Delivery · Data · AI practice
For owner-operated companies that already know how to be successful. I build the system, then leave the method behind it. What you get back is your attention — for the work only you can do. Everything else moves so the growth feels smooth. You would never guess how fast you’re growing.
Engagements start with a fixed-fee, read-only audit. You keep the findings either way.
I spent a career inside the old model: multi-person teams, long timelines, and enterprise price tags. I know what that talent stack costs because I led it.
The same sophistication is now available to owner-operated companies through one person. You get a single point of contact, a shared definition of success, frequent showcases of finished work, and delivery that does not require you to manage a cast of characters.
The recent solo build is proof the compressed model works — weeks, not years; a fraction of the old cost. I use the same method on my own practice every day. Concierge is live; the lessons are real.
What I do
Find the sentence that sounds like your business. Each one opens.
Model the real domain. Build the system that encodes and enforces it. Leave manuals for users and maintainers.
Commercial kitchen — menu cycle, recipes, prep, purchasing — empty repo to daily production in four months. Solo.
One relationship. You keep the key decisions. I handle the rest. The work is Concierge. The team behind Concierge is how I deliver it, not a second product.
Same method on my own practice. Concierge is live. Case Study Zero.
Turn ad-hoc AI use into a clear practice — what gets used, what gets reviewed, what happens when it’s wrong. Leave the method so capability does not leave with the consultant. Single point of contact.
Concierge / Case Study Zero.
Nine financial accounts, 57 statements, reconciled and rendered as one page with payment calendar and payoff scenarios — including what the reconciliation missed.
How it starts
Every engagement starts the same way, because that's how I do the work itself — not because it makes a tidier proposal.
Fixed fee. Read-only. One to two weeks. A written findings report and a standing dashboard — both yours to keep, whatever happens next.
The fix, scoped from what the audit actually found rather than from a guess. Fixed price wherever the audit made that honest.
The framework adapted to your repository and your team. Review gates, templates, documentation rules, the lessons log.
Standing second opinion. Monthly review, escalation, and the argument you need before a decision rather than after.
I don’t start by changing anything. I start by listening and measuring. The audit ships as a finished piece of work that you can keep.
I always start with the same leading question.
I carried this practice with me from Thoughtworks because it gets further in 10 minutes than a discovery deck gets in a week.
“Thinking of this aspect of your business on a scale of 1 to 10, where would you put it? Now talk to me about the gap between that number and 10.”
Then I go after the most obvious pain point — not the most architecturally elegant one. The elegant problem can wait. The obvious one is the one that produces felt relief, and relief is what buys the trust to do the rest.
Case studies
Messages and commitments were landing in different places. Nothing was broken, but nothing was unified either. The cost was attention: scanning, deciding what mattered, and still missing things that should have been simple.
Concierge, as I run it: one place that holds the day. A ranked morning surface, plus specialists as needed, all trained on one voice and one set of rules. I still decide. Portable playbook. Propose-only for anything irreversible.
One surface for what actually needs me. The rest is filtered, proposed, or held. Concierge is live; the lessons log is real.
The method is the product. Stand Concierge up on another practice the same way: sit in their mess, ship on their tools, stay through week two.
Concierge · Case Study ZeroA subset of recipes had quietly wrong ingredient amounts. Scaled to the day’s headcount they produced too little food, or too much. The cause was an inconsistency inherited from an external system — invisible from inside the data.
A lot of effort went into a statistical model of what “healthy” data looks like. It was wrong, and wrong in a way the dataset itself could never reveal — it had been calibrated on its own symptom. One read-only harvest of an outside system made the problem tractable in a way no better heuristic would have.
Repaired data verified on production after deploy.
When correcting data, the first question is what can I check this against? — not what pattern can I infer? An external anchor beats a better heuristic.
Flagship~2,000 recipes and 15,794 ingredient rows maintained by many hands with no enforced conventions. Duplicate identities differing only in case or word order. 48 distinct unit values. 3,487 rows recording dry goods in a liquid measure — the fossil residue of an old mechanical conversion. Roughly 170 free-text values in a field that should have held a closed vocabulary.
Audit first, always: ship a read-only report of the true scope, review the real numbers, then design the fix as a separate step. Pair every cleanup with a rule that stops the drift returning — closed vocabularies, a gate on ingredient auto-creation, validation on the type dropdown. The goal wasn’t just “clean the data once.” It was to make the database outlive any single contributor.
Spend the domain expert's time on rulings, not archaeology — they should review a structured proposal, not answer questions for three weeks. And every cleanup needs a gate, or you'll do it twice.
Data QualityOne honest question: what actually happens when I click merge? The real answer was worse than the felt answer. That inventory is worth running on any project you've been shipping to for a while.
Advisory beats blocking when there's nobody to escalate to. A gate whose failure mode is “the one person who can override it, overrides it” isn't a gate. Separate the second-opinion value from the veto power — you usually only need the former. The repository contains a documented case of a bot finding being knowingly declined, with the reasoning written down.
Solo teams and small teams have to deliberately construct what a second engineer would have provided. It's cheap to build once you name what's missing. And a safeguard that fights the workflow gets deleted — all three of these are still running, hundreds of pull requests later.
For engineering leadersWho you'd be working with
Thoughtworks, as Lead Consultant and Delivery Principal. Enterprise consulting across technology, retail, automotive, airline, financial services, healthcare, and digital platforms, in several countries and at every level of an organization. Since then, fractional COO work — which means being accountable for whether the operation actually runs, not just whether the software shipped.
Over four months, I shipped 45,000 lines of production Python solo into daily operational use and captured the method while I did it.
The same method runs my own practice. Concierge is the system I use daily — Case Study Zero. When I say I leave the method behind, that is the method.
The enterprise years were the apprenticeship. What they produced were the tools I still use: systems and design thinking, requirements gathering, change management, value-stream mapping, continuous improvement loops. The tools stayed. What changed is that the client is now a small business owner rather than an enterprise.
A short call first, to work out whether there's something here worth measuring. If there isn't, I'll say so — that's a cheaper answer for both of us.
Colton Weeks Consulting · San Francisco Bay Area
A 30-minute call. No deck. We work out whether an audit is the right first step, and if it isn't I'll say so.