X discussion: Thorsten Ball's "How I work with Agents" lists 15 habits for coding with AI agents and draws nearly 4K bookmarks

Background and the problem

As coding agents become able to run long tasks on their own, many developers are stuck on how to use them rather than whether they can: over-detailed prompts, endless back-and-forth tweaking, and worry that the codebase will fill up with unmaintainable "slop". At 15:58 UTC on 10-25, developer Thorsten Ball (@thorstenball) turned the advice he usually sends friends in DMs into an X article, "How I work with Agents" (post), labeled as his practice "as of October 2026". It quickly reached X's trending stories, and when we pulled it the bookmark count (3,981) was about twice the like count (1,935).

How it works

The core idea is to let the agent see reality. The author argues that what really stopped hallucinations was tool calls: if the agent cannot see something, it makes it up, so it should run what it builds end to end, read production logs, deploy, watch rollouts, flip feature flags and triage bug reports. He says his team built custom plugins for bug reports, emailing users, system health checks and granting feature flags, and uses Amp as an example of how threads linked to git commits become team memory. He also suggests evaluating whether knowledge files such as AGENTS.md and skills are actually used, by spawning five blind agents split into control and treatment groups.

Benchmarks and measured results

This is an X discussion and a personal account of practice; it has no public benchmark and no reproducible experimental data. The only numbers we can check are engagement: about 1,935 likes, 143 reposts, 92 replies, 3,981 bookmarks and 137K views. The "2x faster compiler" line is a prompt example, and "some threads are 46 messages, some are 3,714" is the author's own description; neither is a benchmark result.

What developers can do now

A few things you can try directly. First, replace "how to do it" with "what result I want" and give a measurable target. Second, instead of trial and error turn by turn, ask the agent to generate 20 variations plus a small page to compare them, and when debugging ask for 4 theories and have it check all of them. Third, write in AGENTS.md what does not count as evidence, and require end-to-end demos or before/after numbers as proof of completion. Fourth, give agents bigger tasks, work asynchronously in batches, and use scheduled checks instead of watching the screen. The author also admits local development gets resource conflicts when several agents run end-to-end tests at once, so remote machines fit better. Whether to adopt it wholesale depends on your team's review standards; views such as no longer caring about duplication or variable names are the most contested.