> For the complete documentation index, see [llms.txt](https://docs.zerve.ai/zerve-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zerve.ai/zerve-docs/superagents/batches/ideation.md). # Ideation Brainstorm many distinct approaches, then rank them before committing to one. An **Ideation** batch generates many distinct ways of tackling a problem, then has them ranked, so the superagent can commit to the most promising ideas before spending budget building them. ## When it's used Use Ideation early, when the right approach isn't obvious. For example: * Brainstorming ways to hedge a portfolio's interest rate exposure * Generating candidate signals for a new factor * Exploring how to detect unusual trading patterns in a new dataset ## How it works 1. Several agents each propose one approach, written up briefly rather than built. 2. To keep the ideas varied, each can be given a different **angle** to work from. 3. Ideation deliberately generates more ideas than it needs, so weak or duplicate ones fall away. 4. [Judges](/zerve-docs/superagents/batches/how-judging-works.md) compare the ideas head to head and rank them. The top ideas often feed into another batch: an [Exploration](/zerve-docs/superagents/batches/exploration.md) to score them on real data, or a [Tournament](/zerve-docs/superagents/batches/tournament.md) to build and judge them. When ideation runs in several waves, what each wave learns is carried into the next, so later ideas build on earlier ones. ## What you see While it runs, the batch shows **Ideating…** and then **Judging…**. Its results view is the **ranking explorer**, showing how each idea ranked and how confident the ranking is. ## Example request > Before building anything, brainstorm at least fifteen ways to detect regime changes in our FX data, rank them, and tell me the top three. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.zerve.ai/zerve-docs/superagents/batches/ideation.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.