LLM Not listening? LLM response keeps changing? - LLMBlitz.io

Hey PH! Zaid here, maker of LLMBlitz 👋 LLMs don’t fail randomly. They fail where they’re uncertain. I built LLMBlitz after building apps at work and spending way too many hours asking: > why did the LLM ignore an instruction > why does it give a different answer every time > why did a one-word change completely change the output Part of the answer shows up in the token probabilities models expose. When a model is uncertain about how to continue, you often see it in the logprobs. Not truth. Not correctness. But a useful signal for where the model is guessing vs confident. LLMBlitz turns that into something you can actually use: > Nondeterminism? See exactly which tokens the model is least confident about—not just that variance exists, but where it shows up > Instruction following? Highlight which instructions were likely followed or missed—and where breakdowns happen using LLM Commander > Prompt comparison? Run Prompt A vs B on the same input and compare model confidence signals, not just outputs > Cost at scale? How much does your prompt cost in 1 run, 10 runs or 100,000 runs, and how can you tweak it for cost? > Prompt creation? Generate, test, and refine prompts tailored to your model and task This won’t magically tell you what’s true. But it will show you where your prompt is weak, unstable, or ambiguous. >> Curious—what’s the most frustrating “why won’t it just do what I said?” moment you’ve had with an LLM? What's your biggest beef with LLM behavior?