The long version, written to be forwarded. Send it to your IT director, your CFO, or whoever runs your next leadership meeting.
You write a job description. That one document produces one accountable agent in a seat on your org chart, and it earns its role the way a person would:
Underneath every hire sit multiple other sub-agents and one shared company memory, built and maintained by us, read and written by your people and your agents alike, so each new agent hired ramps up faster and cheaper than the last. If a hire does not work out, one action offboards it, and everything it learned stays in the memory.
That is the entire model: two primitives, the job description and the company memory built from your company's knowledge. The rest of this memo is detail.
Under that one hire, our system automatically breaks the job into atomic tasks and spawns the agents, automations, and integrations each one needs. You do not manage any of it. You have one agent who does the work and answers for it. And the system tracks every piece of feedback and every interaction, automatically updating both the company memory and the agent's capabilities.
Everyone in your company wants AI. Nobody can tell you how to actually do it. And somehow, that became your problem.
So far, "doing AI" at most mid-market companies has looked the same: a pilot that demoed well and then quietly stalled, because nobody owned it. An AI task force that met four times and produced a memo. Tool licenses scattered across the org, used mostly by the youngest people in the building. And a board that reads about AI every morning and looks at you every quarter.
None of that failed because your team is bad at this. It failed because "adopt AI" is not a plan. It is a mood. A plan has a name, a role, a start date, and someone accountable. You already run an entire company on plans shaped exactly like that. They are called hires.
| The tool way (the one that keeps failing) | The hiring way (the one your company already runs) |
|---|---|
| Starts with a product demo | Starts with a job description |
| Lives in a browser tab, outside the org | Placed in the org chart, on a real team, with real boundaries |
| Knows nothing about your company on day one, and day ninety | Onboards like a new hire: reads the pack, gets interviewed, asks questions back |
| No manager, no team, no accountability | Shadows the team, then earns responsibility through probation |
| When the champion leaves, it dies | Owned by the org: provisioned by IT like an employee, offboardable like one |
| Every learning evaporates when the contract ends | Everything it learns stays with your company |
Your company has spent decades getting good at exactly one way of adding capable workers. It is not procurement. It is hiring. We didn't change it. We just changed who shows up.
And notice what we did not do: recreate your processes to fit AI. We make AI work inside the processes you already run, and we upgrade them into a company memory that keeps updating, usable by your people and your agents alike. That is why the tool way knows nothing on day one and day ninety, and our hire on day ninety looks nothing like day one.
If you can write a job description, you can make this hire. What follows is the full lifecycle, the same one you already run for people, and it comes with the property every manager actually wants: when the work is wrong, escalation ends at one seat, one name, one place to point.
You write the job description. That is the whole input.The same JD you would post for a human: responsibilities, boundaries, who it reports to, what success looks like. AP specialist, sales ops analyst, support tier one; if you have hired for the seat before, the posting you already have is the input. If it is good enough to hire a person with, it is good enough to hire this.
It takes a seat in your org chart, at two levels.The whole organization and its own team: an accounting agent sits inside finance, under a named manager, beside named teammates. From the job descriptions around it, it knows who it reports to, who it hands work to, and what it never touches. So when work arrives that belongs to a colleague, it hands the work over instead of guessing, because your JDs, not our defaults, drew that line.
It onboards like a person. Actually onboards.It reads the same onboarding pack a new hire gets, sits for an interview, and asks questions back, the questions a sharp new hire would ask. Then it shadows real work, recorded sessions and live calls, watching how your team actually operates. Shadowing is read-only by construction, enforced by the scoped account IT provisioned rather than by a promise from us: it is learning your company, not operating in it.
Your team holds the gate.For two weeks the agent works in the open, asking questions in the channel your team picked, and your team reviews every piece of its output before anything counts. Responsibility arrives in increments, draft first, then send with review, then close the loop alone, and your people, the ones who know the job, grant each increment or hold it back. Nothing goes live on our say-so; it goes live on theirs.
Every question, correction, and handoff lands in the company memory.There is no separate training phase: from the first day of shadowing, everything the agent learns is written into the shared company memory we build and maintain for you (primitive two, below). By the end of probation, that memory holds a working record of the role itself, not just the agent in it. The job description got you the agent; the memory is what the next one plugs into.
If it is not working, you offboard it.The exit is the same motion IT uses for a departing employee: revoke the scoped account, one action, done. And here is the part no failed pilot ever gave you: because the memory recorded the role and not just the agent, everything it learned about your processes stays with your company, documented and readable. Even the exit leaves you better off than you started.
| Phase | What happens |
|---|---|
| Before day one | Job description written. Seat in the org chart, boundaries drawn by the JDs around it. |
| Week 1 · Learn | Reads the onboarding pack. Interviewed, asks questions back. Shadows real work, touches nothing. |
| Weeks 2 and 3 · The two-week probation | Works under review, asking questions in the open. Your team grants each increment of responsibility and signs off before anything counts. |
| Ongoing · Compound | Everything learned lands in the company memory. Each new JD plugs into everything already learned and onboards faster than the last. |
This is the slide you show the board. On the call, we fill it in for your org.
IT grants the agent the same access the human in that role would get. No more, no less. There is no shadow integration, no all-access API key, no vendor backdoor: the scoped account from step 03 is the only door it has, and your IT holds the key through every step of the lifecycle you just read. When your security lead asks "what can it touch," the answer is a sentence: exactly what the person in that seat could touch, and the permission list is one your IT pulls from their own console, not one we compile for you.
"Company memory" can mean anything, so here is what this one actually holds:
That is the record every hire, human or agent, plugs into on day one.
Three jobs make that record real. All three are ours.
Your data goes in first.
The hire pulls out what your data never held.
And we do not let it go stale.
You can read what it believes. Human-readable is not a feature adjective; it is how you stay in charge. Anyone on your team can open the memory and read, in plain language, what an agent believes about your company: who approves discounts, which entity that vendor bills under, where the handoff goes. If a line is wrong, your team fixes the record once, and every agent running on it is corrected at once. A wrong belief here is not a support ticket. It is an edit.
That one readable record is also the entire management surface. The moment a vendor hands you a dashboard of twelve bots to orchestrate, they have handed you a second job. You hired to remove work, not to add a control room. Here you manage what you already know how to manage: a job description per seat, one record of how the company runs, and a team that holds the gate.
This is why hires compound. It bears repeating, because it is the whole point: your second job description inherits everything the first agent learned. Your fifth onboards in days, because the company has already explained itself. Several job descriptions, on one maintained memory, are not several tools. They are a workforce that compounds.
And at exit, in either direction. What an agent learns was never stored in the agent; it was written into the record of the role. So retiring one hire costs you nothing it learned, and leaving us does not either: the memory is yours, in plain language your team can read without us in the room. A vendor whose knowledge only works inside their own system has taken something from you. This one is built so it cannot. Software you rent. A memory you own.
Written to be pasted into a security review.
Tools depreciate. Hires compound.
"We are not running scattered experiments. We are making accountable AI hires, starting with one role, with a defined onboarding plan, probation criteria, and IT-controlled access. What each agent learns compounds and stays with us."
"Nobody is being replaced by a chatbot. This thing onboards under your supervision, asks you questions, and does not touch real work until you sign off. You are the manager. It is the new hire."
Most AI plans die because they only work in one of those two rooms. This one is the same plan in both.
We are seasoned operators who built and exited infrastructure start-ups, were in the first 50 at Snowflake, built data-cloud infrastructure at enterprise scale, and trained foundational models. We have spent careers making data systems reliable enough for other people's production workloads, and the hiring model reflects that experience: probation, shadowing, and supervised work are how you deploy technology that matters, without betting the company on a demo.
We are early, and we would rather earn your trust than borrow it, so you will not find borrowed logos or invented ROI here. What you will find is a design-partner cohort deliberately kept small: every company in it gets our senior team working alongside theirs, through the first hire and past it.
You have just read the whole model. The call is where it stops being a memo and becomes a dated plan for one role in your org. The agenda, as we run it:
You describe one role you are stretched on. If you pasted a job description below, we arrive with it already mapped: the seat, the boundaries, the increments your team would grant.
Minutes 9 to 16 · The planWe walk the lifecycle against your org, specifically: what it shadows first, the access IT grants it, the teammate who holds the gate, and what has to be true by the end of week two.
Minutes 17 to 20 · The verdictA straight answer on fit, on the call, not in a follow-up. Either way, the one-page hiring plan is yours.
The standard we commit to for every probation: every output reviewed by a named teammate before it counts, zero actions your team did not grant first, and a written go/no-go your team signs inside two weeks.
You will hear the design-partner terms before the call ends. Plain numbers, no slide deck.
Lock in the time while it is.
A founder confirms it, or proposes another.
You bring the first: one job description for a role you are stretched on. We show you how the second, a company memory your team can read and own, makes this the last hire you explain from scratch. Twenty minutes with a founder, and a hiring plan you keep either way.
A founder confirms your time, or proposes another. Small cohort: we book only the conversations we can staff properly.