What the work is for
The best engineering organisations run on a discipline most companies never reached: the SRE, cloud, and security practice that separates teams that ship reliably from teams that do not. AI has now landed on top of that gap.
The result is predictable. Teams are overwhelmed by a technology moving faster than their operating model. They accept vendor defaults because they have no basis to question them. They spend heavily, and they do not audit the spend.
The work closes that gap. We bring the operating discipline of the best engineering teams to your AI program — across advisory, cloud and platform integration, product strategy, and embedded build — so you leverage AI the way those teams would, instead of accepting the default. The outcome is not a tool you bought. It is a capability you have, and keep.
How an engagement runs
The work ranges from advisory — how to leverage AI at all — through cloud and platform integration to embedded engineering. What is constant: Loom is partner-led and senior-only. The people who scope your program are the people who do it. There is no handoff to a junior delivery team after the contract is signed.
When the work is build, we work forward-deployed: our engineers commit to your repository, run on your CI/CD, and join your standups. The system is built where it will live, by a team that includes yours — so the people who will operate it afterward helped build it. Knowledge transfer is not a final-week event; it is the shape of the work. (More on what that requires: what forward-deployed engineering actually means.)
Scope, build, transfer
Every engagement runs the same arc. The end-state is your team running the system without us.
Scope.
A long conversation about what success looks like at year two, not only year one. We write down what the program must leave your organisation able to do — modify the system without us, survive a model or vendor change, hold an audit trail through a personnel transition — before we contract.
Build.
Senior engineers shipping in your codebase, on your infrastructure — production-grade and owned by you on day one. Not a parallel build that arrives finished and undocumented.
Transfer.
The deliberate end-state: your senior team can modify, govern, and extend the system without us. We engineer ourselves out of the critical path on purpose.
What we hold ourselves to
We judge the work at year two, not month six. Two commitments make the difference.
The decision record. For every consequential decision — model selection, vendor commitment, scope change, architectural trade-off — we record, before the decision is made, three things at once:
What it produces now.
Throughput, customer outcomes, financial results, defect rates. The standard performance read.
What it does to your capacity a year out.
Your team's skills and judgement. The substitutability of vendors. The thickness of customer trust. The resilience of operational practice.
What it does to your ability to adapt.
Time-to-response when a model is deprecated, a regulation changes, or a person leaves on either side.
You finish the engagement with a record of which decisions worked, which did not, and why — alongside the system itself.
Straight vendor advice. When a vendor's cheap SDK creates the kind of lock-in that costs you in year two, we say so — even when our own partnership economics would prefer the other answer. We take no referral fees, no kickbacks, and no vendor incentives that would bias a recommendation.
The approach draws on systems thinking — Deming, Meadows, Goldratt — and is one applied chapter of the Regenerative Intelligence framework. The research sits at kevindickerson.com; the applied writing is in our Index.
What we will not do
We do not work on lethal weapons, surveillance, manipulation, or fraud — technology whose purpose is harm. We screen for this at scope.
We also decline engagements that cannot support the embedded model. A drive-by build with no capability transfer is the engagement most likely to fail at year two, and it is not the work we do.
The first conversation
If you are scoping a multi-year AI program where audit, governance, or strategic optionality matter, the conversation should happen before the architecture is locked in. The decisions that get measured are the decisions that get made.
It is not a sales call. It is about what your program will build, what it will leave behind, and what that requires of the work.