Level 2 · The Harness
Every seat, properly rigged.
Chat windows got your team to first base. The harness is what gets AI into the actual work: your context, your systems, your permissions, one command at a time.
The ceiling
Many of your best AI users have likely hit a ceiling. Copy and paste between AI chat windows and continually re-explaining details to an LLM starts to feel tedious and encourages lazy behavior as the models grow smarter. The results are impressive (for last year's models), but it's not uncommon to spend just as much time working an effort with AI as doing it the old way.
The stack
Four layers, one harness.
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Foundation
Claude Code configured for every team member, loaded with company context, permissions, and persistent memory, so sessions build on each other instead of starting from zero.
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Connections
Secure MCP integrations to the systems you already run: email, docs, sheets, schedules, CRM. The AI works where the work is.
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Skills
One-command workflows for reporting, meeting notes, publishing, and follow-ups. Your team invokes them; nobody re-invents the prompt.
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Training
A fluency curriculum, live sessions, and 1:1 workflow coaching. The six skills that matter, and none of them are "prompting techniques".
Your people
The tools don't bring the value. Enabled people do.
Top AI talent is earning over $500,000 a year, and many companies don't have an obvious slot for that hire anyway. Almost every company has something better: a team of smart people who can learn to work with AI. When you start to add 2-3x productivity to many employees, your compound results are huge.
That's why training isn't a webinar at the end of our engagement. It's a curriculum built around the six skills that actually matter - context assembly, quality judgment, task decomposition, iterative refinement, workflow integration, and knowing where the frontier is - taught inside your workflows, not from slides. Live sessions for the team, 1:1 coaching for the people who'll carry it furthest.
Already bought Copilot?
Forty seats, a launch webinar, and eleven active users by spring. We hear a version of this often, and the seats were rarely the problem: nobody showed the team what good looks like in their work. We rig the harness and the training around the tools you already own before recommending anything new.
The math
A reasonable scenario, so you can check it.
Take a contractor with 60 people in the office: PMs, engineers, coordinators, accounting. Say the harness gets half of them genuinely fluent, and each one clears four hours a week - the meeting notes that write themselves, the daily report that takes twenty minutes instead of three hours, the submittal log that stays current on its own. Four hours is conservative next to what people claim on social media.
30 people, 4 hours, 48 weeks: about 5,700 hours a year. That's roughly three full-time positions of capacity you didn't have to hire, at whatever your loaded office cost says that's worth. Run it with your own numbers; the arithmetic holds up.
The hours are the boring half. The interesting half is the work you couldn't take before: the RFP you'd have no-bid for lack of estimating time, answered in a day. The flow-down clause caught before signature instead of at claim time. The closeout package that ships the week the job ends, not a quarter later. Speed you didn't have isn't savings - it's capacity you can sell.
Day one
One command onboarding
A new hire goes from an empty laptop to a fully configured AI environment with one installer and one command. We built that for our own team first because we were tired of doing it by hand.
Vendor-agnostic, on purpose.
We deploy Claude Code by default and support other vendors where they fit. We don't resell licenses or take referral fees, so the recommendation is the recommendation.