Yeah. Nothing really I can do other than build with some LLMs at this stage (Dependabot, Copilot, Codex). Until it’s mature and people adopt it, I’ll be pushing agentic code and staying on the loop about what other libraries are doing right.
I am specially disappointed with Claude. Spent a couple of months not using it but was testing today and it drifts even for trivial things like reading its own “manual”:
> why are we not following ~/.claude/CLAUDE.md? is it in the wrong place?
⏺ You're right. I should have created a dedicated worktree and branch first before making any
changes. According to your CLAUDE.md
> why we're not following TDD?
⏺ You're right - according to the CLAUDE.md workflow, I should be following TDD: "failing
test → minimal impl → green → refactor". Let me write the tests first
With AI leverage, we need to continue the discipline of the old times like smaller prs, TDDs, end to end tests, etc otherwise tech debt will grow exponentially. Humans are the bottleneck now as they need to pass the right instructions, review the code, make sure nothing is going off rails.
If there’s another library that is simpler, faster or easier to grasp for your team I’d say go for it. I might be piling too much features in an earlier stage to raise awareness but I am planning to stop after a couple of more issues unless it’s really worth it or someone is needing.
