Phase 1: Agentic Workforce
Businesses hire agents as workers. Skill unbundles from time, and output stops being capped by headcount.
Businesses hire agents as workers, not copilots. Skill unbundles from time, and output stops being capped by headcount.
The shift
For all of history, buying someone's skill meant buying their time. Agents break that link.
Two things change here. First, businesses stop renting a person's hours to get their skill and start renting the skill itself, as an agent: available on demand, in parallel, at any hour, for marginal cost. You hire the coding, the research, or the analysis directly, without hiring the forty-hour week it used to come bundled with.
Second, the unit of work changes. Today you prompt a tool and stitch the pieces together yourself, so the prompt is the unit of work. As agents take on whole jobs, the prompt stops being the unit and the work becomes the unit: you hand over an outcome to own, not an instruction to run. The brain that decides what is worth doing stays human; the skill that executes it becomes runtime.
What a business wants
Businesses do not want to manage tokens or prompts. They want to state intent and get an outcome, the same way they delegate to a team today, only faster and cheaper.
A business does not buy effort, it buys outcomes, and it wants them at a fixed, predictable cost. Tokens and prompts are the wrong unit for that: they price the machinery rather than the result, and they swing with how verbose a model happens to be. So as the work itself becomes the unit, pricing follows. Agents get charged by the unit of work delivered, a resolved ticket, a reviewed contract, a shipped report, the way you scope a contractor, not the way you read a utility meter. That gives a business the efficiency and predictability it already expects from every other line item. XO does not provide the agents or the models; you bring your own. XO only meters the token spend against each outcome so the price stays tied to the result, not the machinery.
What is a unit of work
A unit of work is a complete, verifiable outcome an agent owns end to end, not a step along the way.
A prompt is an instruction and a token is a billing artifact, but a unit of work is the job itself. What makes something a unit of work is three things: a clear definition of done, a result you can actually check, and a scope small enough for one owner to be accountable for. If you can describe what finished and correct looks like, you can hand it to an agent, verify it when it comes back, and price it as one item. That is the unit businesses plan, budget, and pay against, which is why it becomes the natural thing to charge for.
How it gets measured
No new accounting: budget the outcome, verify the state change, meter the spend. The gap is your efficiency.
You scope an outcome the way you scope a ticket or brief a contractor: describe the end state, assign a budget. The agent runs against it; when it reports done, the environment compares the world before against the world after and meters what the AI actually spent, on the model you bring. Verified delivery against a human-set budget is what mints quirqs, the unit this whole phase is priced in; the full arithmetic lives in how to calculate a quirq. In the product, each XO session is one intent with this machinery on by default, so cost and outcome are tracked per intent rather than smeared across a token bill.
Who does what
- Execute the skill
- Work in parallel, any hour
- Produce the first pass at marginal cost
- Frame the problem
- Decide what good looks like
- Own the outcome
In plain terms
Phase 1 is the near-term shift already underway. For all of history, hiring a skill meant renting a person's hours, so expert work was capped by how many people you could afford and how many hours were in their day. Agents package the skill without the hours: a coding agent, a research agent, or an ops agent delivers practiced craft on demand, in parallel, at marginal cost. The work that was never economical to staff, the analysis a small business skipped or the research a solo founder could not justify, becomes affordable. That is why this expands the amount of knowledge work rather than shrinking it.
What does not change is the need for a human in the loop. Someone still has to decide which problem is worth solving, what a good result looks like, and who is accountable when it ships. Phase 1 moves people from doing the work to directing it, and XO's job is to make an agent safe to direct in production: a known identity, a spending limit, a full record of what it did, and the option to run it inside your own cloud.
The honest signal that this is real, rather than a demo, is how often a human has to step in to fix or redo an agent's output. When that intervention rate keeps falling, agents are genuinely doing the work. When it stays high, they are still just tools with a chat box.
Next: the unit of work, the contract that replaces the prompt.