The operating model
From product knowledge
to a ready plan.
Start with the product you have. Bring in the ideas and feedback that show where it needs to go.
The first use case
Let Aiaea index your product.
This is the first use case we are building toward: give Aiaea your product’s documentation, source code, and site representation. Bring together how the product is described, how it is implemented, and how it is presented to the world.
Bring the knowledge together
Index documentation, code, and public-facing site content as a shared foundation for understanding the product. Preserve the sources so conclusions can be traced back to their context.
Ask questions and discuss ideas
Ask how the product works, how a proposed feature would fit, or what would need to change. For example: “How would this work for another customer group?” or “Which parts of the system would this idea affect?”
Add the customer’s perspective
Bring in feedback from existing users and potential clients. Put their needs alongside your ideas and the product’s current implementation so they can inform the same conversation.
Get a ready plan
Aiaea’s intended output is consolidated knowledge and a plan for making your product match the expressed requirements. See what needs to change, why it matters, and what can be improved right here and now.
The proposition is practical: turn the context you already have into actionable improvements, with AI analysis at the cost of tokens.
From the plan to working systems
The broader mission carries that knowledge into delivery. An AI harness connects models, tools, and execution; Aiaea’s aim is to give it the enterprise context it needs to carry work through.
Capture the intent
Start with a goal, a problem, a conversation, or operational feedback. Preserve the source so that later choices stay connected to the need they address.
Understand the architecture
Establish what exists and what evidence supports it. Connect business capabilities to applications, information, and technology. Describe the intended change separately from the current state.
Plan the change
Make dependencies, constraints, and expected outcomes explicit. The harness resolves evidence-based questions and brings decisions that require human intent to the person responsible.
Build and verify
AI carries out the implementation work and checks its results against the architectural intent. Code, tests, artifacts, and operational observations provide evidence of what was actually achieved.
Review, revise, and continue
Humans join for revision and decision making. The harness brings results and unresolved choices into that review, then carries the resulting direction into the next cycle of work.