Field notes.
Real opinions about what AI is getting right and wrong for operators in 2026, written by us, in our own voice, not a content calendar. Plus the occasional teardown of something Izzy built and what it taught us.
Articles
How to Reduce LLM Evaluation Costs by 90% (Without Losing Quality)
Stop running exhaustive evaluations. Discover the three-tier monitoring strategy that delivers 95% of the insight for just 5% of the cost.
The 95% Accuracy Trap: Why Multi-Step AI Agents Fail
A 95% per-step accuracy means your 10-step AI agent fails 40% of the time. Discover the math behind cascading errors and how to fix agent reliability.
Your RAG System Is Silently Failing: Why Traditional Metrics Miss It
Is your RAG system returning "200 OK" but hallucinating? Learn why traditional metrics fail to catch silent degradation and how to monitor drift in production.
Do You Actually Need LLM Observability? An Honest Review (2026)
An honest, transparent review of LLM observability for 2026. We analyze the ROI, EU AI Act compliance risks, and tell you exactly when you don't need a tool like PromptMetrics.
LLM Hallucination Detection: 2026 Comparison of Accuracy, Latency, and Cost
Stop overpaying for LLM safety. Compare 5 hallucination detection strategies from HaluGate to SLM-as-Judge based on RAGTruth++ and vLLM benchmarks.
The Fatal Flaw in Your AI Strategy: Why Single-Provider Reliance is a Ticking Time Bomb
Relying on OpenAI alone guarantees SLA breaches. Learn to build a defensive multi-provider AI architecture with AI Gateways to achieve 99.99% uptime.
Why Only 5% of AI Projects Reach Production (And the "Evaluation Gap" Behind It)
Industry data shows only 5% of AI projects reach full production. Discover the 5 hidden evaluation gaps from RAG black boxes to compliance risks that stall the rest.
The 5 Most Common Problems with Agentic AI in Production - And How to Solve Them
Gartner predicts 40% of AI agents will fail. Discover the 5 top production pitfalls from hidden cost spirals to compliance risks and the architectural fixes you need.
Defensible AI: The CTO’s Guide to Reliable "LLM-as-a-Judge" Evaluations
Stop relying on "vibe checks." This CTO guide covers how to build reliable LLM-as-a-Judge evaluations, enforce strict rubrics, and block AI regressions in CI/CD.
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