A practical framework for AI use-case prioritization
A scoring model for weighing feasibility, data readiness, and business value — so the roadmap survives contact with engineering.
Read the guideField notes
Guides and playbooks from active engagements.
What we've learned reengineering legacy systems and shipping agents into production — written down so it's useful before you talk to us.
Guides
Start here if you're setting direction.
Build vs. buy: evaluating AI vendors without the hype
The questions to ask a vendor about data handling, lock-in, and evaluation before signing anything.
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What "production-ready" actually means for an agent
Nine criteria we check before an agent gets access to a real system — beyond "the demo worked."
Read the guidePlaybooks
Step-by-step, for teams doing the work themselves.
Monitoring and fail-safes: a starter checklist for agentic systems
Tracing, evals, and circuit breakers you can stand up in a week, before your first agent goes live.
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Standing up a responsible AI review board in 30 days
A lightweight governance structure sized for a mid-size engineering org, not a Fortune 50 compliance team.
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The strangler pattern, applied to a legacy monolith
How to carve a first slice out of a tightly-coupled system without stopping the business while you do it.
Read the playbookWant the next one first?
New guides land occasionally, not on a schedule.
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