5 posts tagged with "Agentic AI"

The vendor API renamed a field. The agent kept running. No error. No alert. Six days later, someone noticed the revenue reports were wrong. The agent had been silently writing null to a field that used to be called something else.

No crash. No exception. Just quiet, compounding damage.

The competitive intelligence pipeline kept failing at step 6. Always step 6. The agent was trying to simultaneously search for news, pull financials, and cross-reference analyst reports - in one context window, with one reasoning thread.

Splitting it into three specialized agents - researcher, analyst, synthesizer - with an orchestrator routing between them, fixed it in two days.

The research agent was impressive - until you realized it was re-fetching the same papers on every run. No memory of what it had already processed. No way to build on previous work. Every session started from zero.

The model wasn't broken. It had no persistent memory layer. Every conversation was the first conversation.

A team demo'd an agent that "connected to the database." The model described what it would do with the data - in detail, confidently. The database call was never wired up.

Tool descriptions are not documentation. They are the interface between language and execution. Get them wrong and the agent calls the wrong tool, at the wrong time, with the wrong arguments.

A team spent three months building an AI assistant for internal engineering docs. Clean RAG pipeline, good answers. Then someone asked it to find the root cause of a latency spike, check the runbooks, and draft a remediation plan. It answered half from training data. Made up the rest. Confidently.

The problem wasn't the model. It was built to answer, not to act.