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Things I Think I Think About AI (2026 Edition)

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Things I Think I Think About AI (2026 Edition)
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Its best use is as a planner.There are only three real vectors to judge models: Raw intelligence (frontier foundation models), cost-per-intelligence (value models), and tokens-per-second (there's some minimum bar for intelligence here, but it's low), everything else is competing for scraps. The frontier foundation models are where we all pay the most attention (Fable, Opus, Sol, etc.), but I think the most interesting/dynamic space right now is cost-per-intelligence, where you have Gemini Flash-Lite, 5.6 Luna, and open source models like DeepSeek Flash v4. These are workhorse models and play a huge role in almost any large-scale AI project.I still think the hype around local models is far from the reality.

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Original publisherAlephic
Canonical URLhttps://www.alephic.com/writing/things-i-think-i-think-about-ai-2026-edition
Publication timeFri, 07 Aug 2026 12:35:44 +0000
Retrieval time2026-08-07T12:45:47.452Z
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← All WritingAlephic / WritingThings I Think I Think About AI (2026 Edition)In the 2026 edition of Things I Think I Think About AI, I revisit AI harnesses, top models like Fable, and agent-first workflows reshaping the field.Noah Brier/August 6, 2026/6 min readShareSubscribeLast year I published a list of 29 things I think I think about AI, and I thought it might be good to revisit. So here’s my 2026 edition:Everyone is going to be working in harnesses (Codex, Claude Code, etc.) in the future.I'm not sure if that harness-first future is 6, 12, 18, or 24 months out.If your primary experience of AI is still in ChatGPT, Claude, or Copilot, you have no idea what these models are really capable of.Don't count out Google and Microsoft in the harness race quite yet.

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