Suggestions
Samantha Wong
General Partner, Blackbird Ventures | Kauffman Fellow Class 26. **Parental Leave Break**
Samantha Wong is the Co-Founder of Pory, a no-code platform for building internal tools and portals with Airtable.13 She founded Pory in May 2020 and is based in Melbourne, Victoria, Australia.1 Prior to founding Pory, Samantha worked as a Frontend Software Engineer for startups and as an iOS Mobile Engineer consulting for corporations.1
Samantha is also the Co-Founder of Shooting Unicorns, which she describes as a "playground" for housing her spontaneous ideas.1 Through Shooting Unicorns, she has been involved in various projects, including:
- Pory (2020)
- Cadence (First place in Square Hackathon, 2021)
- Porysays (Top 3 finalist in MongoDB World hackathon, 2019)
- Mobu (Top 3 projects in AWS AI Hackathon, 2018)
- Clearpath (Top 3 finalist in Open Innovation Competition on Accessibility, 2018)1
Since its inception in 2020, Pory has helped over 30,000 creators, founders, and operators create software solutions.3 The platform aims to help businesses collect and turn data into beautiful forms, websites, and apps without significant financial investment.23
Samantha is passionate about design and coding, stating that she is in her "happy place" where she gets to do both every day.1 Her goal with Pory is to break the code barrier and help businesses build and scale software more efficiently.3
Highlights
Thanks to Mahesh Muralidhar and the Phase One Ventures community who hosted me for a chat last week. It was the perfect antidote to a week stressing about SVB and the implications for our industry.
We ended the session with a thought-provoking discussion about generative AI and LLMs. I shared a few things I'm thinking about when assessing opportunities to invest in AI companies. This is by no means exhaustive. We're in the first innings and I'm keen to learn from others.
If you are a Kiwi founder interested in this space or actively building in this space, DM Dr Izzy Bigio who is pulling together a small community to meet in Auckland!
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Are they building a foundational model? If so, why do I believe they have a reason to win vs Open AI, Deep Mind, Anthropic etc? Not just from an underlying technology perspective, but also from a capital raising, cost of compute and talent acquisition perspective.
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If they're not building a foundational model and instead are built on other models, you have to assume they are one of many startups attacking the same problem. Where is their long-term (or even short-term) defensibility going to come from? Do they currently have ML capability in their team, and do they have a right to win in the talent wars for AI engineers?
2a) Are they acquiring new and/or unique training data? Is there a land-grab dynamic at play for this data? Does this team have an advantage in distribution?
2b) Is the product regulated in any way? Is it likely that a regulator will accept model outputs trained in this way?
2c) What is gross profit margin of the product today and what might they be in the future if access to foundational models more accurately reflect the cost of running them?
- If you assume AI adoption scales exponentially, how does that change the structure of the market for the product? Is it an increasing or decreasing TAM?
