10 stories tagged with #llm, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.
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Everyone is building LLM routers, we deprecated ours
We don't believe in model routing anymore. For most use cases, sticking to a single battle-tested model is the best thing you can do.…
Ask HN: What are you using for LLM inference in production?
AdaMAST: Adaptive Failure Taxonomies for Improving LLM Agents
Convert an agent system's traces into a compact taxonomy of named failure codes on three fixed axes, induced automatically and validated before anything trusts them.…
Instrument an LLM Agent with OpenTelemetry · TripleCloud Blog
OpenTelemetry can trace an LLM agent the same way it traces the rest of your stack. A hands-on guide to the GenAI semantic conventions: zero-code auto-instrumentation, manual agent…
Why prompt injection is still possible in LLM applications
How a chat conversation actually reaches the model, and why it can still confuse untrusted content with trusted instructions.…
Sequence Is Not Structure: Getting Lost in Long LLM Conversations
Long LLM conversations preserve sequence, not structure. I want a way to see where ideas branch, drift, and remain unfinished.…
Engy – Verified LLM Inference
OpenAI-compatible inference for frontier open-source LLMs, with a cryptographic proof of correct inference on every response.…
KaaS – Knowledge as a Service: an out-of-the-box LLM wiki compiler
Knowledge as a Service: an out-of-the-box LLM wiki compiler. - bybit-exchange/kaas…
The Groundhog Trap – Multi-model consensus and AI output failover framework
The Groundhog Trap by Ricky Rojas: an open AI governance framework using multi-model consensus, adversarial validation, semantic routing, and LLM-as-a-Judge techniques for trustwor…
How Profitable Is LLM Inference? Doing the Math on Kimi K3
A look at LLM inference economics (batch size, GPU count, and the Pareto frontier that sets token prices) applied to Kimi K3 with back-of-the-envelope math.…