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AI models produce matching decompilation but still need human cleanup

decomp.dev 4 min read Editor score 7/10

The decomp.dev team says newer models can use its tools with little guidance and produce decent results in clean, documented codebases, but still need human fixes for errors and questionable shortcuts. It offers a grounded view of where model-driven coding work still needs review.

What

- decomp.dev centralized matching-decompilation progress and supported a community of contributors.

How

- Recent models can test source variants, cross-reference symbols, and sustain long tasks, but still need human cleanup and code review.

Why it matters

- AI can accelerate code-matching work, while human guidance and review remain important for reliable engineering contributions.

Read on decomp.dev → Lobsters · 14 comments

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