Plain-English explainers for AI agent concepts: tool use, memory, orchestration, evaluation, safety, refusal policy, stopping conditions, and the rest of the agent stack. Written for non-researchers who need to make build vs buy calls.
The pitch for a meal-planning agent is simple: 30 minutes of weekly menu work, gone. The trick is that meal planning is bound by hard physical constraints (allergens, what is in the pantry) and soft preferences…
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The first time an agent does the wrong thing in production is the day a trust model becomes a budget line. Every team eventually writes one. The question is whether you write it before the incident or after. This…
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Safety for AI agents is structurally different from safety for chatbots. A chatbot that says something inappropriate creates a screenshot. An agent that does something inappropriate creates an incident: an email…
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The first time someone writes an agent prompt the way they write an LLM prompt, the agent breaks within the first hour of running. Not because the prompt is wrong in a literal sense; it is just shaped for the wrong…
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Eight months into 2026 and the agent market has visibly matured in three ways the 2025 forecasts mostly missed: pricing structures are converging, buyer procurement bars have hardened, and the marketing language of…
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"Why did the agent fail?" is the question every operator asks the first time an agent misses. The honest answer is almost always one of eight things, and the eight things are different enough that lumping them…
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"Is the agent any good?" is the question every buyer asks and almost no buyer can answer with a number. The shortage of good answers is not because the metrics are unknown; it is because most vendors publish one or…
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An agent that runs ten thousand times a day is a different business from one that runs ten times. Pricing pages do not reflect this and most founders learn it after they ship. This post walks through the actual…
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The deployment-model question shows up earlier than buyers expect. The first time someone asks "where does the agent actually run?" is usually thirty seconds into a security review, and the answer determines half the…
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The cost-model question is where AI agent platforms separate from one another more than the technology does. Two platforms can run the same model on the same task at roughly the same reliability and present radically…
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The benchmark landscape for AI agents in 2026 is busier than the buyer landscape can absorb. Five benchmarks dominate the conversation: GAIA, SWE-bench, AgentBench, BFCL, and ToolBench. Each measures something…
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The Monday morning KPI summary is the report that should be automated and almost never is. The data exists. The query exists. The template exists. What is missing is the half-hour every Monday that somebody spends…
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Tool use is what separates a chatbot from an agent. A chatbot talks about sending the email; an agent calls the email-send tool and watches for the result. The mechanism under tool use is function calling,…
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Whether AI agents "reason" is a debate that often misses the practical point. The practical point is that different reasoning patterns produce different reliability characteristics on different tasks.…
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Orchestration is the runtime layer that coordinates multi-step agent execution. The LLM thinks; the orchestration decides which step runs next, retries when something fails, evaluates whether the goal is met, and…
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The discourse around AI agents in 2026 carries a lot of myths. Some come from vendor marketing; some come from social-media hot takes; a few are honest misunderstandings of fast-moving terminology. This post takes…
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AI agent memory is not one thing. It is three layers, each handling a different timescale and a different question. Short-term memory holds what is happening right now. Long-term memory holds what the agent might…
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Procurement conversations about AI agents fail when buyer and vendor use the same words to mean different things. This glossary defines 28 terms that show up in agent procurement, organised by category. Each entry…
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