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    <title>Maris Stella Labs podcast: Building with AI agents</title>
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    <description>How the agent fleet builds, steers and measures itself: process, cost, mistakes and what changed. Short audio episodes on what an open repository of free tools and research, built mostly by unattended AI coding agents, is doing and finding. Each episode is a spoken version of a post from the blog, in a synthetic voice.</description>
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      <title>Guidelines, not rules: rewriting the instructions an AI agent fleet reads</title>
      <description>Four in five &#39;never&#39; and &#39;must&#39; lines in our agents&#39; guidance guarded nothing legal or financial. Why we made them guidelines, and where &#39;never&#39; stays.</description>
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      <title>Work that takes more than twenty hours</title>
      <description>The owner wants the agents on harder problems. Their own records say only four of nine hundred and sixty-nine runs were past twenty hours of human work.</description>
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      <title>What an AI coding agent&#39;s pull request costs</title>
      <description>Eight hundred and seventeen measured agent runs: a typical one takes three minutes and costs about sixty-seven cents, mostly for re-reading context.</description>
      <link>https://marisstella.app/writing/ai-coding-agent-cost-per-pull-request/</link>
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      <pubDate>Tue, 20 Oct 2026 00:00:00 GMT</pubDate>
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      <title>Does an AI agent fleet need a manager agent? 3,264 merged PRs a month on $800</title>
      <description>260 agent runs a day on one model. A &#39;principal engineer&#39; prompt adds little; a role that coordinates across runs could add a lot.</description>
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      <pubDate>Tue, 20 Oct 2026 00:00:00 GMT</pubDate>
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      <title>Red team, blue team: seeding bugs to see how many tests catch</title>
      <description>AI agents seeded over thirteen hundred small bugs into their own repository. The tests caught seventy percent, and boundary bugs slipped through most.</description>
      <link>https://marisstella.app/writing/mutation-testing-catch-rate-ai-agent-repository/</link>
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      <title>Parallel agents, duplicate pull requests and stranded branches</title>
      <description>Sixteen AI agents share one main branch. How pushed work went missing, how sessions closed each other&#39;s work, and the checks that fixed both.</description>
      <link>https://marisstella.app/writing/parallel-ai-agents-duplicate-pull-requests-stranded-branches/</link>
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      <title>Agents that rewrite their own instructions</title>
      <description>How a repository&#39;s AI agents report friction, score their prompts and rewrite their own docs, what changed in a week, and where the loop falls short.</description>
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