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| -rw-r--r-- | 2026/talks/hutch.md | 12 |
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diff --git a/2026/talks/hutch.md b/2026/talks/hutch.md index 42de6f4a..aa8b1e3a 100644 --- a/2026/talks/hutch.md +++ b/2026/talks/hutch.md @@ -37,11 +37,13 @@ Imagine you've just finished implementing a function. Before committing, you ask You can now accept, reject, or investigate each suggestion without leaving the Magit workflow. If the suggestions are useful, hutch can turn them into patches and apply; if it's nonsense, you dismiss it right there. None of it leaves your safe space. The talk walks through how it works and when it doesn't: - • tour of the workflow: how to use hutch, when to use hutch, how to approve and reject things - • patches over comments: hutch biasing outputs towards actionable items, rather than just prose - • tools: guardrails, every agent loop earning its keep, gptel's state-machine - • evals: how does it stack up against other external tooling on recognized benchmarks - • dead-on-arrival: where it fails and why this is only useful if you work in a specific niche way + +- tour of the workflow: how to use hutch, when to use hutch, how to approve and reject things +- patches over comments: hutch biasing outputs towards actionable items, rather than just prose +- tools: guardrails, every agent loop earning its keep, gptel's state-machine +- evals: how does it stack up against other external tooling on recognized benchmarks +- dead-on-arrival: where it fails and why this is only useful if you work in a specific niche way + This is a Magit and review-workflow talk that happens to involve an LLM, it doesn't purport any arguments about whether you should or shouldn't use AI with emacs. **Note:** The hutch package is available on MELPA <https://melpa.org/#/hutch>. |