One key to successfully adopting AI into your workflow is knowing to which tasks AI is suited.
โ Tasks which are too complex/big will fail
โ Tasks which are too small don't bring you benefit
Working with a small team and heavily adopting AI to help us ship faster and build our startup, I've learned to triage the tasks I delegate to AI as follows:
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Touches max 3 files
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Clear success criteria
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Single repository
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No gotchas
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Would take up to 3 hours without AI
When I go through our development backlog looking for these sorts of issues, what I find we're left with tends to include
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All minor bugs
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UI tweaks
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Chore tasks (e.g. adding proper error handling)
In summary, what we call "low-surface context" tasks, where the path to resolution is clear and straightforward.
P.s.
๐ค I've built a script that goes through your Linear and triages your tasks according to these criteria, to add an AI-ready label. I shared it with my substack subscribers. If you're interested, comment below and I'll send you the link.
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