Category

Strategy

How to decide about AI: what to build, what to buy, where judgment belongs, and which problems a machine can actually finish.

22 posts

The Constraint Is the Work 7 min read

The Last Human Job Is Owning the Predicate

At every layer the job collapsed to one shape: own the irreversible commitments, define the invariants, adversarially audit the definitions. The rest is tokens.

The Constraint Is the Work 7 min read

The Regression Ratchet Has No 'Done'

A test suite only encodes the attacks someone already ran. It raises the floor and says nothing about the ceiling, so QA becomes a permanent red team.

The Constraint Is the Work 6 min read

Ask for Attacks, Not Tests

Test generation samples the happy path: coverage theater. Vulnerability finding is adversarial search with a real target. The prompt is the difference.

The Constraint Is the Work 6 min read

Allocate Architects by Irreversibility, Not Difficulty

Hard problems are now cheap to retry. The cheap-looking calls (a field's type, an event's ordering) are the ones you can't undo. Most orgs route backwards.

The Constraint Is the Work 7 min read

Human-in-the-Loop Is a Rubber Stamp Unless It's Adversarial

A passive monitor of a reliable process is a rubber stamp with a person's name on it. Oversight that doesn't attack isn't oversight. It's laundering.

The Constraint Is the Work 7 min read

The Harness Is the Moat: Why That Doesn't Contradict 'Harnesses Aren't IP'

Trading engineering hours for tokens is not a linear trade. Implementation collapses to zero; specification and validation surface all at once, up front.

The Constraint Is the Work 8 min read

The Design→Test Loop Finishes Closable Problems. It Can't Touch Open Ones.

What decides whether an AI loop can own a problem end to end is not difficulty. It's whether the problem closes, and an adversary keeps it open forever.

The Constraint Is the Work 7 min read

Is Anything in Software Still Novel?

Component-level novelty went nearly extinct. The industry's novelty budget moved into constraints, and that decides how to use AI on a real codebase.

The IP Framing Problem in AI 12 min read

What the Lawsuits Are Really About

NYT v. OpenAI, Bartz v. Anthropic, Thomson Reuters v. Ross. Everyone is watching the doctrine. The market has been telling a different story the whole time.

5 min read

The Platform Fee Hiding in Your AI Budget

Some AI gateways charge a percentage of every dollar you spend on AI. At enterprise scale, that percentage becomes the largest line item in your budget.

The IP Framing Problem in AI 14 min read

Agents Don't Have IP. Workflows Do.

The agentic-AI gold rush extended the IP framing onto a layer where it makes even less sense, and is producing very expensive prompt wrappers.

The IP Framing Problem in AI 12 min read

The Half-Life of a Prompt Is Shorter Than Your NDA

The industry's prompt-protection playbook rests on a layer the Copyright Office already found doesn't confer authorship. Here's where real protection lives.

The IP Framing Problem in AI 12 min read

Your Data Isn't a Moat. Your Loop Is.

A contrarian read on the AI industry's favorite defensibility argument, plus a three-filter test for telling a real moat from data hoarding theater.

The IP Framing Problem in AI 5 min read

Introducing: The IP Framing Problem in AI

A four-part series on why most AI defensibility strategies are protecting the wrong thing, and what actually works in 2026.

5 min read

Shadow AI Is Already in Your Enterprise

Your employees are already using AI tools you did not approve, with data you cannot track. The question is not whether to allow AI, but how to govern it.