AI made writing code faster.
It didn’t make shipping software any quicker.
We guide WordPress engineering teams as they build the context, pipeline, harness, and feedback loops that
make AI work at the organizational level.
Nobody designed the system around the tools.
91% of engineering teams have adopted AI coding tools. Organizational productivity has improved by less than 10% (DX, 121,000 developers surveyed).
The tools work individually. Nothing connects them at the organizational level. There’s no shared context for AI to work from, and what one developer learns doesn’t benefit the next developer who faces the same problem.
The next tool won’t close that gap. The gap is organizational.
You onboarded your developers.
You didn’t onboard your AI.
Every organization invests months onboarding human developers. Building up context about the codebase, the architecture, the unwritten rules. Then the same organization gives an AI agent a blank context window and expects useful output.
~6% of organizations are seeing
real financial returns from AI
~3× more likely to have redesigned
how their teams work
before deploying the tools
— McKinsey, State of AI 2025
The instinct to fix and ship is what makes your team good.
When AI produces something that doesn’t match your codebase, your engineer catches it in review, fixes it, and moves on. Problem solved. Sprint commitment met. Nobody stops to ask how to prevent that class of problem from reaching the team again, because fixing it is the job.
The next developer who hits the same area rediscovers the same constraints from scratch. What your senior engineer figured out in that review lives in their head until they leave, change projects, or forget.
The better your team is at fixing and shipping, the longer this pattern persists.
What the 6% built
What they built isn’t a tool or a platform.
It’s organizational infrastructure with five properties.
You’ll recognize which ones are missing.
01
01 / PRINCIPAL_COORDINATION
Coordination
A path from business intent to shipped code that doesn’t degrade at every handoff.
FIG. 01 / PRINCIPAL_COORDINATION
02
02 / PRINCIPAL_CONTEXT
Context
Organizational knowledge encoded so AI agents and engineers work from the same source.
FIG. 02 / PRINCIPAL_CONTEXT
03
03 / PRINCIPAL_PIPELINE
Pipeline
A development process designed around AI-assisted delivery, not bolted onto the old one.
FIG. 03 / PRINCIPAL_PIPELINE
04
04 / PRINCIPAL_HARNESS
Harness
Review agents that catch what AI got wrong before your engineers have to.
FIG. 04 / PRINCIPAL_HARNESS
05
05 / PRINCIPAL_COMPOUNDING
Compounding
What the team learns during delivery flows back into how the tools work next time.
FIG. 05 / PRINCIPAL_COMPOUNDING
The specific AI tools your team uses will change.
The thinking that makes them effective won’t.
You can’t buy this.
Your team builds it.
What working with Principal WP looks like
Not a report delivered at the end. Not training your team forgets by Friday.
Workshops on your codebase, paired sessions on real problems, and continuous review of everything your team produces.
Your engineers encode organizational knowledge so AI can work from it. They structure the pipeline, build automated review, and bring upstream stakeholders into working sessions to align how intent reaches engineering. And they build the learning loops, so what they figure out this quarter is still available next quarter.
Not exercises. Infrastructure they’ll use on Monday.
After twelve weeks
Your team has working AI infrastructure on their codebase that they built and understand.
They maintain it without us.
It doesn’t depend on any single engineer.
And it gets better every cycle.
Get in Touch
Every engagement starts with a conversation.
Tell us about your team and what you’re trying to solve.
No sales pitch. No proposal template.
Just a direct conversation with one of the folks who would do the work.
See the framework in code
We’re publishing our open-source reference implementation on GitHub in mid-May — a working example of what this framework looks like in an enterprise WordPress context. It shows how we think. Newsletter subscribers get early access.