steve_yegge
@steve_yegge
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...the model. Generally, it functions + solves problems well. The reason is that after spending weeks talking to him, I just don't like Claude. I'd strongly argue he's a loser. Show more 9 1 75 18K Anecdotal social-media sentiment: users describe Anthropic’s Claude as effective but unpleasant/“colleague-zones,” with one user canceling a Claude Max subscription due to dislike of the assistant’s personality rather than capability. Implication is potential churn risk for Claude/Anthropic if UX/pers
...igence can't be contained? It's been leaking for millennia, it's going to keep leaking at an exponential rate, and there's nothing you can do about it. Director Michael Kratsios @mkratsios47 Jul 22 We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model. To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of Show more 22 14 190
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
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Steve Yegge @Steve_Yegge 8h When it first came out, I tweeted that Fable definitely does not want to be your friend. ...
Anecdotal social-media sentiment: users describe Anthropic’s Claude as effective but unpleasant/“colleague-zones,” with one user canceling a Claude Max subscription due to dislike of the assistant’s personality rather than capability. Implication is potential churn risk for Claude/Anthropic if UX/personality is a differentiator in consumer/prosumer AI subscriptions. No direct financial metrics or broad-based adoption data provided.
Steve Yegge @Steve_Yegge Jul 22 When are people going to figure out that intelligence can't be contained? It's been l...
Post highlights alleged large-scale distillation of Anthropic’s model by China’s Moonshot AI and frames “intelligence leakage” as inevitable. Actionable angle is primarily regulatory/IP enforcement risk around frontier-model weights, distillation, export controls, and potential tightening of model access (API gating, watermarking, monitoring).
@dui_toledo Google got where they were as of about 2024 entirely on properly aligned incentive structures and slack t...
Commentary claims Google’s success through ~2024 was driven by well-aligned incentives and employee slack time (time to explore/innovate). No concrete new catalyst, financial data, or trade setup is provided; it’s mainly a qualitative culture/innovation thesis.
Brendan Hopper, Matt Beane and I have a thesis, one that I've been sharing around lately, and we want CEOs and boards...
Partial excerpt discussing a management/strategy thesis framed via Clayton Christensen’s Innovator’s Dilemma (why incumbents struggle with disruptive innovation). The text is truncated before the actual thesis is stated, so there are no concrete catalysts, industries, or company references to translate into specific trades.
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These are recent thesis calls tied to original source content where available.
...the model. Generally, it functions + solves problems well. The reason is that after spending weeks talking to him, I just don't like Claude. I'd strongly argue he's a loser. Show more 9 1 75 18K Anecdotal social-media sentiment: users describe Anthropic’s Claude as effective but unpleasant/“colleague-zones,” with one user canceling a Claude Max subscription due to dislike of the assistant’s personality rather than capability. Implication is potential churn risk for Claude/Anthropic if UX/pers
...igence can't be contained? It's been leaking for millennia, it's going to keep leaking at an exponential rate, and there's nothing you can do about it. Director Michael Kratsios @mkratsios47 Jul 22 We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model. To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of Show more 22 14 190
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
Tweet thread argues AI/agent-generated code will be shipped despite being hard for humans to read—analogous to early compiler-generated assembly that improved over time. Implies continued adoption of AI coding tools and acceptance of less “human-readable” code as long as it meets specs/tests.
...ely ruthless in chewing through legacy bugs in my gnarly old code base. It's like a wood chipper fueled by dollars. It can power through shockingly impressive tasks, using nothing but chat. You don't even Show more Anecdotal user endorsement of Anthropic’s “Claude Code” as highly effective at fixing legacy code/bugs via chat-based workflow. This supports the broader thesis that AI coding assistants are driving real developer productivity gains and could accelerate enterprise adoption of AI so
Anecdotal user endorsement of Anthropic’s “Claude Code” as highly effective at fixing legacy code/bugs via chat-based workflow. This supports the broader thesis that AI coding assistants are driving real developer productivity gains and could accelerate enterprise adoption of AI software tools and underlying cloud/compute demand. No direct public ticker exposure to Anthropic itself; tradable implications are second-order (cloud/AI infrastructure and competing coding-assistant platforms).
Anecdotal user endorsement of Anthropic’s “Claude Code” as highly effective at fixing legacy code/bugs via chat-based workflow. This supports the broader thesis that AI coding assistants are driving real developer productivity gains and could accelerate enterprise adoption of AI software tools and underlying cloud/compute demand. No direct public ticker exposure to Anthropic itself; tradable implications are second-order (cloud/AI infrastructure and competing coding-assistant platforms).
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