Aerial view of downtown San Francisco at golden hour, looking across the financial district toward the bay and the Bay Bridge

AI strategy & deployment · fixed scope, priced up front

AI that gets past the demo.

Side B is an AI practice for small businesses, startups, and independent professionals. Strategy, deployment, and systems that actually run — designed and built by the same person.

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Fixed scope and a fixed fee, agreed in writing before work begins
Designed and built by one person — no handoff, no junior team
You own everything: the code, the prompts, the documentation

Sound familiar?

You don't have an AI problem. You have a where-do-I-even-start problem.

These are the conversations I have most often. If one of them is basically a transcript of your last month, that's the place to begin.

Everyone on the team uses ChatGPT a little differently, and nobody can tell you what's actually working.
You've sat through three AI demos that looked incredible and none of them survived contact with your real data.
There's a task eating six hours a week that obviously should not be done by a human anymore.
You're paying for AI seats and tools, and you cannot tell whether they've earned it back.
A competitor is advertising AI and you can't tell if it's real or if it's marketing.
You know AI belongs somewhere in your product, but not where it actually earns its place.
A vendor is pitching you an AI platform and there's nobody in the room who can tell if the pitch is true.
You started building something with AI, it works about 70% of the time, and it's been stuck there for a month.

The gap I work in

The same research says both of these things.

66%

Average productivity gain across three controlled studies of business users given generative AI for real work.

Nielsen Norman Group, 2023 — nngroup.com

95%

Of enterprise generative AI pilots produce no measurable return, against $30–40 billion spent. MIT calls the cause organizational, not technical.

MIT NANDA, State of AI in Business, 2025 — report PDF

The difference between those two numbers isn't the model. It's whether somebody designed the work around it. That's the entire job.

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Where most people start

Four ways to work together.

Every engagement is scoped and priced in writing before anything starts, so you know the cost and the finish line before you commit.

AI Readiness Sprint

Two weeks to answer the only question that matters: where does AI actually pay off in this business, and what should you do first? I look at how the work really gets done, not the org chart, and come back with a ranked plan.

Opportunity map, ranked by value against effort
A recommended first build, scoped and costed
Tool and model recommendations with real monthly run costs
Risk, privacy, and acceptable-use notes
A 90-day roadmap you could hand to someone else

Best for Anyone who keeps starting AI conversations that don't end in a decision.

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Build — agents & automations

I design and ship the thing. A working agent or automated workflow, running against your real data, in your stack. This is the part most AI consultants hand to somebody else. I don't have a somebody else.

A working system, deployed and running on a schedule or on demand
Evaluation set, so you can see when it's right and when it isn't
Monitoring, logging, and a sane failure mode
Plain-English documentation and a live handoff session
All source, prompts, and configuration, owned by you

Best for A specific, repetitive, expensive process you already know is worth fixing.

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Team enablement

Half your AI value is locked up in people not knowing what's possible. A working session built on your actual workflows — your documents, your emails, your process — not a generic prompting webinar.

Half-day or full-day session, in person or remote
Prompt and workflow patterns built around your real tasks
A written playbook the team keeps and can hand to new hires
A one-page acceptable-use policy sized to your business
Follow-up session 30 days later to fix what didn't stick

Best for Teams already using AI informally, inconsistently, and sometimes unsafely.

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Fractional AI lead

Senior judgment on retainer, for companies that need an AI person but can't justify hiring one. I sit in the decisions, review the vendors, and keep something shipping. Availability is limited on purpose.

Standing working sessions and async access
Vendor and tool evaluations before you sign anything
A build in flight at all times, on the higher tiers
Ongoing enablement as tools and models change
Quarterly written review of spend against value

Best for Companies where AI decisions keep coming up and nobody owns them.

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See the full list of project types →

How it works

No surprises, at either end.

A 30-minute call

We talk about how the work actually gets done and what's costing you the most right now. If AI isn't the answer, I'll say so on this call. No charge, no obligation.

A scoped proposal

You get defined deliverables, a fixed fee, and a timeline in writing before any work starts. You know the cost and the finish line before you commit to anything.

Something that runs

Work is delivered running, documented, and handed over — with the reasoning behind every judgment call written down, so it still makes sense to you six months after I'm gone.

Who I work with

Small enough to move. Big enough that it matters.

The common thread isn't industry, it's size. When there are fewer than a few hundred people, one good AI decision changes the shape of the week. There's also nobody whose whole job is to get it right — which is where I come in.

Small businesses — trades, clinics, shops, and local service companies with real operational drag
Startups — pre-seed through Series A, deciding where AI belongs in the product
Independent professionals — consultants, designers, coaches, and creators who need leverage, not headcount
Professional services firms — law, accounting, real estate, and agencies drowning in document work
Nonprofits — small teams carrying grant reporting, comms, and donor work at once
Operators and investors — anyone who needs a straight read on whether an AI claim is real

Background

A designer who learned to build the thing.

Most AI advice comes from strategists who've never shipped, or engineers who've never sat with a customer. I do both, which is the only reason any of this works.

20 yrs

Product design, most of it at enterprise and consulting scale

Big Four
& Fortune 500

Lead and senior design roles, including enterprise AI products

Strategy,
formally

Business strategy training on top of the design career

Built,
not briefed

The agents behind this practice, I designed and shipped myself

The agents behind this practice are ones I built — a research agent that scores stocks off SEC filings and options flow, and a lead-generation agent that emails a sales team a fresh qualified list every weekday morning. Both are real, both run on their own, and both started as somebody saying "could AI do this?"

More about me and how I work →

Straight talk

What I'll tell you for free.

Sometimes the honest answer is that you don't need AI. You need a cleaner process, one integration, and thirty minutes of thinking about who does what. I've talked people out of builds that would have worked technically and failed in practice, and I'd rather do that on a free call than six weeks in.

I'll also tell you when something is genuinely hard. Models are confidently wrong in ways that are expensive when the output goes straight to a customer. Where that risk is real, I'll say so and design a human check into it rather than pretend it away.

The goal isn't to make you dependent on me. It's to leave you with something that runs and a team that understands it.

Tell me what's costing you the most right now.

Thirty minutes, no charge, no pitch deck. Worst case you leave with a clearer picture of your own operation than you came in with.

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