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What it takes to put an AI agent into production
An agent demo is a weekend. An agent with real tool access, running unattended against your systems, is a distributed system with a non-deterministic component in the middle of it.
Five questions to ask before any AI project
Most of what gets pitched as an AI project is an integration problem, a process problem or a data problem wearing a costume. Here is how I tell the difference before anybody writes code.
Nobody’s RAG system fails at the model. It fails at retrieval.
Wiring up retrieval-augmented generation takes an afternoon. Making it return good answers is the actual project — and almost all of that work happens before the model is involved.
The offer
A free AI & automation opportunity review.
You do not need another generic AI strategy document. I look at how your business currently works and come back with practical opportunities where AI, automation, integration or better architecture would reduce manual work and create measurable value — including the ones I would tell you not to bother with.
Two minutes to request. The written map is yours whether or not you hire me, and there is no follow-up sequence.
- 01UnderstandYour current workflow, tools, systems and where things get stuck.
- 02IdentifyRepetitive work, manual handoffs, disconnected systems, AI-shaped problems.
- 03PrioritiseSeparating interesting ideas from the things that would move the business.
- 04RecommendPractical opportunities ranked by impact, complexity and likely return.
- 05ImplementIf you want it built, I design and build it. If not, the map is still yours.