Tokenmaxxing
I burnt 250M tokens in a day. Tokenmaxxing is the deliberate practice of maximizing AI token consumption through parallelization.
I burnt 250M tokens in a day. Tokenmaxxing is the deliberate practice of maximizing AI token consumption through parallelization.
On April 9th, Lena Waters kicks off Office Hours with Marketing in the Agentic Era. 15 minutes. One topic. Call-in questions.
What happens when AI stops getting cheaper & starts getting more expensive? The implications for software companies are profound.
Intercom & Chroma shipped custom AI models today. Would you choose one software over another because it has a proprietary model with better performance?
The SaaS era rewarded unbundling & specialization. AI companies are rebundling into platforms because rapid model changes create cognitive burden for buyers assembling best-of-breed stacks.
When a $50 billion American company builds its flagship model on Chinese open-source weights, that's a sign of the criticality of open source to innovation.
Agent pricing reveals whether you're solving scarcity or creating disruption - and the market rewards these very differently.
Stripe launched Tempo today. I raced Claude against a local model on my laptop - and the simpler model won.
For every dollar hyperscalers earn from AI today, they're spending twelve dollars to build more capacity. That's the 12x bet embedded in $575 billion of capex this year.
Amazon lost $6.3M in orders from AI coding failures. Utah law eliminates the hallucination defense. Companies bear liability for their agents' mistakes.