Build Capacity · For the CTO and IT leaders
Ship faster, and clear the backlog everyone else is waiting on.
Every company has a backlog of internal tools and automations that people have asked for. It grows because engineering capacity is spent on the product, and requests from the rest of the business wait.
The Leverage Diagnostic takes about 6 minutes. No call required.
Why it matters
Engineering and IT throughput.
AI coding tools can change the math, but only when they are set up with your standards, your codebase and your review process. Without that, teams get faster drafts and the same delivery speed.
We find the point where a small change moves the number, build the system, and measure what it moves.
Where it hides
Four places build capacity leverage leaks.
01
Tools used ad hoc
Some engineers use AI coding tools daily, without shared standards or context from your codebase.
02
Slow path to users
A finished change waits days or weeks for review, testing and release.
03
The internal backlog
Requested tools and automations that never reach the top of the list.
04
Knowledge in a few heads
Decisions, systems and ownership history known only to long-tenured engineers.
What the Diagnostic asks
Three questions that score your Build Capacity.
Answer them with the rest of the Leverage Diagnostic and you get a score, a priced gap with the math shown, and the moves that pay back first.
Score your Build Capacity- 01What share of your engineers use AI coding tools every day, set up with your own standards and codebase?
- 02Once a change is ready, how long does it take to reach users?
- 03How large is the backlog of internal tools and automations that people have requested?
What we build
AI-native delivery setup
Coding agents configured with your standards and codebase, and the internal-tool backlog cleared in weeks.
- AI-native delivery setup: shared standards, codebase context, review and test gates
- A faster path from finished change to users, with automated checks
- An internal tools program that clears the backlog in priority order
Built inside your accounts and security rules, tested on known answers, and live with people reviewing every output on day one. See the company brain it runs on.
Proof and method
$0 to $500M
enterprise platform architected by Mike Kohl, who built the architecture himself, then hired and led the team around it.
Fortune 500
delivery at Allstate, Slalom Consulting and Catapult Systems.
Read the thinking
What a $500M Platform Architect Sees in Your Operating Model
Single points of failure, dark data, unversioned expertise, expensive talent on cheap work. An architect's audit of a mid-market company, in the order the findings would appear in the report.
Your Playbook Is Software Waiting to Be Compiled
The way your best people decide is a program that only runs on one machine each. How to inventory it, encode it, and ship the first version in weeks.
The AI Leverage Blueprint
The six moves from AI activity to results your CFO can audit.
Questions
Will this replace our engineers?
+
The goal is more throughput from the team you have, and a backlog that finally gets cleared.
Do you work with our existing stack?
+
Yes. We build inside your repositories, tools, security rules and approved vendors.
How do you keep AI-written code safe?
+
The same way you keep any code safe: standards, tests and review, plus logging of what the tools did.
The other five places leverage hides
Score your Build Capacity in six minutes.
A Leverage Score, a priced gap with the math shown, and the three moves that pay back first.
Start with Build Capacity