The market is already delegating real work to agents — and already demanding an accounting for it

• —Portfolio leads and PMOs are accountable for tying AI spend to results and for distinguishing AI work from human work in reporting to the board. A survey of 300 senior PMO leaders (Tempo/Potloc, June 2026) names this the top-priority KPI of the current year.

• —CTOs and VPs of Engineering at companies that have already moved past the pilot stage (43% of enterprise codebases in 2026 versus 12% in 2024) measure productivity and oversight at the same time: 89% report a productivity gain, and that very same wave is turning oversight of AI output into a visible line item on the engineering leader's own KPIs.

• —Both profiles need not one more status-tracking system, but a structural record of who proposed what, what was rejected, and why — something that can be handed to an auditor, a board, or a client without retelling the conversation.

An order of work where every decision is verifiable — like bookkeeping

Arkhitsyn is a rule for working with an AI assistant on a project: every important decision is first recorded with its alternatives and the reason it was chosen, and then a separate "second pair of eyes" (also AI) hunts for the error in it before the decision turns into code or a contract. As a result, the project's history always shows what was proposed, what was rejected, and why — not just what came out in the end.

• 01Alternatives and the criteria for judging them are fixed before the choice is made — there is no way to retroactively fit the decision to an answer already settled on.

• 02A separate role that took no part in the decision independently reviews it for concrete factual errors — not a rubber stamp, but an active search for a named defect.

• 03The decision log only ever grows downward: an error is never erased by an edit, it is acknowledged in a new entry next to the old one — history is never rewritten.

Minutes to a fix, not a sprint and not a stage

By comparison: the "what went wrong — let's correct it" review in PRINCE2 and Scrum happens, by definition, once per stage or once per sprint (Scrum Guide 2020: a retrospective once a month for a month-long sprint). In arkhitsyn, that same review happens at every step of the pipeline.

• —CI/CD for several game builds (github-deploy pilot) reached a green three-platform build within three rounds in a single day — macOS 1m15s, Windows 3m29s, Ubuntu 1m42s.

• —The method writes its own new rules in response to what it finds: verbatim-quote discipline, mandatory independent review of the coordinator's decisions, carrying a verified fact forward into reusable knowledge — every rule emerged inside the project itself, none was planned in advance.

flowchart LR
    subgraph Agents["Agents (role = owner of its own card)"]
        AG["its own findings,
new questions,
progress
on ITS OWN task"]
    end
    subgraph Dispatcher["Coordinating process"]
        DI["task status,
who's driving,
decision → proposed"]
    end
    subgraph Navigator["project map"]
        NAV["state,
log,
summaries"]
    end
    subgraph Human["Human"]
        HU["everything;
the only one who sets
decision → accepted"]
    end

    Agents -.->|"never touches another
task or the maps"| Dispatcher
    Dispatcher -.->|"never touches accepted"| Human
    Navigator -.->|"never touches task content"| Agents
    

WUXIN: X-ELEMENTALS — not a pilot, a shipped application

Five board games in one app (Gomoku, Dots, Go, Reversi, Pyramid) with 3D rendering via three.js, for desktop and mobile platforms — built with the very same method described above, from the first recorded decision to the public build.

• —The Android build is actually built and published as a GitHub Release — downloadable by direct link today.

• —618+ automated tests green, a clean type check, all five games run through live by hand in both themes across every input method — tap, wheel, right-click, shift-click, two-finger gesture.

• —The build was verified beyond CI's own green status: the package was unpacked by hand, and the presence of the specific fix in question was personally confirmed in its code.

From market size to a real capture point

Growth today runs through package licensing plus hands-on rollout support — exactly how every current pi-space pilot already operates. Investment unlocks the next rung of scale: a network of certified partners (modeled on the Claude Partner Network) and a platform that turns rollout support from the coordinator's own hands-on work into a service.

Three channels — from organic reach to a ready-made partner network

• —Dedicated communities — r/ClaudeAI (1.06M members), r/ClaudeCode (≈387K), r/LocalLLaMA (806K) — the exact people working with agentic development every day.

• —Dedicated industry summits (AI Engineer Code Summit, Agentic AI Summit) — the attendee list is already filtered by the organizers down to actual decision-makers.

• —Claude Partner Network — a ready-made network of 150,000+ certified consultants and 40,000+ enrolled firms (Accenture, Deloitte, PwC, KPMG, Slalom, Tribe AI, Turing), launched by Anthropic in March 2026 with a $100M fund for training and go-to-market.

Both figures sit above the B2B SaaS industry median (3.2–4.1:1, Aleph/Benchmarkit 2026). The organic channel is what every current pilot already grows on; the partner channel is the next wave of growth, with its commission base already fixed in advance.

Investment means concrete next steps, not abstract growth

• →A network of certified partners. The commission band (10–15% per referral, 20–25% recurring for rollout) is already set — the first partners inside the Claude Partner Network will turn it from a modeled figure into a measured practice.

• →Platform. The methodology's harnesses and validator are command-line tools today; the next step is deploying the same capability as a service with its own interface, available with no installation.

• →First contract. It turns customer acquisition cost from an estimate into a measured figure — and sharpens the economics of every channel beyond the band shown on this page.

• →Expanding the evidence base. Every new pi-space pilot (more than a dozen today) adds one more measured data point alongside the minutes and hours already shown — WUXIN proved the method reaches all the way to a public, downloadable result, not only an internal pilot.

• →The Arkhitsyn trademark. Registering the name is the nearest organizational step on the way to the first contract, running alongside the work itself, not blocking it.