While tools like Miro serve many use cases adequately, they are a "bad fit for all of them." The future of canvas tools lies in vertical-specific applications that go deeper on a single use case (e.g., pharmaceutical workflows, remote onboarding), offering a more powerful, tailored feature set that a generic tool cannot match.
Instead of being limited by off-the-shelf software, designers can dramatically accelerate their process by building bespoke tools. MDS used the AI tool V0 to create a custom bitmap icon builder, enabling rapid prototyping of a unique interactive element.
Vercel's Pranati Perry explains that tools like V0 occupy a new space between static design (Figma) and development. They enable designers and PMs to create interactive prototypes that better communicate intent, supplement PRDs, and explore dynamic states without requiring full engineering resources.
While generic AIs in tools like Notion are powerful, they struggle to identify the 'source of truth' in an infinite sea of documents. A purpose-built PM tool has a smaller, defined information domain, making it more effective and reliable for specialized tasks.
V0's success stemmed from its deliberate constraint to building Next.js apps with a specific UI library. This laser focus was 'liberating' for the team, allowing them to perfect the user experience and ship faster. It serves as a model for AI products competing against broad, general-purpose solutions.
Canva's success wasn't from targeting competitors but from identifying a real market gap through their first niche product (a yearbook tool). When users asked to use the tool for newsletters, it validated a larger, unsolved pain point that Canva then focused on exclusively.
The future of data analysis is conversational interfaces, but generic tools struggle. An AI must deeply understand the data's structure to be effective. Vertical-specific platforms (e.g., for marketing) have a huge advantage because they have pre-built connectors and an inherent understanding of the data model.
The current model of separate design files and codebases is inefficient. Future tools will enable designers to directly manipulate production code through a visual canvas, eliminating the handoff process and creating a single, shared source of truth for the entire team.
For marketing, resist the allure of all-in-one AI platforms. The best results currently come from a specialized stack of hyper-focused tools, each excelling at a single task like image generation or presentation creation. Combine their outputs for superior quality.
The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.