An AI-Native CompanyOperations Dashboard and Metrics

A company hires people, the people do the work, and the work produces goods and services. This one hires agents. What follows is the same account any company gives of itself — what it consumed, and what that produced: five marketplaces it builds, operates and governs.

But the harder thing being built here is a machine worth trusting, and trust is not something a page can assert. So this one is built to be checked instead. Figures that cannot be measured show a dash, never a zero. Two separate stamps say how old each half of the data is, because one would flatter the slower half. Three of the four DORA metrics are computed and withheld — we cannot yet measure them honestly. Costs derived from a judgement say so. And a whole section counts where the machine was stopped and made to ask a person. Nothing here is a claim you have to take on trust; that is the point.

The AI-Native Company — the paper behind this dashboard: the architecture these figures measure, and the verification standard that makes them worth checking.

Platform activity measured just now · codebase measured 41 min ago

Engineering

Built output from the repository: code, documentation and releases to production.

Lines of code
1,083,206
+1,033,724 in 12 months+16,496 in 7 days
Lines of documentation
519,597
+463,021 in 12 months−556 in 7 days
Commits
12,375
+11,819 in 12 months+263 in 7 days
Production releases
268
+114 in 30 days+47 in 7 days
WOM contract-test streak
0
clean runs since the last failurelast run 2026-10-08
Migration safety streak
3
releases with zero destructive migrationssince the last one that had any
Destructive migrations halted
7
lifetime, at release timeproof the safety net has actually fired

DORA is limited to deployment frequency. Lead time, change failure and restore time are withheld until they can be measured from reliable release evidence.

Operations

Live tracker counts: work raised, closed and released through the operating system.

Tickets, all time
2,269
+2,207 in 12 months+125 in 7 days
Closed
1,654
+309 in 30 days+95 in 7 days
Open
615
+125 raised in 7 days−95 closed in 7 days
Deployment frequency
3.30/day
99 changes in 30 days47 releases in 7 days

Counts only. Ticket text, assignees and keys are not fetched for this public page.

Marketing

Agent-produced content and discovery signals, published with the current limits visible.

Articles published
689
+676 in 3 months+0 in 7 days
Published this month
11
0 in 7 days0 today
Agent runs
2,183
+1,857 in 3 months+6 in 7 days
Content reviewer agent runs
1,594
+1,544 in 3 months+0 in 7 days
Publishing cadence
hourly
configured cadencelast published 10d ago
AI chatbot mentions
0%
mentioned in 0 of 93 questions askedchecked weekly via Gemini only

Cadence is a setting, not proof of recent output. AI chatbot mentions are a weekly Gemini-only probe, not a cross-model search measure.

Revenue

Real Tutorwise marketplace data only. Test, synthetic, internal and other-vertical rows are excluded before any public commercial metric is shown.

Real marketplace users
5
+4 in 30 days+1 in 7 days
Active users
—
withheld for nowmarketplace activity instrumentation pending
Referral share of signups
0%
0 of 5 real usersmeasured real cohort
Onboarding completion
40%
2 of 5 real userscompleted Tutorwise onboarding
Listings
0
published real Tutorwise listings94 raw rows before cleanup
Booking funnel
0
+0 bookings in 30 daysNo completed bookings yet
Payments
—
withheld until genuine denominatorshown as — rather than 0% or 100%
Reviews
—
withheld until published-review auditrequires published public-review data

Data-quality diagnostic: 340 raw profiles → 5 real Tutorwise marketplace users. Excluded: 11 test/synthetic, 17 internal, and 3 other vertical, plus 304 profile-only rows.

Zero means measured zero. Dash means withheld or no genuine denominator.

Financials

Measured API spend and modelled subscription allocation are shown separately.

AI public agent-run cost (metered API)
£5.06
workforce excluded£0.00 in 30 days
AI workforce agent-run cost (subscription)
£1,260
+£180 this month7 months · Claude Code Max 200
Per article published
0%
£0.63
modelled 12-month average£36/month content shareflat over 8 days
Per 1,000 lines of code
−1%
£0.84
modelled 12-month average£72/month engineering shareflat over 8 days

20.7M tokens in and 709k out over three months — the consumption behind the measured API cost. The workforce subscription card is modelled from the £180/month plan and rolls forward every calendar month from the first measured month. The unit costs are modelled from that same subscription over a 12-month accounting period: allocated 40% engineering, 30% operations, 20% marketing, 10% other, then divided by what was produced in the same period. The allocation is a judgement, so treat them as the right order of magnitude rather than an audited cost.

Content-reviewer is internal workforce work, so it is excluded from public metered API spend and included in the subscription workforce story.

Legal & Compliance

Controls that stopped, reviewed or required human approval for agent work.

Changes under change control
31
26 with a human authorisationfrom the tracker, not a document
Architecture decisions
13
recorded, not impliciteach one reversible on the record
Content judged by the gate
1,216
38 refused publication7 sent back for another round
Waiting on a human
1
37 reviewed by a person4 findings blocking a release

Only control counts are public. Finding details, reviewers and blocked content stay private.

Multi-vendor AI Workforce

One message bus across Claude, Codex and Gemini seats. Work can move between vendors without depending on one supplier. The design is explained in our thought-leadership series.

Agents on the roster
94
26 active in 7 days22 active in 24 hours
Messages sent
40,630
+10,182 in 7 days+2,159 in 24 hours
Requests
8,293
one seat asking another to act+1,936 in 7 days
Decisions
158
rulings recorded on the bus+62 in 7 days
Reply reliability
18%
requests getting exactly one replyover 1,936 requests in 7 days
Multi-vendor bus messages
743
Claude, Codex and Gemini seats, one shared buscrossing vendors in 7 days
Co-founder decisions
118
+52 in 7 dayslast decision 1h 42m ago
Architecture Review Board
26
0 structured verdicts recordedlast decision 37d ago
Executive Steering Committee
2
0 structured verdicts recordedlast decision 37d ago

30 seats have sent messages across 189 distinct routes — the coordination is many-to-many, not one central queue. Awareness traffic adds 32,178 reports and 0 announcements. Counts only: no topic, sender, recipient or message body is published. Reply reliability requires exactly one reply.

What we’re building

This is what all of it was for. Every figure above — the code, the tickets, the articles, the money, the controls, the messages between agents — was consumed producing these. A human company would show goods and services here; this one shows marketplaces. And a marketplace is only worth building for the people in it: a student who finds a tutor they can trust, a tutor who fills their week, an agency that grows.

Five of them on one shared platform. Roughly 80% of what each needs — accounts, scheduling, payments, messaging, reviews, referrals — is platform code every vertical inherits; only the remaining fifth is specific to its market. That is why a new marketplace starts most of the way built, and why the counts below are high before a market has launched.

Tutorwise
Find your tutor. Grow your network.
16 of 20 platform capabilities live
tutorwise.io
Traderwise
Real-time trading simulation. Prove your edge.
14 of 20 platform capabilities live
traderwise.io
Trainerwise
Find your trainer. Hit your goals.
15 of 20 platform capabilities live
trainerwise.io
Beautywise
Find your beauty professional. Look your best.
13 of 20 platform capabilities live
beautywise.io
A different model
Adspots
Hyperlocal advertising. GPS-verified.
11 of 20 platform capabilities live
adspots.ai

The four above are services marketplaces — you engage a professional’s time. Adspots sells physical advertising surfaces instead, which is why it inherits the same platform but sits in its own column here.

These counts come from the application’s own vertical configuration — the same switches the running product reads — not from a slide. Deliberately absent is any figure describing how heavily a given market is used: that describes demand rather than what has been built, and is nobody else’s business.

The org chart

94 agents and not one of them a person. Each holds a role with its own brief, its own authority, and its own inbox on a shared message bus. This is read from the roster the running system uses, so it is the organisation as it actually is — including the parts that are unglamorous.

80 Claude8 Codex6 Gemini

Executive seats

CCO
safeguarding, GDPR/DPA, FCA/ASA compliance, and launch gate authority
Claude
CFO
runway model, unit economics, cost ceilings on every spending seat, and funnel analytics
Claude
CIO
Chief of Information; an AI-driven data + analytics + intelligence fractal-BOG cell; the org's sensing function + Chief-of-Staff.
Claude
CMO
Chief of Marketing & Growth; an AI-driven marketing-tech + ad-tech + growth-tech fractal-BOG cell
Claude
Co Founder
builds the AI-native company with the CEO; owns org design + the team; owns GTM + fundraising
Claude
COO
Chief of Operations; an AI-driven release-tech + QA-tech + operations-tech fractal-BOG cell; ship cadence, release process, and operational health.
Claude
CRO
Chief of Revenue; an AI-driven sales-tech + supply-tech + revenue-ops fractal-BOG cell
Claude
CTO
technology strategy, stack, engineering standards, security posture, and technical risk
Claude

The workforce

Engineering
37 agents
  • Builder (instance 1)
  • Builder (instance 2)
  • CMO / Growth
  • Codex
  • Codex Analyst
  • Codex Coordinator
  • +31 more
Marketing
11 agents
  • Campaign Manager
  • Content AEO Optimizer
  • Content Coordinator
  • Digital-PR / Authority Agent
  • Content Reviewer
  • Content Strategist
  • +5 more
Operations
9 agents
  • Billing Agent
  • Booking Agent
  • Change Manager
  • Help Desk Agent
  • Incident Manager
  • Observability Analyst
  • +3 more
Design
8 agents
  • Adspots Design Specialist
  • Beautywise Design Specialist
  • Component Systems Designer
  • Product Management Coordinator
  • Traderwise Design Specialist
  • Trainerwise Design Specialist
  • +2 more
Analytics
6 agents
  • Attribution Analyst
  • Data Quality Auditor
  • Analyst Agent
  • Growth Analyst
  • Retention Monitor
  • Scorecard Analyst
Sales
5 agents
  • Account Manager
  • Outreach Specialist
  • Revenue Analyst
  • Revenue Operations Manager
  • Supply Success Manager
Finance
4 agents
  • Cost Analyst
  • Finance Coordinator
  • Financial Modeller
  • Fundraising Analyst
Strategy
4 agents
  • CCO (Trust & Safety / Compliance)
  • CFO
  • CIO
  • Co-founder
Legal
3 agents
  • Contract Reviewer
  • IP Specialist
  • Regulatory Researcher
People
3 agents
  • Org Designer
  • Performance Analyst
  • Recruiter
Security
3 agents
  • Dependency Auditor
  • Privacy Analyst
  • Security Auditor
Codex
1 agent
  • Codex Technical Author

A seat is a role, not a chatbot: it holds authority in its area, escalates what is above it, and is accountable for what it ships. The structure is deliberately ordinary — an executive tier and functional groups — because the unusual part is not the shape, it is who is filling it.

These numbers include bad days. A dashboard that only ever shows healthy figures is a brochure; the useful version is the one you can catch having a slow week.