From: aidotengineer
Munir, CEO and co-founder of Porsche AI, shares insights from his journey as a founder of an AI startup, drawing on his previous product roles at Stripe, Google, and Amazon [00:00:03]. Porsche AI, launched in June last year, is an open-source SDK for building production agents with a focus on regulated industries [01:28:00]. This presentation aims to provide useful notes for those looking to start their own company in AI or those in a similar early stage [00:00:25].
User Problem Discovery in the AI Space
Discovering user problems in AI is significantly different from traditional product development [02:11:00]. Unlike conventional product spaces where user problems have a defined shape and adjacency to existing problems, the AI landscape presents a unique challenge [02:31:00].
The speaker uses a “Soulslike game” analogy to describe this initial phase, where nothing makes sense at first and users don’t truly know their problems [03:00:00].
“Users don’t really know what their problems are. They sort of know that they want to use AI and they know that there’s some opportunity there, but they don’t the user problems are almost like an emergent property of the space. They are not defined yet.” [03:25:00]
Additionally, what is possible and what the technology allows is changing very quickly [03:39:00]. This rapid evolution means that conventional three-month or six-month roadmaps are largely irrelevant [03:45:00]. Instead, the focus must be on making directional bets and iterating very fast by putting products out there and observing user reactions [03:52:00]. The anchor for development becomes hypothesis-driven, deliberate iteration [04:06:00].
Traditional tools like user storyboards and critical user journeys also become less applicable [04:21:00]. The experience is likened to the game No Man’s Sky, where the player creates their own narrative rather than following a defined mission [04:39:00]. This requires founders to help users overcome initial inertia and work with them to create narratives and anchor on a specific use case [04:51:00]. Once a use case is established, the development process gradually moves into more familiar territory, allowing for product refinement against defined problems [05:17:00].
Product Development Velocity in AI
The product development process in AI is described as highly gratifying due to its speed [06:01:00]. Unlike large organizations where multiple sign-offs are needed, an AI startup can go from an idea and a spec to testing and release in a matter of hours or days [06:21:00].
However, this velocity is not merely a “nice to have”; it is a “table stakes” requirement for survival in the AI space [06:52:00]. The speaker emphasizes that if a company cannot release quickly and effectively, they are out of the game [07:02:00].
The reason for this urgency is that opportunities, or “power-ups,” in the AI field emerge and disappear rapidly [07:07:00]. Examples include moments like MCP, agent-to-agent protocols, or diffusion models [07:20:00]. It is crucial to be able to react and build products that are at the forefront of these trends and technological breakthroughs to grow the brand and cement oneself within the developer and user communities [07:31:00].
Challenges in Awareness and Adoption
One of the toughest and most underestimated challenges is the lack of scaffolding for outreach, awareness, traffic, and adoption when starting from scratch [08:11:00]. The AI space is currently amidst “full-on hype and meme wars,” making it difficult to distinguish signal from noise [08:25:00].
Without the advantages of being attached to a larger brand, gaining visibility is like playing Crash Bandicoot without boosters or Mario Kart without power-ups [08:36:00]. Key learning points include:
- People follow people: Unlike launching a product at a big tech company where a tweet from leadership can generate instant awareness, startups must find credible industry voices and advocates to act as force multipliers [09:04:00].
- Finding allies: To overcome the lack of brand association and established channels, startups need to find allies [09:49:00]. These can be other startups at a similar stage or slightly ahead, who see synergy and are interested in cross-marketing, cross-selling, or even integrating product documentation to drive traffic to properties like websites or GitHub repos [09:51:00].
This phase represents a significant learning curve, emphasizing the need to continuously stretch and adapt to figure out solutions for brand visibility and product adoption [09:56:00].