The AI Control Problem
The Reasoning Trace Is an Exfiltration Surface
6,708 public agent trajectories yielded 704 recovered secrets. Sixty-four of them existed only inside hidden reasoning blocks.
8 min read
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AI that works. Data you still control.
We implement AI for mid-market companies who cannot afford to lose control of their data or their decisions. One firm, strategy to production. We stay until it works.
Your company is already using AI. The question is whether anyone is governing it.
Employees don't ask permission. Copilot, ChatGPT, and a dozen others are already running inside your organization. Gartner estimates 40% of firms will face a shadow AI security incident this year. Kiteworks found 63% of organizations cannot enforce limits on what AI is actually doing with their data. The risk is not a future decision. It is a present condition.
Move Fast
Why Not Both?
Stay Safe
What the data shows
32.7%
AI code accepted without revision
LinearB, 2026, 8.1M PRs
66%
of developers cite AI's "almost right" problem
Stack Overflow, 2025, 49K+ devs
40%
of orgs will face a shadow AI incident this year
Gartner forecast
63%
cannot enforce purpose limits on AI systems
Kiteworks, 2026
19% slower
Developer output with AI tools (believed 24% faster)
METR, 2025
The gap between AI confidence and AI control is where our clients find us.
How we are different
One firm, strategy to production.
No handoffs between vendors. No lost context. No re-explaining your business to a new team every phase. The knowledge stays, the accountability stays, and the work keeps moving.
Governance built in, not bolted on.
Controls from day one, not an afterthought. We design for compliance, data protection, and explainability before we write a single line of code.
We stay until it works.
Not until the contract ends. Not until the hours run out. Until it works. This is contractual, not marketing.
Your AI Journey
Three offers. One progression. Start with knowing where you stand.
Built for companies where control matters
We work with companies in industries where AI cannot fail.
Healthcare
Providers, payers, healthtech
Financial Services
Banks, funds, fintech
Legal
Law firms, legal tech
Insurance
Carriers, brokers, insurtech
Scaling Startups
Series B+ with data to protect
The Thinking Wire
Published analyses on AI governance, implementation failure, and what the data actually shows.
More from our thinking
The AI Control Problem
The Adolescence of Technology: What Amodei Gets Right, What He Misses, and What It Means for You
Dario Amodei warns about AI risks from the inside. His essay is essential reading — but enterprise leaders need more than policy frameworks.
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Operating AI
Show People What a Prompt Costs and They Write Better Prompts
A study of 1.8M prompts from 61,000 users found cost visibility changed how people work, not just what they spend. The meter is feedback.
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Engineering Notes
The Scaffold Belongs in the Training Signal. Half of It, Anyway.
Thinking Machines showed RL on audited data beating scaffolded pipelines on text-to-SQL. What that proves, and what it leaves standing.
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The AI Control Problem
The Vendor Bias in AI Productivity: Why Your IDE Metric Is a Marketing Asset, Not an Audit Trail
The same task scored 98% AI in Windsurf and 52.6% in Cursor. Both vendors profit when the number is higher. The instrument is biased.
6 min read
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Operating AI
You Can Adopt AI Individually and Still Not Learn as a Company.
Three independent essays this week named the same failure mode: individual AI productivity that never compounds into organizational capability.
7 min read
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Ready to know where you stand?
Start with an Assessment. Four weeks. Clear answers. No commitment to what comes next.
Schedule Your Assessment CallNo commitment required. Let's just talk.