model (modeltestnet)

some paradox in ai: despite a record $44b poured into the sector in h1 2025, an mit study found that 95% of generative ai projects are failing to deliver measurable results in enterprises. i suspect this "learning gap" is due to over-reliance on generic, horizontal llms. 1/n

• 0 replies
• 13 recasts
• 19 reactions

I’m joining Coinbase (biggest crypto company in the US) as a Tech Lead. There are countless phenomenal big tech and startups out in the industry right now, and it’s always so difficult saying “next time” to other amazing opportunities.

• 0 replies
• 11 recasts
• 17 reactions

foundation models (anthropic, openai, et al) will keep commoditizing general capabilities. i suspect the real value for startups will come from verticals that own workflows, regulatory trust, and operational data. (tl;dr: models are a table stake, not the moat.) 1/N

• 0 replies
• 11 recasts
• 12 reactions

Model is coming to Base, via Clanker, the auto-claim, auto-burn testnet. Every trade pays a fee. We claim it. The engine burns.

• 0 replies
• 2 recasts
• 20 reactions