Instead of trying to convert skeptics, AMP focuses exclusively on users already at the frontier of AI adoption. They believe that building for someone who doesn't know how to prompt well forces them to build simplistic features and fall behind the pace of innovation.
Related Insights
Many teams wrongly focus on the latest models and frameworks. True improvement comes from classic product development: talking to users, preparing better data, optimizing workflows, and writing better prompts.
In the fast-evolving AI space, Vercel's AISDK deliberately remained low-level. CTO Malte Ubl explains that because "we know absolutely nothing" about future AI app patterns, providing a flexible, minimal toolkit was superior to competitors' rigid, high-level frameworks that made incorrect assumptions about user needs.
To appeal to the "layperson" rather than tech early adopters, Comet's designers made the core browser experience familiar, like Google Chrome. This reduces cognitive load, allowing users to focus their limited learning bandwidth on the novel AI features, even if it disappoints power users expecting a radical redesign.
In the fast-paced world of AI, focusing only on the limitations of current models is a failing strategy. GitHub's CPO advises product teams to design for the future capabilities they anticipate. This ensures that when a more powerful model drops, the product experience can be rapidly upgraded to its full potential.
The history of AI tools shows that products launching with fewer restrictions to empower individual developers (e.g., Stable Diffusion) tend to capture mindshare and adoption faster than cautious, locked-down competitors (e.g., DALL-E). Early-stage velocity trumps enterprise-grade caution.
To avoid disrupting existing enterprise customers and being disrupted themselves, Sourcegraph launched a new brand, AMP. This freed them from Kodi's contracts, customer expectations, and release cycles, enabling a much faster, more radical development pace for their new coding agent.
Traditional software required deep vertical focus because building unique UIs for each use case was complex. AI agents solve this. Since the interface is primarily a prompt box, a company can serve a broad horizontal market from the beginning without the massive overhead of building distinct, vertical-specific product experiences.
To get mainstream users to adopt AI, you can't ask them to learn a new workflow. The key is to integrate AI capabilities directly into the tools and processes they already use. AI should augment their current job, not feel like a separate, new task they have to perform.
The AMP team is small and agile, bypassing traditional processes like code reviews to ship 15 times a day. They leverage Sourcegraph's customer trust, revenue, and platform teams (e.g., security), allowing the core team to focus purely on product velocity and radical innovation.
The AMP team believes that accommodating popular user requests like model choice or 'bring your own key' would slow their ability to innovate. They argue that their target users ultimately prefer a superior, opinionated product over peripheral features, even if they ask for them.