We help government and enterprise engineering teams build real AI fluency — through structured workflows, peer learning, and skill progression that sticks. Not a one-day workshop. A capability your team owns.
85%
average adoption rate across programs
150+
engineers onboarded to AI workflows
4
enterprise adoption programs delivered
8 weeks
average time to measurable adoption
EXPERIENCE ACROSS SECTORS
Government
Oregon State Government — Engineering AI Team
Enterprise
Nike, Warner Bros, Microsoft
Results
Tools still in daily use 6+ months later
AI fluency isn't built in a 2-hour workshop. We design structured skill progression — novice to intermediate to advanced — with peer learning loops that build confidence over months, not days.
Structured progression • Peer learning • Long-term habit formation
We start with AI tools that fit how your engineers already work — not the other way around. Engineers keep ownership of their work — AI handles the repetitive parts so they can focus on what matters. No one gets replaced.
Workflow-first design • Engineer ownership • Augmentation over automation
Government and enterprise have real constraints: procurement, governance, cross-team accountability. We've navigated these. Your team doesn't need to figure this out alone.
Government-ready • Governance-aware • Cross-team coordination
2-3 month engagement
Ongoing engagement
6-12 month engagement
4-6 week engagement
A snapshot of current and past engagements, with deliverables and outcomes your team can review.
Embedding AI workflow integration across engineering teams — building daily-use habits through structured skill progression and peer learning.
Highlights
Deliverables
Designed and led an adoption program for AI coding assistants across 150+ developers — achieving 85% active usage through structured onboarding and peer learning cohorts.
Highlights
Deliverables
The team wasn't using the AI copywriting tool. We redesigned the workflow around how copywriters actually work — adoption hit 100% and saved $1.9M annually.
Highlights
Deliverables
What adoption looks like when it actually works.
150 Developers, 85% Active Usage
A monolithic codebase with limited docs. Developers were leaving the IDE constantly just to find code snippets. Over eight months we onboarded 150 developers in phases: setup guides first, then hands-on workshops with a prompt playbook, then a focused refactor sprint on the Payment Service module. That sprint ran 4× faster with 90% test coverage. Suggestion acceptance hit 70%, satisfaction averaged 4.2/5.
85%
active adoption (target: 75%)
70%
suggestion acceptance
4×
refactor sprint speed
4.2/5
developer satisfaction
Current Engagement
Working with the state's engineering team on AI workflow integration. The focus is structured adoption: building daily-use habits through skill progression and peer learning.
0% → 100% Writer Adoption
The AI copywriting tool existed. Nobody was using it. Writers found it clunky and disconnected from how they actually worked. We redesigned the workflow to fit their process, not the other way around. Adoption went from zero to 100% of the writing team, SLAs jumped from 72% to 100%, and the $1.9M agency contract got retired. A/B tests showed product pages with AI-assisted copy lifted cart-add rates by 8.9%.
100%
writer adoption (was 0%)
72% → 100%
copy SLA hit rate
$1.9M
agency spend eliminated
+8.9%
cart-add rate (p < 0.01)
11 Teams, 8-Week Rollout
The old chatbot handled 5% of 16M+ annual chats. Leadership wanted an LLM replacement but 11 teams had to agree on rollout, governance, and escalation paths. We designed the phased adoption plan, aligned the squads, and got it from internal pilot to 10% live traffic in eight weeks. The agents who were skeptical about AI chat saw resolution times drop from 7 minutes to under 3. Cost per chat went from $6.33 to $1.98.
11 teams
aligned on rollout
8 weeks
pilot to live traffic
7 → 3 min
resolution time
69%
cost per chat reduction
From first audit to full team ownership — in weeks, not quarters.
We believe the best AI programs make teams stronger — not smaller. That's the work we do.
A small, focused team that embeds with yours. We work alongside engineers, not above them — building fluency through structured workflows, peer learning, and skill progression that sticks.
Currently working with Oregon State Government engineering teams. Previously led AI adoption programs at Nike, Warner Bros. Discovery, and Microsoft.
Team
Credentials
Book a free 30-minute call. We'll look at where adoption stalled, what's actually blocking your engineers, and what a structured path forward looks like.
No pitch deck. No pressure. Just a candid conversation about what your team needs.
Email Brief
What's working (and what isn't) in government and enterprise AI adoption. One email per month.