Our prediction

Enterprise codebases bloated on AI
will bottleneck by June 2027.

AI adoption shows up in delivery velocity about twelve months later. Companies that adopted hard and ungoverned through 2025 and 2026 are seeing it now.

Those that wait will hit June 2027 unable to ship reliably, to hire engineers who will touch the codebase, or to unwind the debt at the speed the market expects.

The question isn’t whether the bill comes due. It’s which side of June 2027 you want to be on.

What’s compounding

Three ways AI-written code
goes wrong.

01 — Architectural drift.
Agents optimise for the prompt, not the system. Drift accumulates one feature at a time, until no engineer can reason about the whole.
02 — Compounding defect rate.
AI-written code looks right because it reads right. Tests written by the same AI miss the same blind spots. The defect rate compounds.
03 — Governance void.
The vendor doesn’t own the output. The engineer didn’t fully understand the tool. The next hire inherits code with no author.
Our position

Our position: discipline first,
speed second.

We use AI in every engagement. Any team can ship AI-written code fast; few can ship code the next hire will maintain and the next auditor will sign off.

Architecture decisions stay human. Evaluation gates sit between every agent output and production. Governance is a release criterion.

The instruments themselves — the golden path, tiering, reuse gates, the mapped codebase and the one control surface — are on the Method page →

What we do

How we help.

Start here
01

The AI readiness audit

2 weeks

Four workshops: is your AI adoption accruing leverage or debt? Free if we don’t surface three material risks. Our guard-rail templates — evaluation gates, governance patterns, audit trails — follow on engagement.

Start with a studio audit →
02

Fractional AI leadership

3–6 months

Senior AI judgement in the room every week without the full-time hire. We lead your roadmap, hold your team to a higher standard, hand over clean when you’re ready.

See how fractional works →
What we don’t do

What we won’t do.

We don’t sell AI transformation programmes. The phrase assumes the outcome is known before the work begins.

We don’t replace your engineering team with ours. If the right answer is a full-time CTO hire, we’ll tell you and point you to the search firm.

We don’t build custom models. The edge in this cycle is operational discipline around the foundation models that already exist.

And we won’t take engagements where speed trumps everything else. The client who wants speed above all other values is not a client we can serve honestly.

The advantage goes to teams that adopt AI
with discipline, not the fastest.

The teams that thrive through the next cycle won’t be the ones that adopted fastest. They’ll be the ones that built the guard-rails while the adoption was happening.

Start with a studio audit. Two weeks to clarity.

Book a studio audit →