Depth Beats Breadth in AI
Dave Rogenmoser, CEO and co-founder of Jasper, on the generative AI opportunity
The core bet in AI writing is that depth beats breadth. Jasper won early by being narrowly useful for marketers, first on ad copy and then on long form blog posts, with product decisions pulled by a marketer community that told the team which workflows mattered most. In a market where many apps rent the same base models, the advantage comes from building the best workflow for a specific job, gathering feedback, and turning that into better outputs over time.
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Jasper’s first wedge was direct response marketing. It started as a tool for Facebook and Google ads, then expanded into a Google Docs like editor for blog posts after users pushed for that use case. By late 2022, 60% to 70% of users were using Jasper for blog writing, which shows how focus created a clear expansion path.
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This focus mattered because the app layer was already getting crowded. By 2022, dozens of text and image startups were renting the same model layer, so broad feature checklists were easy to copy. Jasper’s defense was workflow fit, community input, and feedback data from templates and ratings that could improve fine tuned outputs.
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The market later reinforced the need to go deeper. After ChatGPT hit prosumer AI writing tools, horizontal SMB copywriting got commoditized, and companies like Jasper and Copy.ai shifted toward enterprise use cases where AI is tied to a concrete team workflow and measurable ROI, not generic writing help.
The next phase favors AI products that act less like a general text box and more like a specialist coworker inside one team’s software. Jasper’s path forward is to keep using embedded surfaces like its extension and integrations to spread across apps, while staying narrow enough within each workflow to deliver output a company can actually use and trust.