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Debugging used to be straightforward: A service failed, you checked the logs, followed the stack trace, and fixed the bug. The post Debugging the undebuggable: building observability into probabilistic AI systems appeared first on The New Stack.
The problem I am building Spanlens, an open-source LLM observability platform. Every call to OpenAI, Anthropic, or Gemini gets recorded with its model, latency, tokens, cost, and full request and response body. At low traffic on Supabase Postgres this was fine, but I could already see a few signs th
Kin Lane, API industry analyst and co-founder of Naftiko, believes that the bill for AI is coming soon. It’s arriving The post Taming the agentic influx: a blueprint for AI business observability appeared first on The New Stack.
Most AI monitoring tools tell you if your API is up. Visit: https://ai-pou-tracker.vercel.app Type any prompt in the Quick Test box on the left Hit ▶ Send Request Watch your request hit the live AI engine and appear on the dashboard instantly Or call the API directly: curl -X POST https://ai-pou-tra
