AI Agents for Business: A Practical Guide
What AI agents actually are, where they earn their keep, and how to deploy them without the hype.
An AI agent is software that can take a goal, decide the steps, and act across your tools, not just answer a question. The useful ones are narrow: they handle a defined job — triage a ticket, qualify a lead, read a document — inside guardrails you set.
The gap between a demo and a system that runs unattended is where most agent projects stall. Real inboxes, real edge cases, and the need to escalate rather than guess are what separate a build that holds up from one that quietly corrupts data.
This guide collects our notes on where agents pay off, how we scope them, and the patterns that keep them safe and legible in production.
In this guide
- AI agents vs. chatbots: what actually reduces support loadJune 17, 2026
- What AI agents can't do yet, and how to design around itDecember 12, 2025
- Design agent permissions before you design agent capabilityAugust 15, 2024
- RAG isn't optional anymore: why retrieval beats fine-tuning for most use casesAugust 22, 2023
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