How we
work together.
Most AI tools impress in a demo, then stall the moment real work hits them. I build the opposite: systems that get more useful with age, because they're grounded in evidence, shaped around how you actually work, and built to keep paying back long after the pilot.
Everything I do runs on the same engines I build in the open, webdevOS and cofounderOS. The four practices below are how I put that discipline to work for you.
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Find the Value
Where do I start? Which tools actually pay back?
You've tried a few tools and the impact hasn't matched the hype. The real question isn't which tool. It's where, in your actual business, intelligence earns its keep.
I start with evidence, not enthusiasm. In a one-hour call, the first 30 minutes free, I look at how your work flows today and benchmark what you're running against what good looks like, mapped to the four stages of adoption.
You come away with an honest read of where you sit, a recommended stage to aim for next with the reasons why, and practical take-homes you can act on straight away, instead of another pilot that plateaus at the demo.
- D.01An audit of where you sit today, mapped against the four stages of AI adoption.
- D.02An honest read on what you're running versus what good looks like, and where your work leaks time.
- D.03A recommended stage to aim for next, with the reasons why.
- D.04Practical take-homes you can act on right away: clear next steps plus pointers for self-research.
I've already tried some AI tools and they didn't help much. Is this different?
That's exactly the situation this is for. Tools that underdeliver are usually pointed at the wrong problem, not the wrong vendor. I start by auditing how your work actually flows and benchmarking what you're running, so the next step is grounded in evidence about where value lives in your business rather than in tool enthusiasm.
Where do I start? I don't know which tools actually pay back.
You start with a diagnosis, not a tool purchase. I look at how work flows today, compare it against best-practice reference points, and surface the small set of places where intelligence earns its keep. The output is a prioritised opportunity map, so you can see where to invest before you commit to any particular tool.
Will my team be able to act on this, or is it just a report?
It comes with practical enablement, not just a document. The people doing the work need to understand what changed and why, so I pair the diagnosis with hands-on enablement aimed at the team, leaving them equipped to go get real impact themselves.
Not sure which fits?
The four practices map to the four stages of adoption. Most people start with Find the Value and grow from there.