aiagent.app vs win.sh: Company Workspace or Autonomous Loop
aiagent.app exposes a visual company workspace. win.sh runs a continuous business loop governed by authority, approvals, and budget.
Founder, Task Machine
Low-touch agent operations can fail in two directions. A founder can spend the day configuring the system that was supposed to save time, or review a completed action too late to prevent the mistake. The product's main control surface determines which risk it handles best.
aiagent.app exposes agents, squads, Workflows, knowledge, Board tickets, Inbox decisions, and Performance in one hosted workspace. win.sh watches the business continuously, acts within an authority matrix, and reports through Decisions and a morning brief. Both preserve context, schedule recurring work, gate risky actions, and retain evidence.
How do aiagent.app and win.sh compare?
| Dimension | aiagent.app | win.sh |
|---|---|---|
| Primary object | Company workspace containing agents, squads, workflows, Board, Inbox, context, and performance | Continuous monitoring and action loop across connected business systems |
| Human role | Build and equip agents, compose workflows, assign work, review Inbox items, and inspect performance | Set authority by work type, review decisions and briefs, and expand autonomy as rules improve |
| Recurring work | Scheduled Autopilots promote a defined agent and runbook into operations | The loop continually watches signals and proposes the next move |
| Process control | Visual graphs with agents, tools, branches, loops, waits, approvals, typed handoffs, and durable state | Authority matrix, approval gates, operating rules, and a hard monthly budget cap |
| Work surfaces | Chat, Board, Inbox, agent and workflow builders, Company Brain, Performance, Audit Log | Decisions, morning brief, connected context, receipts, and memory |
| Learning | Memory, skills, observations, scorecards, and reusable context | Approvals, edits, and rejections become operating rules |
| Commercial shape | Tiered hosted plans, per-member Teams offer, provider keys, and managed builds | Self-serve monthly operating budget with a hard cap and no revenue share |
aiagent.app is closer to a configurable company operating suite. win.sh is closer to a delegated operating loop.
Who does aiagent.app fit?
aiagent.app fits a team that wants to see and shape the system. An operator can define an agent's role and model, attach knowledge and connections, test it in Chat, put stable work into a visual Workflow, schedule it as an Autopilot, and route the resulting review into Inbox or Board. Squads provide another coordination layer when several specialists should delegate among themselves.
The public product guidance gives the operator clear boundaries. Agent judgment handles investigation, analysis, drafting, and triage. Workflow blocks handle required branches, waits, approvals, and outputs. Company Brain grounds work in connected records, while Performance and Audit Log make aggregate and individual activity inspectable.
That visibility creates setup work. The team still needs to design roles, context boundaries, workflows, approval points, and project ownership. aiagent.app offers templates and managed implementation, but self-serve customers are operating a system with many parts.
Who does win.sh fit?
win.sh fits a founder who wants fewer operating surfaces. The product watches connected accounts continuously, proposes actions, and acts inside authority levels set for each class of work. Sensitive areas such as spend, outreach, publishing, or changes can wait for approval. Decisions and a morning brief provide a compact review rhythm.
The budget and ownership rules are explicit. Customers keep their external accounts, set a monthly budget with a hard cap, and give no revenue share. As approvals and corrections become rules, the system can handle more work without requiring the founder to design a specialist roster or visual workflow for every case.
The tradeoff is retrospective control. A continuous loop is valuable because it runs before a person asks. Some ordinary decisions therefore happen before the morning review. Authority gates catch the known sensitive categories, but a team that needs to see an explicit process before client-facing work ships may prefer more structure.
How much of the operating model should you configure?
aiagent.app exposes the building blocks. That helps when different jobs need different agents, models, knowledge, tools, retry behavior, and workflow graphs. A support operation and a growth audit can share Company Brain while retaining separate controls and scorecards.
win.sh exposes the operating boundary. Its configuration covers what the system can decide, what must wait, and how much it can spend. A founder manages authority instead of constructing each internal mechanism.
aiagent.app can represent more of the process explicitly. win.sh can reduce the amount a founder must model. The right answer depends on whether configuration is a source of control or an operating burden.
Where does Task Machine fit?
Task Machine starts with a recurring job. A Playbook installs its Agents, Workflow, Skills, Documents, and setup values, while humans and Agents share the resulting Tasks and handoffs. Chat directs work, Inbox resolves judgment calls, and Tasks retain the detailed state.
Verifier nodes provide the control that matters in this comparison. A failed check stops the run and creates an Inbox decision with the evidence and resolution actions attached. This requires more operator involvement than win.sh's morning-brief rhythm and less free-form composition than aiagent.app's company builder.
Task Machine does not replace aiagent.app's company-level Performance view or win.sh's continuous monitoring loop. You keep 100% of your revenue, Task Machine takes no cut, and Task Machine never custodies your accounts.
How much system do you want to operate?
- Choose aiagent.app when you want a broad visual workspace for building agents and squads, composing durable workflows, organizing Board work, reviewing Inbox items, and inspecting aggregate performance.
- Choose win.sh when you want the company watched continuously, prefer an authority matrix and hard budget cap, and want a morning brief to be the main review rhythm.
- Choose Task Machine when recurring jobs should start from installable Playbooks, humans and Agents need to share accountable Tasks, and verifier failures must become explicit decisions.
For deeper product-specific tradeoffs, read Task Machine vs aiagent.app and Task Machine vs win.sh.