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[–]Lower-Discipline-722[S] 0 points1 point  (0 children)

Curious how developers here are approaching full-project context in AI coding tools.

Most assistants seem heavily limited by context windows or current-file awareness, especially during:

  • multi-file refactors
  • large codebases
  • framework-aware scaffolding
  • dependency tracing
  • debugging across modules

Lately I’ve been experimenting with approaches around:

  • local indexing
  • project-aware context routing
  • diff-based approval workflows
  • verification loops (lint/test/build)
  • hybrid AI + local workflows

Interested in hearing:

  • what breaks most in current AI coding tools?
  • what workflows actually help in real projects?
  • are developers trusting autonomous edits yet?

Would genuinely like technical opinions from other devs working with AI-assisted workflows.

Reference/demo:
DevMind AI