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2026-10-15 · 5 min · Agentic AI, Training
Since mid-July this blog has published twenty pieces on putting agents into production: workflows before autonomy, evals, MCP, context, approvals, guardrails, cost, latency, retrieval, and injection. Mid-October is a goo
Read the article →Agentic AISince mid-July this blog has published twenty pieces on putting agents into production: workflows before autonomy, evals, MCP, context, approvals, guardrails, cost, latency, retrieval, and injection. Mid-October is a goo
Leadership"We'll know it when we see it" is an expensive phrase in any software project. In agent projects it is worse, because agents fail charismatically. A wrong answer delivered fluently looks a lot like a right one, and a dem
Agentic AIAny agent that reads email, tickets, documents, or web pages will eventually read a sentence written to manipulate it. Sometimes it is crude: "ignore your previous instructions." Sometimes it is subtle: a support ticket
Agentic AIObservability has become the default first investment in agent infrastructure, and that is a good thing. LangChain's *State of Agent Engineering* survey found it in place at roughly 89% of responding organizations. Yet i
Agentic AIAccuracy wins the keynote. Latency decides whether people keep using the product. LangChain's *State of Agent Engineering* survey ranks latency as the second most common barrier to putting agents into production, cited b
Agentic AIThe fastest way to make an agent "know" your company is to paste documents into its system prompt. It works beautifully in the demo. Then a policy changes on a Tuesday, and on Wednesday the agent is still confidently quo
TrainingThere is a kind of AI training that produces fluent spectators. Participants leave able to explain what an agent is, name the major frameworks, and sketch an architecture on a whiteboard. Then they sit down to build one
DeliveryA demo is designed to convince. A production readiness review is designed to decide. Agent projects get into trouble when the first is allowed to substitute for the second, because a fluent demo is exceptionally persuasi
Agentic AIAsk an engineer what an agent should optimize and you will hear accuracy. Ask finance and you will hear the monthly invoice. LangChain's *State of Agent Engineering* survey puts quality first and latency second among bar
Agentic AIMost agent teams can tell you what went wrong yesterday. Fewer can stop it from going wrong tomorrow. LangChain's *State of Agent Engineering* survey quantifies the gap: observability is reported by about 89% of responde
Agentic AI"Let's add more agents" has become the new "let's split it into microservices." Sometimes it is exactly right. Often it multiplies failure modes while making each one harder to find.
TrainingHiring for agentic engineering right now is noisy. Titles are unsettled, every résumé lists the same handful of frameworks, and the market moves month to month. Beneath the noise, though, the skills employers ask for hav
Agentic AISecurity teams reviewing an agent project do not need another slide saying AI is risky. They need a mapping from named threats to concrete controls, and a way to verify each control works. The OWASP GenAI Security Projec
Agentic AISomewhere along the way, "human-in-the-loop" became something teams say apologetically, as if needing a person means the AI fell short. In production it is closer to the opposite. Systems that know when to ask are the on
Agentic AIFor two years, the craft people talked about was prompt engineering: the right phrasing, the right examples, the right persona. That craft still matters. But once a model is calling tools across many turns, the words you
Agentic AIThe Model Context Protocol has moved from an interesting standard to an expected skill faster than most platform teams have adjusted. Agentic Ready's June 2026 Agentic AI Jobs Index found MCP in 454 of the 2,072 agentic
Agentic AIRead a stack of agentic engineering job postings and a pattern emerges. The headline skills are protocols, orchestration, and retrieval. Somewhere further down, often in a single line, sits "experience with evaluation."
Agentic AIIf your picture of a production agent is a tireless digital coworker that runs for hours without supervision, the best available data will disappoint you. That disappointment is useful. It is far cheaper to adjust expect
Agentic AIMost AI roadmaps I review skip a step. They go straight from "we should use AI here" to "we should deploy an agent," as if *agent* were a feature you toggle on. It is not a feature. It is a decision about who controls th