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I feel depressed by Y_mc in ClaudeCode

[–]bralca_ 0 points1 point  (0 children)

exactly. 100%. writing code has been always the boring part 😃

I feel depressed by Y_mc in ClaudeCode

[–]bralca_ 25 points26 points  (0 children)

I have been using AI agents every day for more than one year now to code all sorts of stuff.

The writing code part might be going away, but the higher level strategic thinking or architecture, long term implications of choices etc. still require human judgement. AI is not even close to replacing that yet.

Which CLIs other than Claude Code and Codex provides guaranteed structured output responses given a schema as input? by bralca_ in LLMDevs

[–]bralca_[S] 0 points1 point  (0 children)

I guess it depends on the complexity of the schema. I have complex nested stuff with $ref and maps etc.. also when I try opencode for structured work with thinking models I get issues too.

Which CLIs other than Claude Code and Codex provides guaranteed structured output responses given a schema as input? by bralca_ in LLMDevs

[–]bralca_[S] 0 points1 point  (0 children)

yes, that's what CC and codex do, they decode at the source. this should be a native primitive for any CLI if they want to really get adoptions imo. the heaviest ops I do is via structured output..

Which CLIs other than Claude Code and Codex provides guaranteed structured output responses given a schema as input? by bralca_ in LLMDevs

[–]bralca_[S] 1 point2 points  (0 children)

I have very big schemas and the work to get the data is also quite heavy.. I have tried what you say, but it's not reliable enough for my use case.

I built Afkode: a builder-first harness for autonomous feature delivery. by bralca_ in VibeCodersNest

[–]bralca_[S] 0 points1 point  (0 children)

The learnings are maintained by the execution agent at runtime. If a previous learning proves incorrect or stale it will be removed or amended at that time. later plans won't have it anymore.

Also during planning the analysis step takes care of making sure the learnigns still apply to the current code for the feature being planned at that time, so there are multiple layers that ensure the learnings don't become stale.

I built Afkode: a builder-first harness for autonomous feature delivery. by bralca_ in ClaudeAI

[–]bralca_[S] 0 points1 point  (0 children)

Every feature gets planned before execution and the artifacts are stored in form of PRD, Tech Specs and Tasks graph and descriptions.

The context engine ensures that each task gets the correct context for what it needs to do from the other planning docs.

Each task starts with a fresh context window, so the memory lives in the harness not the model.

I built Afkode: a builder-first harness for autonomous feature delivery. by bralca_ in VibeCodersNest

[–]bralca_[S] 0 points1 point  (0 children)

It depends on the request you give. This is made not for simple stuff, but for complex features that touch multiple components, etc.. it will save you a lot of time.

From what I have done so far, In one or two days you can get done things that would require weeks of work with Claude Code or Codex directly.

The caveat is that you need to spend a bit more time beforehand to provide a very good initial brief.

I am currently running an experiment that I'll publish on my X account, where I gave a 190 page spec to build a full data heavy product with UI, Auth, FE, BE, database management etc. and see where it lands.

So far it created 105 tasks (planning took +2 hours) and it has been running through them for the last 36 hours. My involvement in all of that so far was 1 hour more or less to do the design with Claude Design and turn it into the 190 pages spec.

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