Summary
The How I AI channel documents hands-on benchmark testing and practical workflow demonstrations using GPT-6 Astra, OpenAI’s new frontier model priced at $10 per million input tokens and $50 per million output tokens. The video focuses heavily on computer use and browser automation, with Automation Bench scores roughly double those of GPT-5.6 Soul and a significant jump on Frontier Math Tier 4. The creator notes that Astra is rolling out first to enterprise Daybreak customers before broader availability on GPT Plus, Pro, Enterprise, the API, and AWS.
Real-world use cases drive most of the runtime. Astra is shown managing lead routing inside a CRM (cxo.dev), dividing inbound contacts between team members based on company type—a task previously done manually. In a QA automation example, Astra ran for 1 hour and 45 minutes autonomously testing a chat application in Chrome, inspecting console logs, triggering race conditions, refreshing the browser, and filing fixes without human intervention. The model also generates thumbnail images via browser tools in minutes, a task the creator estimates normally takes an hour.
On the coding side, Astra is credited with solving several persistent software engineering challenges that Fable, Opus, and GPT-5.6 Soul could not resolve—specifically a product intelligence aggregation feature pulling data from Intercom, Granola, Linear, and GitHub.
📺 Source: How I AI · Published September 03, 2026
🏷️ Format: Benchmark Test
