The Frontier

Tomasz Tunguz notes SpaceX's upcoming IPO is oversubscribed 2.5-3x, part of a wave with OpenAI and Anthropic whose combined IPO targets exceed the total of all IPOs in the previous decade.

Bending Spoons filed for an IPO; Tomasz Tunguz describes it as an AI holding company that buys legacy businesses and revives them with AI-native coding practices.

Paige Doherty's firm, Behind Genius Ventures, closed an $8.9 million second fund. She observes portfolio AI-native companies are achieving 10x to 100x+ annual revenue growth.

Paige Doherty states the average revenue for the 100 most recent billion-dollar-plus IPO companies is now between $300 and $500 million.

Tomasz Tunguz attributes soaring startup growth rates to corporate AI budgets being over 50% net new, and to labs signing massive contracts worth tens to hundreds of millions.

Michael Downey cites a company that raised a $4M seed round and reached a $120M revenue run rate, generating $750k monthly free cash flow.

Michael Downey observes founders are now raising late-stage venture less for hiring and offices, and more to fund massive token spend for AI inference.

Discussing multi-tranche funding rounds, Tomasz Tunguz estimates blended valuation structures appear in roughly 5% of deals today, a trend re-emerging from 2021.

Tomasz Tunguz explains applications now use model orchestration, using a high-cost model like Claude Fable to create skills, then running them locally to drastically cut token costs.

Paige Doherty describes vertical AI startups, like Mana which builds video-to-robotic-action models for factory floors, as having an advantage over incumbents due to native AI workflows.

Carta data shows US seed round valuations have surged, with the 95th percentile at $174M and the 90th at $94M, up from $66M and $50M in 2022.

Michael Downey argues the top 1-5% of seed deals may be underpriced, as outcomes are scaling faster and larger than ever, pointing to the SpaceX, OpenAI, and Anthropic IPO targets.

Sue Kim says Brilliant teaches problem solving over procedural knowledge, a more transferable skill than memorizing formulas. She says school math often fails when students encounter unfamiliar problems.

Brilliant’s new AI tutor Cooji launched last week and went viral with nearly 5 million views on X. Kim says the success shows consumer demand for AI that makes you think, not AI that replaces thinking.

Jason Calacanis says startup founders should ignore traditional TAM analysis for novel ideas, citing Airbnb and eBay as companies that induced entirely new markets. He says bad VC behavior often stems from an inability to assess non-existent markets.

Jason Calacanis explains his firm's process to improve founder feedback scores. He mandates that every first meeting ends with the investor repeating the founder's vision back to them to ensure understanding.

Brilliant’s AI tutor Cooji is Socratic, uses interactive canvases LLMs can read and write to, and gradually removes visual scaffolding as students reach mastery. The core pedagogy and mathematical correctness are deterministic systems built over seven years.

Sue Kim says Brilliant’s pricing is benchmarked against human tutors, not casual apps. The goal is a product that does 95% of a tutor's job for 30 dollars a month, a fraction of the typical 10,000 dollar annual tutoring cost.

Jason Calacanis recounts a story where John Doerr attended a pitch meeting directly from the emergency room after a biking accident, viewing it as a sign of ultimate commitment despite Doerr being groggy.

Sue Kim says 40% of Brilliant’s users are in the US, with 60% international. This drove the choice of the name Cooji, which is short, globally accessible, and not tied to a specific language.

Sue Kim says Brilliant chose a direct-to-consumer model over B2B sales to schools to stay close to learner feedback. They read every app store review and customer email for real-time product development insights.

Sue Kim says the ability of frontier LLMs to tutor well has plateaued since GPT-3.5 because they lack verifiable reward signals for learning outcomes. Brilliant's unique dataset of tutoring sessions provides that signal for model improvement.

Jason Calacanis tells a story of a VC firm canceling a meeting while he was driving to it after a cross-country flight. He confronted the investor, calling him the worst venture capitalist of all time.

Sue Kim says Brilliant’s vision is a world-class tutor in every home for every subject and language. They are expanding from math and coding into science and younger age groups, leveraging LLMs for high-quality localization.

Jason Calacanis argues OpenClaw has become the number one open-source project in history based on metrics like GitHub stars, exceeding React.

Logan Allaire's Fin Capital invested in Circle at the pre-IPO stage with a thesis that stablecoins would become the rails for cheaper, faster digital money movement, from credit card settlements to remittances.

Calacanis identifies adoption signals for new technologies: first by criminals and discreet actors, then by fee-sensitive transactional apps like Venmo and PayPal, and finally by everyday service providers like gardeners.

Eric Voorhees founded Venice AI as a private, non-censored ChatGPT alternative to bring crypto principles of user sovereignty, privacy, and free speech to the AI world.

Allaire passed on proprietary LLM investments, believing open-source models would close the gap on intelligence, speed, and price, forcing AI-first companies to rely on sticky domain differentiation and data integration for moats.

Voorhees criticizes frontier AI labs for prioritizing distant safety concerns while engaging in mass surveillance, calling it the most present danger.