codeantai.hashnode.devHow Poor Tool Calling Behavior Increases LLM Cost and LatencyYour AI agent just made twelve API calls to answer a question that needed two. Each unnecessary tool call burned tokens, added latency, and pushed your costs higher, all while the user waited. Tool calling is what makes AI agents useful beyond text g...Feb 12·8 min read
codeantai.hashnode.devWhy Overall AI Accuracy Scores Miss Critical Domain-Specific FailuresThat AI code review tool you're evaluating claims 94% accuracy. Impressive, right? But here's what the marketing page won't tell you: that number might mean almost nothing for your actual codebase. Overall accuracy scores average performance across d...Feb 11·8 min read
codeantai.hashnode.devHow to Safely Test New LLMs in Production Using Shadow Traffic and A/B TestingSwapping out an LLM in production feels a lot like changing the engine on a plane mid-flight. One wrong move and your users notice immediately, degraded responses, slower latency, or worse, hallucinations that erode trust. Shadow traffic and A/B test...Feb 10·8 min read
codeantai.hashnode.devHow to Evaluate LLM Performance in Agentic Workflows (2026)LLM agents that plan, reason, and take actions across multi-step workflows break traditional evaluation approaches. A single prompt-response test tells you almost nothing about an agent that chains tool calls, recovers from errors, and adapts its str...Feb 9·8 min read
codeantai.hashnode.devHow Standardized PR Sequence Diagrams Transform Team Alignment in 2026Your PR process probably makes sense to you. But ask three engineers on your team to describe it, and you'll get three different answers, each one missing steps the others consider obvious. That gap between "how I think it works" and "how it actually...Feb 8·9 min read
