laxmena

Industry is increasingly moving towards complex, autonomous agentic loops and feedback chains. They obviously comes with significant latency, non-determinism, low-accuracy and cost.

I'm interested in hearing from engineers who have moved in the opposite direction.

At what point in your product lifecycle did you decide that agentic approach was wrong tool for the job?

What was the specific failure mode (reliability, cost, latency, maintainability) pushed you to replace agentic loop with more deterministic system/pipeline?

As someone tinkering with AI agents daily, I’ve seen massive shifts since mid-2025.

What’s the single AI tool, feature, or technique that gave you the biggest productivity leap in the last year? (Cursor Composer? Claude 4.5 projects? A custom RAG setup? Vibe-coding with o1?)