Product insights for technical founders.
Upskilling resources for experienced professionals.
No hype, just help.
Built the initial innovation and now it's time to find product-market fit? Get relevant discovery insights on nuanced market requirements, target personas, user journeys, and product operations tailored for startups.
ExploreLaunched a successful career and AI feels like chaotic nonsense? Cut through the noise with practical, non-hype resources to help you build confidence with modern tooling and techniques.
Discoverunconventional underdogs was founded on the belief that technical excellence, product insight, and helpful products don't have to be separate universes. We understand the complexity involved when building emerging, and potentially, disruptive products. We also have deep experience working with technical founders that are akin to unicorns, dragons, and sabertooth tigers. We are here to help and enable, not control.
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Unfortunately, many technical founders build amazing innovations that never find their market. Not because the innovation isn't good enough, but because the product insights came too late or never at all. Yet, identifying the right personas and applying product market fit methods addresses this challenge. We've seen this pattern from multiple angles: bringing emerging technologies to market at O'Reilly Media, building developer tools at NVIDIA, and working directly with founders navigating these waters.
We work with technical founders in machine learning, data science, data engineering, and infrastructure to bridge the gap between technical excellence and product success. This includes:
Technical founders are akin to unicorns, dragons, and sabertooth tigers. Frameworks for the sake of frameworks are not helpful, particularly when responsible for the care and support of highly unique intelligent entities with intense skills. unconventional underdogs acquire specific contextual insights on technologies, markets, target users, constraints, and potential tradeoffs that support nuanced complex product roadmap and engineering decisions.
Acquiring this relevant data and insights may mean structured user interviews to validate or invalidate assumptions. It might mean analyzing usage patterns to find unexpected use cases. The insights may broker intense internal collaborative conversations about prioritization. The work adapts to what is actually needed, not a restrictive spec or doctrine that may not be applicable for product development built on emerging technologies.
We specialize in working with founders who have deep technical expertise in:
If our approach aligns with yours and you'd like help with understanding your market, your users, or your product strategy, contact us.
The AI landscape is filled with supposed helpful resources that are inflated with hype, hallucinations, advertorials, arrogance, even worse ...toy examples that do not transfer, migrate, or are applicable in a professional setting. There's very little for experienced professionals who need practical guidance on what actually matters for their work. Professionals are under pressure to provide quality work. Professionals need to understand which tools are worth the time investment, which methods are transferable to multiple situations, and how to build confidence with "AI" technologies without drowning in noise.
In 2012, when data science was just emerging, our founder took the stance at O'Reilly Media that anyone could become a data scientist. The same principle applies now: AI tools and techniques are learnable, and your existing experience is an advantage, not a liability. You already know how to solve problems, how to evaluate solutions, and how to deliver value. Now we're providing bridges, tunnels, or access, to new knowledge, methods, and techniques. Ultimately, you decide what you do, and do not, need depending on your situation.
There is no such thing as an "AI expert". "AI" is domain that is constantly changing and increasing fluency within the domain helps professionals build skills to assess and navigate the emerging domain. As professionals build up fluency, it becomes easier to understand the limitations of "AI" and where it can actually help. unconventional underdogs resources are intended to provide professionals with knowledge that is additive and reinforces confidence.
We're not selling AI as a revolution. We are building practical bridges and tunnels from where you are now, to where these technologies, methods, and tools can help. Some AI applications help workflows. Others are overblown. Learning to tell the difference is part of the journey.
Interested in diving deeper on navigating AI without the hype? Contact us to be notified as resources become available.
Contact →unconventional underdogs was founded on the belief that technical excellence, product insight, and helpful products don't have to be separate universes. We understand the complexity involved when building emerging, and potentially, disruptive products. We also have deep experience working with technical founders that are akin to unicorns, dragons, and sabertooth tigers. We are here to help and enable, not control.
As the Data Editor at O'Reilly Media in 2012, our founder championed the idea that anyone could become a data scientist. Even today, there is still no single path. Our founder built technical resources to help onboard developers to new emerging data science, data engineering, and machine learning technologies. They also helped amplify emerging founders who would go on to build companies like Databricks. At NVIDIA, they launched an open source recommender systems framework with libraries that were designed to accelerate data scientists and ML engineers' workflows. Today, we provide product insights to startups with expert technical founders in machine learning, data science, data engineering, and infrastructure.