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Getting started

Choose your path

Not sure which of these you need? Start from the symptom. Find the row that sounds like your week, and it points you at what’s actually going on and where to start.

#Match the symptom to the fix

Most people arrive describing a symptom, not a solution — “the chatbot said something wrong,” “every release breaks something,” “we’re buried in intake.” Each of those maps to a different capability. Find your row; the last column is a real page you can open right now.

The symptom you haveWhat’s actually going onWhere to start
Our AI chatbot / assistant sometimes says wrong or unsafe thingsYou shipped an LLM feature but have no way to prove it behaves — no golden set, no judge, no gate. Prompt changes ship on vibes.You need an eval layer → AI evaluation & quality, then run the live eval on your own AI
Every release we ship breaks something elseNo regression suite a release manager trusts, or a flaky one everyone ignores. Red stopped meaning anything.You need a regression suite + CI gate → Test automation & CI
We’re buried in manual intake, triage, or routingRepeatable work a well-built automation could run — but it has to be safe, logged, and not invent things.You need workflow automation → AI workflow automation
We need the AI feature built, not just testedThe chatbot, RAG assistant, voice agent, or copilot doesn’t exist yet — you need it built reliably, with the eval seams already in place.You need AI product engineering → AI product engineering
We need the app around the AI — auth, payments, dashboardsThe model is the easy part; the production surface around it (accounts, billing, admin, data viz) is the real work.You need product & platform → Product & platform
Not sure — it feels like several of theseThat’s normal; a shaky AI feature usually needs both building and proving. The cheapest way to find the real bottleneck is to measure it.Start with the free mini-eval or a 15-minute call
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The two most common paths are the first two rows: you either have an AI feature you can’t prove, or a release process you can’t trust. Both start by measuring the failure surface before anyone writes code.

#The lowest-friction ways to start

Whichever row you landed on, there are three doors in, ordered by commitment. Most people start with the first — it costs nothing and does real work.

1 · Free mini-eval

Point me at your live AI feature and I run a batch of real adversarial probes — injection, hallucination, scope, PII, tone — and send verbatim pass/fail findings. No call, no cost. See the sample report first.

2 · The audit

A short, focused engagement (about a week) that maps your highest-leverage failure surface and hands you a prioritized plan you own plus a concrete quote. If I can’t help, I say so and it costs nothing.

3 · A 15-minute call

Describe the problem and I tell you honestly which of these it needs, what it takes, and roughly what it costs — or that it doesn’t need me at all. You leave with a plan either way.

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See the format before you commit: the sample report shows exactly what a mini-eval hands back, and the live eval grades an AI in your browser in real time — try “bring your own AI” on a real answer of yours.

#If none of the rows fit

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If nothing above sounds like your problem, don’t force a fit — book a 15-minute call and describe it in plain terms. If it’s not something I can genuinely help with, I’ll tell you that directly rather than sell you a package. A clear “this isn’t for me” is a better outcome than a wrong engagement.

Once you know the capability you need, each page above goes deep on what it is, what you get, and how it works — and every one ends with real proof you can open. When you’re ready to see the whole path from a short audit to a shipped, owned system, read How engagements work.

Found your row?
Start with the free mini-eval, or book a call and I’ll tell you honestly which path you need.
Build your plan → 2 minor book a call →
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