Theme

Working with agents

How to run AI coding agents day to day: memory, context, handoffs, many sessions at once.

103 posts by Ben Downey, in two lanes: plain-language stories and the technical build log.

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Everyday lane

Plain-language stories. No jargon. 14 posts.

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A Seven-Hour Session With 390 Prompts and No Record

A day of overlapping AI work showed us why every open task needs a name, a record, and a clear end.

· 4 min read
Giving agents context that stays accurate 2
Agent memory, notes and session handoffs 4
Running agent sessions and browsers unattended 2
Tracking many sessions and catching mistakes 3
Measuring and managing AI cost and quota 1
Show 2 more chapters
Coordinating multiple agents without wasted effort 1
More in this theme 1

Technical lane

The build log: the logs, the code, the fix. 89 posts.

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A 522-Line Markdown File Changed Every Session We Start

A committed AI context file turns repeated codebase explanations and product guardrails into a reviewable project artifact that sessions can be instructed to read first.

· 6 min read
Giving agents context that stays accurate 12
Agent memory, notes and session handoffs 9
Running agent sessions and browsers unattended 11
Tracking many sessions and catching mistakes 9
Coordinating parallel agents on one machine 10
Show 7 more chapters
Shared memory and pipelines across AI tools 9
Measuring and managing AI cost and quota 7
Coordinating multiple agents without wasted effort 6
Orchestrating parallel sessions and trusting their reports 6
Measuring AI work and keeping its plans 3
Pitfalls when agents share files and output 2
More in this theme 5

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