Figma's expansion into multiple products (FigJam, Slides) wasn't based on abstract strategy but on observing users pushing the main design tool to its limits for unintended use cases. Identifying these 'hacks' revealed validated market needs for dedicated products.

Kun Chen doesn't just use off-the-shelf agents; he builds his own tools like Lavish (visual planning) and 'no mistakes' (validation). This highlights a key trait of power users: identifying and solving personal workflow frictions with custom software instead of waiting for public solutions.

Intentionally create open-ended, flexible products. Observe how power users "abuse" them for unintended purposes. This "latent demand" reveals valuable, pre-validated opportunities for new features or products, as seen with Facebook's Marketplace and Dating features.

Major product opportunities are revealed by observing how customers use your product in unintended ways or "jump through hoops" to achieve a goal. For example, Anthropic noticed non-engineers struggling to use their coding tool, revealing the latent demand for CoWork, a knowledge-work assistant.

Simply building what users ask for can trap a product in old paradigms, like reinventing Photoshop's lasso tool for an AI context. A successful strategy involves staying slightly ahead of user adoption, introducing new capabilities that fundamentally change their workflow, and guiding them toward a more efficient future.

Users often develop multi-product workarounds for issues they don't even recognize as solvable problems. Identifying these subconscious behaviors reveals significant innovation opportunities that users themselves cannot articulate.

Exceptional AI content comes not from mastering one tool, but from orchestrating a workflow of specialized models for research, image generation, voice synthesis, and video creation. AI agent platforms automate this complex process, yielding results far beyond what a single tool can achieve.

Identify how users are already "hacking" your product for unintended purposes (e.g., using Facebook Groups for commerce), then build dedicated features to serve that existing intent. You can't make people do new things, but you can help them do what they already want to do more easily.

A meta-workflow is emerging where designers use AI prompts not just to build the prototype, but to build tools *within* it. Examples include creating live version pickers for stakeholders or generating a markdown file that lists and controls all component states, effectively prompting a custom handoff tool.