AI AGENTS

Run a project with Project Autopilot

Turn project evidence into a validated delivery plan, safe autonomous actions and owner-controlled decisions.

18 minFor project owners and delivery leadsUpdated July 19, 2026

One governed control loop for the whole project

Project Autopilot reads the project's authorized source evidence and produces one coherent delivery plan. It compares the brief and roadmap with the current team, tasks, dependencies, acceptance criteria, cadence, hours, costs and delivery signals instead of reacting to one isolated message.

It does not replace the project owner. It prepares evidence-based options, applies only validated low-risk work allowed by the saved rules and keeps team, budget, deadline, client commitment and invoice decisions behind explicit approval.

Agent Center2 projects · 3 agents

Live

Agent objectsDigital PM TwinSprint AgentBilling Agent

Product launch2 active agents

PM TwinActive

PlanningPaused

Animated connections mean active work; paused connections remain visible and still.

Project Autopilot and PM Twin have different responsibilities

Agent	Owns	Typical output
Project Autopilot	Delivery structure and governed change	A validated roadmap, missing tasks, team recommendation, quality findings and approval-ready decisions
Digital PM Twin	Ongoing attention and communication	Targeted status questions, follow-ups, owner summaries and client-safe updates
Project owner	Consequential authority	Approval or rejection of team, money, timing, client promise and invoice changes

What the review uses

Evidence	What Autopilot checks
Brief and project source	Outcomes, constraints, non-negotiable requirements and missing context
Architect roadmap	Phases, concrete tasks, dates, dependencies, roles and acceptance criteria
Project Workspace	Actual task state, blockers, overdue work, assignment and completion evidence
Teams and profiles	Role coverage, verified capabilities, availability, collaboration evidence and capacity risk
Delivery policy	Weekly, two-week, monthly or continuous cadence plus time, cost, billing and invoice capabilities
Analytics and Team Pulse	Recent delivery movement, workload pressure and collaboration conditions
Commercial records	Budget boundary, tracked hours and relevant cost signals when the project enables them

Choose the autonomy level deliberately

Mode	Autopilot may do	Owner remains responsible for
Draft	Analyze evidence and prepare a complete plan	Approving every proposed action
Managed	Create missing tasks only after deterministic validation against saved quality gates	All consequential project changes
Within limits	Operate inside saved capabilities, variance and deadline boundaries	Every category marked Always ask approval

Review decisions as alternatives, not yes-or-no prompts

1
Read the reason
The decision card explains the observed project condition and why owner attention is required.
2
Inspect evidence
Check the concrete tasks, dates, role gaps, hours or commercial boundary that support the recommendation.
3
Compare options
Each option states its operational impact. The recommended option is identified, but it is not applied merely because the model prefers it.
4
Choose or dismiss
Your decision is stored in the project run history. The next review incorporates the selected direction and avoids presenting the same unresolved choice as new work.
5
Verify the result
Open Project Architect, Teams Canvas or Workspace from the review when you need to inspect the changed object in its native tool.

Quality gates run after AI planning

INSIDE COLLTY

Model reasoning plus deterministic validation

The model proposes a structured plan, but server-side rules decide whether it is complete enough to apply. The runtime checks the saved project-agent state again immediately before execution and stores a fingerprinted run trace for audit and later evaluation.

Missing acceptance criteria, dependencies or role coverage can block application when those gates are enabled.The agent cannot invent a specialist profile or silently attach a team; team recommendations use the shared profile-backed assembly engine.A material source or project-state change triggers a new review; unchanged evidence does not continuously consume model requests.Provider usage, retries and background runs are attributed to the responsible account.Later runs compare blocked, overdue, closed-task and Team Pulse movement so outcomes can improve evaluation without treating every correlation as proof.

Configure the first run

1
Connect Project Autopilot
In Agent Center, select the project, add Project Autopilot and open its control panel.
2
Select autonomy and rhythm
Start with Managed and Manual or Workdays until the project evidence and approval boundaries are stable.
3
Choose the team source
Use My people, Saved teams, External or Best fit according to who may be considered for this project.
4
Set approval boundaries
Keep team, budget, deadline, client commitment and invoice changes selected unless governance for the project explicitly permits otherwise.
5
Save operating rules
The visible controls are only a draft until the panel confirms Saved.
6
Run the review
Read quality findings first, then resolve decision cards or apply a validated task plan.

If Autopilot does not apply a plan

Paused or detached agents do not run, even when an old plan is visible.
Unsaved operating rules do not control the server runtime.
A quality-gate failure intentionally blocks task creation; correct the source evidence or change the gate deliberately.
Team, budget, deadline, client commitment and invoice changes wait for owner approval by default.
A project without enough source evidence should return a bounded request for missing information rather than fabricated detail.
Smart Console shows new owner decisions, blocked reviews and safe task plans once; open Agent Center for the full evidence.

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