ARCHITECTURE Signal 142
Author uses Domain-Driven Design to split work into strategic human decisions and tactical AI implementation
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Illustration only Photo by Sven Mieke on Unsplash
An author proposes a workflow where engineers handle strategic decisions and Domain-Driven Design while AI agents execute tactical implementation tasks based on written skills.
LLMs struggle with legacy codebases because they guess incorrectly when systems lack a shared language. By using Domain-Driven Design to establish that language, engineers can offload the now-cheap tactical implementation to AI agents while focusing their own effort on strategic design decisions.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
LLMs fail on legacy code because they guess wrong in systems with missing meaning and no shared language.
The cost of typing out code has collapsed, making tactical implementation cheap and leaving deciding as the primary human expense.
Domain-Driven Design provides the shared language necessary for humans to make strategic decisions that AI skills and sub-agents can then tactically implement.
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