Hi Product Hunters! 👋 I’m Senya, and I built TRI·TFM Studio because I was tired of guessing how to write the "perfect prompt" for complex RAG pipelines. Most developers throw vague instructions at an LLM and hope for the best. When it hallucinates, they manually tweak words for hours. We decided to automate this. Under the hood is a 12-step Proposer-Critic-Arbiter (PCA) loop. You paste your garbage prompt, and our engine automatically expands it for detail (D-block), compresses it for token efficiency (S-block), and evaluates it across 5 specific axes (EFMNB). Our mathematical Arbiter forces the model to iterate until it reaches optimal convergence. The result? A highly structured, machine-readable instruction set that drastically reduces LLM hallucinations. Try throwing your most complex, conflicting constraints at it. I’d love to hear your feedback!

TRI/TFM — Prompt Optimization Engine

Deterministic Proposer-Critic-Arbiter loop for AI prompts

Deterministic Proposer-Critic-Arbiter loop for AI prompts