Ethan Mollick: The UK’s state AI Security iIstitute findings: 1) Mythos is a big gain in cyber capabilities. But so is GPT-5.5 2) It is...

The UK’s state AI Security iIstitute findings: 1) Mythos is a big gain in cyber capabilities. But so is GPT-5.5 2) It is hard to establish an upper bound on Mythos/GPT-5.5, which appear to be limited by tokens used, rather than ability. 3) Capability doubling time is 4.5 months. Ethan Mollick: The UK’s state AI Security iIstitute findings: 1) Mythos is a big gain in cyber capabilities. The BotsFired read on Ethan Mollick: this matters only where it changes a real workflow, budget, deployment constraint, or buyer decision. Model progress only matters when it changes the work people can actually ship. The hard question is whether the model improves accuracy, latency, cost, or tool use enough to change a production decision. For builders, the practical question is whether Ethan Mollick removes a constraint that teams already feel. A launch is cheap; a default workflow is expensive to earn. Developers will test it against real tasks, not leaderboard language: messy prompts, long context, tool calls, regressions, and the cost of switching. For operators, the test is narrower: what work moves from manual judgment to repeatable system behavior, who approves the change, and what failure mode appears when the tool leaves the demo path? The next read should compare the claim against customer behavior, integration depth, pricing, reliability, and whether the same pattern repeats across adjacent companies