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Service · Advisory and build
Agentic AI consulting for teams past the demo
Most agentic AI pilots work. The trouble starts when real users, real data and a real invoice arrive. I help teams close that gap, either as a second opinion before you scale or as hands-on build work.
An agentic AI pilot is easy to make impressive and hard to make dependable. The demo runs on a clean path with a friendly question and a person watching. Production is a different system: unfamiliar phrasing, missing data, a tool that times out, a user who asks for something the agent should refuse, and a finance team that wants to know what each resolved case cost.
The work is closing that distance. Sometimes that means telling you the architecture is fine and the evaluation set is what is broken. Sometimes it means the agent should have less autonomy than it has, on the tasks that matter. Sometimes it means building the thing properly, with the production concerns designed in from the first commit rather than bolted on after the first incident.
I do not sell a framework, a platform or a preferred vendor. What I bring is twenty years of enterprise systems and fourteen shipping AI inside Fortune 100 organizations, which mostly shows up as knowing which risks are real and which ones a room is worrying about because they are easier to discuss.
This is for you if
- → You have an agentic AI prototype or pilot that works, and a decision to make about scaling it.
- → Your team can build, but nobody has taken an agent through a security review, a cost ceiling and an on-call rotation before.
- → Leadership is asking for a number and you do not yet have one you would defend.
- → You want a senior engineer who will write code and own the outcome, not a deck.
Where I am not the right fit
- × You want a large team on site for six months. I work in small, tightly scoped engagements, and I will point you elsewhere for staffing.
- × You want someone to be your permanent AI person. Every engagement is designed to end with your engineers owning the system.
- × You want a vendor selection blessed rather than examined. If the shortlist is wrong I will say so.
- × You need the agent live in two weeks regardless of whether it should be. I will not sign off on a gate I do not believe.
- 01
Get to the real question
A short intake before anything else, so the first session goes deep rather than wide. Usually the stated problem ("the agent is not accurate enough") turns out to be a different problem, and finding that early is most of the value.
- 02
Look at the system, not the slides
Architecture, prompts, retrieval, tool boundaries, the eval set, the traces, the cost per unit of work. The eval set gets read by hand, because a score cannot tell you that your answer key is wrong.
- 03
Name the gates honestly
Which checks are genuinely blocking, which are compensating controls, and which ones the team has quietly been treating as optional. Scored on what is true, not graded on a curve.
- 04
Write it down, then build if you want
A short memo you can forward, then a readout with the engineers who will own the work. If you want the build done too, that is scoped separately, in writing, with a fixed deliverable.
- → A readiness picture across roughly ten dimensions: architecture, retrieval, evaluation, autonomy, security, observability, cost, reliability, ownership, and the exit path.
- → The top risks, in the order they will actually hurt you, with the person and the artifact that answers each one.
- → Quick wins that are worth doing this sprint, separated from the structural work that is not.
- → A three to five page memo written to be forwarded to someone who was not in the room.
- → Knowledge transfer to your engineers throughout, so nothing here depends on me afterwards.
Why Most Agentic AI Demos Fail in Production
The four gates a demo has never had to pass, and why each one fails quietly.
Read it → ArticleThe AI Agent Production Readiness Checklist
Twelve checks, four of them hard blocks. This is close to what a review actually walks through.
Read it → ArticleWhat to Automate First
If you are choosing where to point an agent, start here rather than with the technology.
Read it →Frequently asked
Quick answers
- What does an agentic AI consultant actually do?
- Two things, usually in sequence. First, look at a system that already exists and say honestly whether it is ready to carry real users, real data and real cost, and what has to change before it can. Second, build the parts the team cannot get to, with evaluation, cost ceilings, security and observability designed in rather than added later. The work is engineering judgment applied to a specific system, not a methodology applied to a category.
- How is this different from hiring a large consulting firm?
- Scale and who does the work. A large firm brings a team, a method and a longer engagement, which is the right answer when the problem is organizational. Here you get one senior engineer, a tightly scoped piece of work with a fixed deliverable, and code rather than recommendations. If your problem genuinely needs thirty people, a large firm is the better call and I will say so.
- Do you work with a specific framework or cloud?
- No. I have shipped on the major clouds and worked across the common agent frameworks, and the choice is usually less load-bearing than teams expect. Most of the difficulty in an agentic system lives in evaluation, tool boundaries, retrieval quality and cost, none of which a framework decides for you. If you have already committed to a stack, that is a constraint to design around, not something to relitigate.
- How quickly can we start?
- The Readiness Review is a 90-minute working session plus a memo and a readout, and it usually lands within a couple of weeks of the intake form coming back. Build work is scoped after that, because scoping it before anyone has looked at the system produces a number that is wrong. Book a 30-minute call and we will work out which of the two you actually need.
Start a conversation
Tell me what you are building, and what is worrying you.
A 30-minute call, no charge. If there is a fit we will scope it tightly in writing. If there is not, I will say so and point you somewhere more useful.