Why Fewer Tools Make a Better AI AgentGive an AI agent ten tools and you usually get worse output, not more capability. Every tool you add is another place the model can pick wrong, pass bad arguments, or silently do the wrong thing whileSep 1 · 6 min readpykero.hashnode.dev
Why Your AI Feature Needs Deterministic Guardrails, Not a Smarter ModelLLMs are probabilistic, so trying to make one output consistently is a losing battle. The fix isn't a bigger model or a longer prompt: it's a deterministic layer of rules sitting between the model andAug 31 · 6 min readpykero.hashnode.dev
How to Detect an AI Agent Scheduled Run That Silently FailedA scheduled AI agent that never fires looks, from the outside, exactly like one that ran and did nothing wrong. Nobody gets an error email. Nothing shows up in your exception tracker. The only signal Aug 27 · 6 min readpykero.hashnode.dev
How to Calculate ROI on an AI Agent Before You Build ItCalculate ROI by comparing what the manual process actually costs today (fully-loaded labor, error correction, missed volume) against the one-time build cost plus ongoing per-run inference cost, then Aug 25 · 5 min readpykero.hashnode.dev
LLM Router vs Direct API: What Founders Should WeighUse an LLM router when you're still testing which model fits your product, need multi-model flexibility, or want automatic failover without building it yourself. Go direct to the provider API once you11DAug 23 · 6 min readpykero.hashnode.dev
