Agentic AI consulting

AI agents are the first kind of AI that acts instead of answering: they take a goal, plan the steps and work across your systems. That is where the value is, and also where a mistake stops being a wrong sentence and becomes a wrong transaction.

I help companies put agents to work without losing control of them. I wrote Implementing AI Agents in Your Company, a free book for the managers who have to make this pay, and I write regularly about what happens when agents meet production: how much autonomy to give them, how to limit what they can touch, and how to know afterwards what they did.

What we work through

• Where an agent belongs. Which workflows have a business case and a result you can check, and which are better left to a person or a simpler tool.
• Build, buy or wait. Agent platforms, model choice and what the running cost looks like at production volume.
• Permissions and blast radius. What each agent may read, write and spend, and what enforces that limit.
• A record of what happened. Logs and reviews good enough to explain an agent’s action to a customer, an auditor or a regulator.
• A pilot that tells the truth. One workflow, a baseline, a named owner, and an agreed test for going to production.
• People. Who supervises the agent, what they need to learn, and how the team’s work changes.

How to start

Bring one workflow you are considering to an advisory hour. You leave with a view on whether an agent fits, what it would take, and the smallest pilot that would prove it. If you need continuing senior oversight across several AI initiatives, that is the fractional Head of AI arrangement.

For the full argument on governing agents, read the guide to deploying AI agents safely.

Common questions

What is agentic AI consulting?

Advice on putting AI agents to work: software that takes a goal, plans steps and acts across your systems, where a chatbot only answers. The consulting covers which workflows suit an agent, whether to build or buy, what the agent may touch, and how to prove the result before scaling.

How do you implement AI agents in a business?

Start with one workflow where mistakes are cheap to catch and cheap to undo. Write down what the agent may do and what needs a person’s approval, run a pilot against a baseline with a named owner, keep a record of every action, and widen the scope only as the evidence comes in. My free book, Implementing AI Agents in Your Company, walks through each step.

Should we build AI agents or buy an agent platform?

Most companies should buy the agent loop and keep what compounds: their own corrections, review rules and data. Building makes sense when the workflow is your differentiator and you have the engineers to maintain it.

Which business workflows are good first candidates for AI agents?

Work with clear inputs, a result that is quick to check, and a low cost of error: support triage, document processing, reconciliation, internal research and reporting. Avoid starting with long multi-step workflows, because small error rates compound across steps.

Do you build the agents as well?

I build small prototypes and proofs of concept to answer the key questions. For a full production build I help you choose a vendor or team and review their work, so the advice stays independent of who builds it.

Talk it through

Book an AI advisory hour or write to hitesh@256tec.com.