Agent systems / Explore the architecture
WinDAGs.ai
Find specialist AI skills and connect tasks into clear graph-based plans, giving agents focused knowledge and a useful starting point.
Made for
For people building with AI agents who want to choose useful expertise, understand dependencies, and see which parts of a project can move together or need an earlier decision.
Specialist skill discovery
A task can call for several kinds of judgment. Skill matching helps make those needs explicit instead of asking a general agent to improvise every method.
Start here
Describe the work you are trying to accomplish. The useful starting point is the task and its constraints, rather than a collection of agents looking for jobs.
Explore the live planning demo, specialist-skill approach, and published scenarios. The walkthrough shows an interactive graph replay, including parallel work and the moments that need a person’s input.
Availability
Explore the architecture
How it works and what’s inside
Made for
For people building with AI agents who want to choose useful expertise, understand dependencies, and see which parts of a project can move together or need an earlier decision.
A large task becomes more manageable when the right expertise meets a clear plan. WinDAGs combines specialist skills with graph-based planning, making the structure of agent work visible before a single confident answer hides the complexity.
How it works
Workflow
Start with the problem
Describe the work you are trying to accomplish. The useful starting point is the task and its constraints, rather than a collection of agents looking for jobs.
Match expertise to the work
Find specialist skills that give the task a more informed approach. Connect those methods to the steps where they can actually help.
Follow the graph
Read the dependencies, parallel branches, and decision points as a plan you can inspect. The public demo makes that structure tangible through an animated replay.
Inside WinDAGs.ai
Features
Specialist skill discovery
A task can call for several kinds of judgment. Skill matching helps make those needs explicit instead of asking a general agent to improvise every method.
Dependency-aware planning
A directed graph shows which work unlocks something else, making sequencing and opportunities for parallel progress easier to discuss.
An explorable demonstration
The published scenarios show graph progression and human-input moments, giving the architecture a concrete visual explanation without requiring a live agent run.
Explore the live planning demo, specialist-skill approach, and published scenarios. The walkthrough shows an interactive graph replay, including parallel work and the moments that need a person’s input.
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