One person startup # One person thinks. Hundreds do the work. fleeTau is conceived, programmed, deployed and promoted by a single founder. The roles a whole department is usually hired for are performed by hundreds of AI agents. The human stays where a decision costs money: task setting and acceptance. [Talk about investment](https://fleetau.com/#talk) [See the product](https://fleetau.com/en/) The product runs in production. Below — exactly what, and on what. Founder and strategist What we build, what matters more, and which finished work to accept. 1 person — the only one who decides hundreds of agents — all the work except decisions - **Development** — code · migrations · tests · review · layout · deployment - **Data** — analytics · reports · payment reconciliation · exports - **Customers** — tech support · consulting · onboarding · training - **Market** — SEO · copy · translations · mailings · social media Team ## Ten roles. One hire. On the left — how a product of this size is usually staffed. On the right — how it is staffed here. Not a single line is skipped: all the work gets done, only the executor changes. Role Usually At fleeTau Backend · Go 2–3 engineers agents · acceptance Frontend · React 2 engineers agents · acceptance Infrastructure and deployment 1 DevOps agents · acceptance Data schema and migrations 1 engineer agents · acceptance Testing 1–2 QA agents · acceptance Code review the whole team’s time agents · acceptance Design system and layout 1 designer agents · acceptance Copy, documentation, SEO 1 writer agents · acceptance Product analytics 1 analyst agents · acceptance Fleet support and onboarding 1–2 operators agents · acceptance Total 12–15 people **1 person** The savings are not the point. The point is that between “decided” and “live in production” there are no approvals and no context handoffs left: it is the same person. Loop ## The company runs on the same loop as the product We do not “apply AI” — we run the company with it, and we sell fleets exactly the same loop. The product is proven on ourselves before any customer. 01 ### The agent proposes Company Breaks down the task, writes code, migrations, tests and copy, and presents the finished solution as a whole. Product Sees idle time, an overdue payment, an expiring insurance policy — and proposes an action with the amount. 02 ### The human confirms Company The founder accepts or rejects. The decision stays with him — and only the decision. Product The fleet owner confirms from the phone with a single tap. The decision stays with them. 03 ### The system executes Company The pipeline builds, deploys, and verifies that the service answers from production. Product A debit, a message to the driver, a charge to the partner, a record in the history. From this follows what usually has to be promised: speed. Between a hypothesis and a working feature there is no sprint and no task handoff — there is task setting and acceptance. In production ## Not a presentation — a working system Everything listed is answering requests right now — on a single machine in a Kazakhstan region, with pipeline deployment and one-command rollback. 7 Go services accounts, people, vehicles, rental, messages, payments and the gateway 4 web applications the site, the fleet workspace, the driver workspace, the partner workspace 22 database migrations embedded in the binary, applied under a lock at startup 1 744 car models a reference of 176 makes, a snapshot of the Kazakhstan market Perimeter 1 address Only the gateway has a public address. The other services have none at all. Isolation own database Each service has its own database and its own queue: another service’s data cannot be read even by accident. Hardware 2 vCPU 7 GB of memory, 20 GB of disk. That is what the entire infrastructure costs right now. Rollback 1 command Releases sit side by side; switching the symlink is instant. Economics ## Money goes into the market, not into headcount In a typical company a round turns into hiring, and the first months go to onboarding. Here the expense side does not grow with the workload — only the agent bill grows, and it is tied to work done, not to the month. Team 1 Infrastructure 1 machine Agents per work done Office, hiring, onboarding 0 Development spend ≈ one person’s salary An order of magnitude, not a report. Exact numbers — in a conversation, with a data export. ### What the money buys - **Cars in partner fleets.** The product is three-sided: the more cars under management, the denser the other two sides of the market. - **Expansion beyond Kazakhstan.** The product is multi-tenant and multilingual from day one; the next country is configuration and local payments, not new development. - **The payment loop.** Card data does not pass through our services, but connecting local providers is work that agents cannot speed up. - **Speed.** More agents per person — a shorter path from hypothesis to production. This is the only line item where money converts directly into time. Objections ## The four questions asked first ### One person is the entire risk That is why decisions do not live in one head. Contracts between services, role rules, breakdowns of expensive mistakes and the reasons behind every non-obvious choice are written down in the documentation repository — both the agents and the human read it. Whoever joins the project gets not access to people but a working system and its explanation. ### Agents write code nobody can maintain later Human acceptance is mandatory, and it is not the only line of defense. The database holds the boundaries: composite foreign keys, time-based exclusion constraints, uniqueness within a fleet. An agreement can be forgotten; a database constraint cannot. ### This cannot scale: support will hit the limit of one person Support is the first candidate for handing over to agents, and the product is already built for it: a messaging service, workspaces and a single event loop. A fleet asks right where it works. ### This is a one-off sprint, not a model A model is tested by speed over the long run, and it is measurable: every service reaches production through the pipeline, every deployment leaves a trace. We are ready to show that history in full, not a showcase. Conversation ## We will show the system, not slides Fifty minutes: live workspaces, the deployment pipeline, the decision repository, and how a task travels from statement to production in a single evening. Amount and terms come after — first it is worth making sure the model is real. [hello@fleetau.com](https://fleetau.com/mailto:hello@fleetau.com?subject=fleeTau%20—%20investment) [Back to the product](https://fleetau.com/en/) The founder answers. There is nobody else in this company to answer.