It is going to be like what happened in coding: as soon as models crossed a certain threshold (Opus 4.5, GPT-5.2, Gemini 3), suddenly Claude Code & Codex were viable. Before that, it was all about coding assistance, afterwards it was all about agents from relatively small gains.
@emollick
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Gradual AI improvements cause discrete jumps in economically important areas
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Soon, at each gradual improvement level of AI, you will start to see large discrete jumps in ability in economically important areas, because the previous AI ability level in some aspect of the job bottlenecked progress. When bottlenecks are released, it looks like a leap forward
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Previous belief in AI compute bubble and recession wrong
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Six months ago, there was a lot of focus on the idea that the there would be a massive glut of unused computing power which would could a recession as AI use plateaued. The "compute bubble" belief was absolutely everywhere. The degree to which this was wrong deserves some notice
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Seedance 2.0 depicts mech battle of Neanderthals vs Homo Sapiens
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Impressed that Seedance 2.0 can pull of "a mech battle between Neanderthal and Homo Sapiens" so well. (This is exactly what happened, historically) pic.twitter.com/isz8yANi3k
— Ethan Mollick (@emollick) 13 avril 2026Impressed that Seedance 2.0 can pull of "a mech battle between Neanderthal and Homo Sapiens" so well. (This is exactly what happened, historically)
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Sketchy demonstration: prompts fed vulnerabilities to small model
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That particular demonstration was pretty sketchy, the prompts appeared to feed the small model the exact vulnerabilities.
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Mythos backlash: agentic coding tools raise cybersecurity concerns
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I am catching glimpses in my feed that there is a backlash against Mythos as "marketing hype," and it is a little confusing. I don't think anyone who has used the latest agentic coding tools, would think that expecting large-scale cybersecurity implications of increasingly good
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Summarized thinking traces useful despite trade secret internal reasoning
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(thinking traces are always summaries of the internal reasoning, since the actual internal chain of thought is a trade secret, but that doesn't mean they aren't useful when summarized, especially when those summaries contain the tools used by the model and web searches it made)
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AI models debate power usage of local OpenClaw on Mac
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And if you are interested in the answer, Claude and ChatGPT 5.4 Pro think running OpenClaw with local inference on your Mac uses more total power. Gemini doesn't think so (but appears to have not thought about that too hard)
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ChatGPT best at thinking traces, Claude good, Gemini weak
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Currently, ChatGPT has the best way of viewing thinking traces, a short summary of steps in the main window, and a detailed audit in the sidebar if you want it Claude does almost as well, but more summarized and harder to see calculations and code Its a big weak spot for Gemini
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Debating optimal markdown files for AI agents likely temporary
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It is notable that we are all debating exactly which markdown files are most important to feed AI (skills, memory, tool instructions) and in which order to feed them to get the best output. Feels that this is likely a temporary state of affairs in the development of agents