For teams and agencies
Everyone on the team can generate now. Nobody has time to finish.
AI moved your bottleneck from first drafts to finishing: review, integration, verification, polish. After AI Work gives your team vetted experts on demand for exactly that work, with client-visible review and a record you can hand to anyone who asks how AI was used.
The team problem
More output, same number of people who can say "this is done".
When every team member can produce a draft in a minute, the capacity limit becomes the people who can finish and sign off. That work is skilled, uneven across the team, and usually invisible until it is late.
of committed code is now AI-generated or assisted, and developers expect that to reach 65% by 2027. Finishing capacity did not grow with it.
Sonar, 2026 State of Code Developer Survey. Sourceof developers say reviewing AI-generated code takes more effort than reviewing a human colleague's. Verification is the new bottleneck.
Sonar, 2026 State of Code Developer Survey. Sourcesecurity pass rate for AI-generated code, unchanged in two years. Coding-specific models are no safer than general ones (51% vs 52%).
Veracode, 2026 GenAI Code Security Report. SourceWhat teams get
Experts on demand. A bench you build. A record you keep.
Craft you do not have in-house
A marketing team with generated video needs an editor for a week, not a hire. A dev team with a generated admin UI needs a UX designer for two days. Post it.
Preferred experts
Rehire the people who did good work. Build a bench per craft. New jobs go to them first, with the same funded-and-approved protection.
Client-visible review
Agencies can add client reviewers to a job. Their decisions land on the record. "You approved this" becomes a fact with a timestamp.
One view of all after-AI work
Every open job across the team: what is posted, matched, in work, waiting on approval, shipped. The invisible backlog, visible.
Audit trail and disclosure
Who generated what, which expert changed what, who approved. When a client, a regulator or your own policy asks, the answer exists.
Templates
Save a definition of done that worked. The third AI-assisted landing page is posted in two minutes with the same criteria as the first.
Agencies
Charge for the finish. Show the work.
Clients increasingly ask two questions: "did you use AI?" and "then what am I paying for?" The record answers both. The path from generated concept to finished deliverable, with a named expert's changes, is the evidence of your judgement.
- Post overflow to vetted experts and keep the client relationship.
- Client reviewers see and approve on the record.
- Honest AI disclosure per deliverable, generated from the record.
Governance, lightly
Your AI policy, applied to every job automatically.
Most AI policies live in a PDF. Here the policy is the flow: provenance captured at Post, a definition of done before work, a named expert and a named approver, disclosure at Ship.
- Provenance by default. What was generated, by which tool, from which prompt.
- Human change is visible. The delta between AI output and shipped result is the record of expert work.
- Approval is attributable. A person, a time, a reason.
- Team billing. One account, many requesters, consolidated invoices. Details on the pricing page.
Give your team a bench for the work after AI.
Start with one job. Add the people who touch it. Build your preferred experts as you go.