If 2023 was the year every enterprise ran its first LLM pilot, 2024 is the year those pilots get their first real jobs. The move from chat-with-your-document to do-a-multi-step-task is the largest shift we’ve seen in how AI is deployed inside a business since RAG, and it’s happening faster than most roadmaps expected.
The word “agent” is doing a lot of work in the industry right now — it covers everything from a scripted tool-calling loop to an experimental self-directing system. For enterprise purposes, the useful definition is narrower: an agent is a language model that can decide which tool to call next, execute it, observe the result, and repeat until the task is done or it gives up and asks for help.
Five decisions every team deploying agents should make this quarter:
- Pick the shape of your agent before you pick a framework. A single-agent tool-user is a different system from a multi-agent team with a router. Don’t adopt LangGraph, CrewAI or a custom loop before you can sketch the control flow on a whiteboard in under two minutes.
- Budget for failure modes that don’t exist with chat. Agents can loop, they can call the wrong tool, they can burn tokens for twenty minutes producing nothing. Rate limits, iteration caps, and a hard wall-clock timeout are table stakes — not polish.
- Instrument the trace, not the turn. A single agent run can produce dozens of LLM calls. Your observability needs to group them into a trace with a task ID, cost, tool-call graph and final verdict. Without this, debugging a failed run is a bisection problem no engineer wants to own.
- Give the agent fewer tools, not more. The most common cause of agent failure in the last six months has been tool-choice confusion — giving the model forty functions to choose from when six would do. Smaller tool menus produce more reliable agents. Always.
- Human-in-the-loop is a feature, not a fallback. The most successful agent deployments we’ve seen this quarter have an explicit ask-for-confirmation step before anything irreversible. Write, create, send, charge — these are the verbs that should always go through a human until you’ve earned the right to automate them.
The interesting part of this year won’t be the agent demos on Twitter. It will be the quiet announcements from operations teams about the first repetitive back-office task they stopped doing themselves. If you’re not running at least one contained agent pilot by the end of Q2, you’re going to be buying someone else’s agent story in 2025 instead of telling your own.
