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The Mainline Approach

The Factory
Problem

Every organization just got a new engine. Almost none have redesigned the factory.

The Pattern

New Motor, Same Factory

1890

Factories swapped steam engines for electric motors.

No productivity gains for 30 years. They redesigned the motor, not the factory floor. Same layout. Same workflows. Same bottlenecks. Just a different power source.

2026

Companies are swapping in AI tools.

Giving everyone ChatGPT and Claude Code licenses. Same workflows, same processes, same org charts. Individual productivity goes up. Organizational output stays flat.

“Individual AI productivity tools have not made companies 10x more valuable.”

The gains leak out through coordination failures and process debt.

The Evidence

Code Already Figured This Out

The coding world proved that the harness matters more than the model. With data.

0x

improvement from harness alone

Slate V1 Terminal Bench

0M

lines of code, zero human-written

OpenAI internal

42→0%

same model, different harness

Claude Opus benchmark

They stopped at code. What about marketing? Operations? Strategy? Hiring?

The Framework

Five Roles, Infinite Depth

Every organization, every team, every process can be decomposed into five roles. The pattern is fractal: each Executor becomes a Decision Maker at the next level down.

1

Decision Maker

Owns outcomes. Sets direction. Human at the top level.

2

Coordinator

Routes work. Maintains context. Where judgment concentrates.

3

Researcher

Gathers intelligence. Synthesizes options. Surfaces what matters.

4

Reviewer

Catches gaps. Validates quality. Embedded at every level.

The pattern repeats at every level. Click the Executor to see it again.

The Spectrum

Intelligence vs. Judgment

Not everything automates. The question is knowing which parts of your organization are intelligence (complex but rule-based) and which are judgment (experience, taste, strategic calls).

Intelligence

Complex but rule-based. Automates with AI.

Judgment

Experience, taste, strategic calls. Stays human.

Researcher

Mostly automates

Executor

Mostly automates

Reviewer

Interesting middle ground

Coordinator

Interesting middle ground

Decision Maker

Stays human

The question isn't whether to adopt AI. It's knowing which parts of your organization are intelligence and which are judgment.

The Convergence

Why This Compounds

This isn't a one-time transformation. The organizations that build this muscle now will have a compounding advantage that's hard to replicate.

Today

Services

Human judgment combined with AI intelligence. We design and build the systems.

6 months

Compounding

More intelligence automates. Judgment focuses on highest-value decisions. Data from every engagement makes the next one faster.

18 months

Advantage

Institutional memory is deeper. Context architectures are more refined. Feedback loops have been running longer.

Their institutional memory will be deeper. Their context architectures will be more refined. Their feedback loops will have been running longer.