Welcome to another AI by Aakash. I follow the AI news, and test all the latest AI tools, so you don’t have to. Personal agents are THE trend of 2026. We’re covering every one, and last week was OpenAI’s Dots. Muse is already getting more daily US downloads than Threads, WhatsApp and Facebook, and it’s the biggest consumer AI launch since ChatGPT. Muse hit 5 million downloads in 22 days, and ChatGPT needed 56 days for that. So how does the “worst” model end up as the most used product? That’s todays deep dive. But first, a word from our sponsors + this week’s top news. Partnership🤖 Build three AI agents for your product team in one weekOptimizely’s AI Experimentation University is a free, live cohort for growth and product managers. Five days, one hour a day, and you leave with three AI agents of your own. 300 leaders have already graduated, including teams from Calendly, BBC, ODEON, and Legal & General, and they’ve built 1,667 agents between them. The next cohort starts November 16th. You’ll learn how to:
Past graduates have built agents that turn test requests into Jira epics, diagnose why a variant lost, and return a single ship-or-hold call from frequentist and Bayesian models. Save your seat now. It’s free, but only 50 seats. NewsTop News this week: Anthropic Just Cut the Price of Intelligence by 10xAnthropic shipped Claude Haiku 5.5, its cheapest model ever. It costs $0.10 per million input tokens and $0.50 output, against $1 and $5 for Haiku 4.5. That’s 10x cheaper cost but with a superior performance. On real work Anthropic says it runs about 75% cheaper, and my own bill fell 80% when I switched the models. It also scores 72.4% on OSWorld, up from 15.7% for Haiku 4.5 and it beats OpenAI’s Luna models at using a computer (48.9%).
So now you can get more work done with agents at a cheaper cost. One that burns a million tokens an hr now costs about $2.40/day in input. The cheap price covers requests under 100K tokens which is roughly 90% of old traffic, and cache reads fell from a dime to a penny. The Other News that Mattered
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