Fireworks processes more than 40 trillion tokens per day, the majority from customised rather than off-the-shelf models.
Snapshot · The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
Fireworks processes more than 40 trillion tokens per day, the majority from customised rather than off-the-shelf models.
Where this was said
At 36:54 · chapter starts 28:00
One of the most technically rich chapters in the episode. Lin explains that early AI tech adopters are hackers who want control, and Cursor — flush with frontier lab researchers — is the prime example. The problem they solved together is profound: hyperscalers run RL training on 100,000 interconnected chips. Cursor and Fireworks had no such cluster. Their solution was to decouple the trainer (which updates model weights) from the RL rollout (which deploys the model into a synthetic environment to collect rewards), distributing the system across five or six global data centre regions and syncing fresh model weights efficiently enough that the reward signal stays numerically sound. This distributed design enabled Cursor's recent model launches without a hyperscaler-level budget.
Fireworks CTO Dima embedded at Cursor for months to build a distributed reinforcement learning infrastructure that decouples the trainer from RL rollout across six global data centre regions. This let a capital-constrained startup run training jobs that previously required 100,000 interconnected chips at a hyperscaler.
Lin Qiao sees 2024 as the year of coding AI and 2025 as the year of co-work. Co-work is dramatically more diverse than coding — spanning legal, finance, healthcare, customer support, and consumer-facing AI — and Fireworks is already landing customers across all of those verticals.
Fireworks processes more than 40 trillion tokens a day today. Lin Qiao projects that number could be 20x to 100x higher by end of next year. At those volumes, worries about a CapEx bubble look completely backwards.
The founder attached their SaaS demo to the trending debate about whether AI coding is actually good enough to build a full SaaS product.
Quickly forming opinions on how the Twitter algorithm and platform worked allowed the speaker to grow rapidly on the platform.
Sam's initial MVP was coded in approximately one week using ChatGPT voice mode and copy-pasting code, with no prior technical experience.
Sam argues Discord is 10x better than email for building relationships with younger users who rarely check their inbox.
Sam's monthly operating costs include Cursor ($200), AI image generation ($100), AI video generation ($200), hosting ($100), email marketing ($80), and AI compute ($300–$500).
Sam recommends copying days of Discord chat history into ChatGPT and prompting it to list recurring pain points as a fast, free market research technique.
Bhanu and his team built approximately 50 free tools to attract search traffic, each linked back to SiteGPT.
With AI coding tools like Cursor, Bhanu can now create a new free marketing tool in less than 5 minutes by referencing existing tools.
Bhanu filters Ahrefs keyword results to show only those with a keyword difficulty below 10, making them realistic ranking targets for any decent website.
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