the delivery arm · 2026
We build software the AI-native way and govern it end to end. Speed with a spine.
checked · scored · traceable
the inversion
The AI-native SDLC inverts. The bottleneck moves from writing code to reviewing and verifying it: teams generate far more and ship no faster, because the work now piles up at the gate. The answer is not more generation. It is governance that makes review high-leverage, with judgment moved upstream, decisions made per unit, and evidence attached to every change.
Sources: 1. GitLab 2026 AI Accountability Report (conducted by The Harris Poll, 1,528 respondents across six countries); 2. Faros AI 2025 telemetry (10,000+ developers, 1,255 teams). The bottleneck did not vanish, it moved to the gate. We govern the gate.
01the market reality
Scan the field and it sorts into tiers. Almost everyone sits at the bottom: an AI page bolted onto delivery that never changed. A few built a named methodology and a platform, and a few now say the word "governed." One tier up is still empty. Nobody restructures the work itself, decides machine versus human per unit, and holds every decision to account. That is the tier we build in.
The gap is not tooling. Analysts already named it: most teams now run AI agents in delivery with no formal governance, and the specific decisions those agents make belong to no one in particular. Governing the pipeline, or approving the finished pull request, does not close it. The unit of accountability has to be the work, not the output.
02how we work
Every engagement is broken into atoms: the smallest reviewable, traceable, estimable units of work, defined before any implementation or tooling choice. Each atom is then assessed for who does it best, machine or human, so autonomy comes through augmentation, not abdication. The system carries the cognitive load; people keep the judgment. Underneath, the method rests on three primitives:
The smallest reviewable, traceable, estimable unit of work, drawn before any implementation or tooling choice. Sized by judgment, not line count.
Machine or human, chosen per atom, on purpose and before the work starts, with the choice and its reason on the record.
Warn, route, or block, each with a confidence and a reason. Overriding it is as hard as the risk of being wrong, and the override is itself classified and recorded.
The atoms run through one control loop, the same loop at every altitude of the work. Nothing advances a stage it has not earned. Skip a step and you automate chaos faster.
Sense the real state from the code, not the claim.
Decompose intent into atoms that carry their own proof.
Score on a deterministic, replayable math layer.
Warn, route, or block against calibrated policy.
A human overrides in proportion to the risk.
Every decision becomes data the next loop reads.
03why it holds up
The model proposes; a deterministic layer decides. No stochastic output ever gates a state change. Every verdict recomputes from frozen inputs with zero new model calls, so it is replayable, auditable, and hash-chained. That is the difference between "an AI wrote it" and being able to prove what shipped, and why. Trust here is a function of predictability and transparency, not a promise.
Reads code and context. Produces raw observations, findings, and evidence. The only place a model runs.
Scores, attribution, reliability bundles. Recomputable from frozen inputs and pinned versions. The authority.
Warn, route, or block, written to an append-only ledger. Every change we ship carries the evidence that cleared it.
Compiler-grade fact, verified at a location. Weighted highest.
A reasoned link, marked as inference, never as proof.
Confirmed not there. Recorded, because a gap is a finding.
Every atom ships with a receipt.
One decision, one owner, and the evidence that cleared it, chained to an append-only ledger. This is what turns "an AI wrote it" into a record you can replay and audit.
04what we build and maintain
Greenfield or brownfield, a one-off read or an ongoing team, every engagement runs through the same decomposition, the same deterministic gate, and the same audit trail. Start small and low-commitment, or embed us end to end.
New products, built AI-native from the first atom. Decomposed, assigned, and governed from day one, never audited in after the fact.
OUTCOME-BASED · new productBrownfield systems mapped and decomposed, then modernized atom by atom. Ongoing maintenance runs under the same governance and the same trail.
BUILD + RUN · legacy to liveA fixed-scope, fixed-fee read of a codebase or a single change. The lowest-commitment way in: you get the evidence, and the decision record, before you commit to a build.
FIXED SCOPE · the entry pointA forward-deployed engineer plus the platform, embedded with your team. You buy governed outcomes, not hours. The pod carries the load; a named person owns the judgment.
SERVICES-AS-SOFTWARE · embeddedaudit to scope · build to ship · modernize to renew · a pod to stay. Every path writes to the same ledger.
05the model
You do not rent a rack of hours or an offshore team you never meet. You buy governed outcomes: units of work the platform carries, each with a named, forward-deployed engineer accountable for it. The software does the work. A person owns the judgment. Your receipt is a decision record, not a timesheet.
A forward-deployed engineer is a senior builder who embeds with your team, wields the platform, and stays accountable for the atoms they own. One person you can name, not a pool you cannot.
three ways to work with us
Same governance brain underneath. You choose how the work reaches it.
Autonomous workers grind your specced backlog under org keys, governed end to end. Machines carry the volume; the gate admits only what passes.
Your developers work in their own agents (Cursor, Claude Code, Codex, Gemini) under their own subscriptions. We govern the output: pull a ready atom, request a family-diverse review, submit through the gate. Tool-agnostic by design.
A forward-deployed engineer joins your team and stays accountable for the atoms they own. The human compiler: intent in, governed change out.
beyond software
The same governed spine works wherever generation outpaces trust. In marketing that means content, campaigns, and lifecycle automation: decomposed into atoms, generated by machine where it fits, and checked against brand, claims, and compliance before anything reaches an audience.
Explore governed marketing →for teams that build
Not everyone needs us to build for them. If you already ship code, run products, or deliver for clients, you can adopt the instruments and the method that govern our own work, and run them inside yours. Your team, your stack, our spine.
See the partner program →the price
Most firms sell hours and hope. We measure work deterministically, so we can price on the result. The same governed method runs consultancy, software, and marketing automation, and prices the same way.
the on-ramp
Pay as you go
metered · no lock-in
Metered by governed unit. You hold the risk, and you hold the exit: at any stage we hand off a fully traceable, ownable work-product to you or any agency you choose. No black box, ever.
the default
Fixed outcome
shared risk
We define the outcome together as a governed spec, charge near breakeven on infrastructure and talent, and put our margin on delivering it. If it does not verify, support is free until it does. We are paid when it ships and passes, not before.
the metric
Performance
for measurable outcomes
Wherever the result is a measurable number (conversion, uptime, cost saved, cycle time), part of the fee tracks the lift. Our incentive becomes your metric.
Base at cost, barely marked up, plus an outcome fee tied to the value we define together. We publish the structure, not a rate card, because the price is a function of your outcome, and that is yours to set with us.
06the proof
We did not learn governed delivery on your codebase. We built the governance engine itself this way. AmphSE orchestrates frontier coding agents, Claude Code, Codex, Cursor, and Gemini, under one governed loop, taking a backlog to verified, deployable code on the hardest and most measurable domain in software: its own construction. Its sibling instrument, CodeSentinel, audits code across 28 areas with 408 checks and a full reliability bundle. The method is the product, and the product is the proof. It rests on a formal foundation: The Fractal Org, a general theory of the autonomous enterprise.
The share of atoms that clear their gate on evidence, per engagement.
How much of a change is checked deterministically, not sampled.
What the governance layer catches before it ships, not after.
Variance between estimate and actual, measured atom by atom.
These are numbers our system produces that a status deck cannot. Figures publish per engagement as pilots close.
A first design-partner engagement. Metrics and write-up publish on close.
The AmphSE build itself, governed atom by atom. Walkthrough available under NDA.
A brownfield modernization pilot. Case study to follow.
Start with a fixed-scope governed audit, or a governed pilot. Either way, you see the evidence before you commit to the build.
Machines do the work. A named human stays accountable.