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        <p class="eyebrow"><span class="status-dot"></span> Field notes</p>
        <h1>Lessons from work that had to hold up.</h1>
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          Practical notes on agent evaluation, human review, and the decisions that sit between a
          promising model and useful software.
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            <div class="blog-entry__meta">
              <time datetime="2026-09-03">September 3, 2026</time>
              <span>Agent evaluation</span>
              <span>6 minute read</span>
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            <h2><a href="./response-only-evals-missed-176-faults.html">A response-only eval missed 176 of 263 broken agent runs</a></h2>
            <p>A reproducible comparison of response-only, trace-only, and trace-plus-outcome evaluators against the same 263 controlled agent failures.</p>
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              <time datetime="2026-08-05">August 5, 2026</time>
              <span>Human review</span>
              <span>5 minute read</span>
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            <h2><a href="./human-review-ai-agents.html">Human review stops working when everything needs review.</a></h2>
            <p>
              Every review consumes a person's attention. A practical way to decide which AI
              actions should stop, what the reviewer needs to see, and where the software's
              authority ends.
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              <time datetime="2026-08-03">August 3, 2026</time>
              <span>Agent evaluation</span>
              <span>6 minute read</span>
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            <h2><a href="./agent-eval-mutation-testing.html">Your agent eval passed. Would it catch a broken tool call?</a></h2>
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              Plant one known failure, rerun the same evals, and see whether the score changes. A
              practical introduction to mutation testing for agent tool use.
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