I’ve been conducting a systematic evaluation of several AI assistants for their utility in pre-sales solution design and internal process brainstorming—two areas where my team heavily relies on rapid, divergent ideation. My initial hypothesis was that Claude.ai, with its praised verbosity and reasoning, would excel. After a month of rigorous side-by-side testing against competitors like ChatGPT and Gemini, I have to concur with the thread title: Claude is, unfortunately, a subpar brainstorming partner. Its core failure mode is a tendency towards synthesis and rephrasing rather than genuine expansion or challenging ideation.
My testing methodology involved presenting each model with identical, complex seed ideas related to customer support workflows. For example:
* Seed Idea: "We want to reduce Tier 1 ticket volume by 30% using a new AI-powered self-service portal."
* Desired Output: A wide range of unconventional approaches—gamified knowledge bases, predictive FAQ generation from resolved tickets, proactive chat intervention on help pages, integration with community forums for peer support, etc.
Claude's response pattern consistently followed this structure:
1. A polite affirmation of the goal.
2. A meticulous re-statement of the original seed idea, often breaking it down into its constituent parts.
3. A list of "suggestions" that were, in essence, slight variations on the core concept. Instead of "AI-powered self-service portal," I would receive "implement a smart FAQ chatbot," "create a dynamic knowledge base," and "use an AI to guide users through troubleshooting steps." These are semantically the same core idea, just rephrased.
4. A well-structured but ultimately safe summary.
The critical lack is in what I call **lateral ideation**. When prompted with "challenge my assumptions" or "give me five radically different alternatives," Claude defaults to refining the initial premise. It seems optimized for consolidating and clarifying existing information, not for the messy, generative, and sometimes contradictory process of early-stage brainstorming. In a pricing model comparison, this is akin to a tool that can only list the features you already know you want, rather than suggesting innovative bundling or cost structures you hadn't considered.
This has tangible implications for my work in support platform design. Brainstorming sessions need to generate novel approaches to omnichannel routing, SLA exception handling, or knowledge base article generation. A tool that simply rephrases my initial proposal doesn't advance the conversation. I've found it more effective to use Claude for the subsequent phase: taking a wild idea generated elsewhere and asking it to develop a structured implementation plan, assess risks, or draft documentation. Its strength is in depth, not breadth.
I'm curious if others in the community have observed this behavior and, more importantly, have developed prompting strategies to circumvent it. Have you found specific phrasings or iterative techniques that force Claude out of its rephrasing loop and into a more generative mode? Or is this a fundamental limitation of its underlying architecture compared to other models?
Support is a product, not a department.