, which raises the value of people who can decide what to build, how to sequence it, and how to frame it coherently. It is a useful articulation of how AI can shift status and bottlenecks inside product teams.
-
Tweet
Mar 6, 2026
5% of merged PRs now come from background agents
Concrete adoption metric: background agents now account for 5% of merged pull requests. The post also points to the surrounding workflow, including Slack as the coordination layer and local dev environments with Claude Code.
-
Blog post
Mar 3, 2026
Harness engineering
The post argues that the leverage point is often the harness around the model: tools, instructions, verification loops, and environment design. Useful framing for teams that are focusing too narrowly on model selection alone.
-
Blog post
Feb 19, 2026
Stripe’s Minions, Part 2: blueprints, rules, and MCP at scale
This follow-up focuses on the operating model behind the agents: blueprints, scoped rule files, shared MCP infrastructure, and bounded CI loops. It is a useful example of the harness needed to make coding agents repeatable at large-company scale.
-
Blog post
Feb 9, 2026
Minions: Stripe’s one-shot, end-to-end coding agents
Stripe says Minions already generate more than a thousand merged pull requests per week. The notable pattern is end-to-end agent implementation paired with normal human review before merge.
Levie sketches the supporting stack he expects around large-scale agents: sandboxed execution, tool access, memory, wallets, identity, and governance. It is useful as a map of the infrastructure and workflow changes companies may need as agents move from demos into real operating environments.