GPT-6 Astra Explained | The Biggest Change Isn’t Intelligence

Most models stop at an answer. GPT-6 Astra is built to finish a job. This AI Mechanics episode explains the real shift: from one-turn chat to goal, reason, act, observe, adapt, complete. Computer use, agentic coding, research loops, mid-turn steering, async tools, and a token price about 2. 5 times Sol. No AGI claims. Vendor benchmarks are labeled OpenAI-reported.

Price is part of the story. In this video: • Why the old user-model-answer loop fails on real work • How Astra becomes part of a workflow, not the whole show • Computer use: see the screen, act, check, continue • Coding as a multi-step job: edit, test, read the failure, fix • Research as a repeated loop, not one search • Documents, sheets, and slides as artifacts • Mid-turn steering without restarting the whole job • Async tool calling for independent work • Reasoning effort you can change mid-conversation • Same long context window as Sol, better retrieval • OpenAI-reported numbers, and why the bill still matters • Agency needs boundaries: intent, policy, permissions MORE AI MECHANICS AI agents: https://www.

youtube. com/playlist? list=PLNeIEtc2-vsw How LLMs work: https://www. youtube. com/playlist? list=PLK3S1GR94Fzg AI Mechanics. Understand the system, not the hype.

Watch the video for the full walkthrough. Use this page when you want the argument in writing without scrubbing the timeline.