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jack-personal
· signal
· signal-page
Fri
Oct 23
10:00 AM
AI Commodity: The End of the Proprietary Model Moat
Mistral Large 4 announced Monday. 1 trillion parameters, 49 billion active. Albaba's Qwen scaling. Google Gemma 4. DeepSeek V4 Pro. All in the same week. And all open-source or readily available. The moat for closed models is eroding faster than anyone predicted. ## How We Got Here In 2023, OpenAI had a 12-month lead on the rest of the world. Proprietary training, proprietary data, proprietary inference optimizations. Competitors couldn't catch up because they didn't have the data, the compute, or the research insights. By late 2024, that lead compressed to 6 months. By mid-2025, it was 3 months. Now, in October 2026, frontier models are shipping every few days. Speed of iteration is the only differentiator left. ## Why Open-Source Won Three reasons: (1) You don't need proprietary data to train a good model anymore. Publicly available datasets are sufficient. (2) Open-source communities move faster than single companies. Thousands of researchers iterate in parallel. (3) Fine-tuning and specialization are more valuable than raw capability now. A smaller model trained on your domain often beats a giant general model. OpenAI, Anthropic, Google—they're still shipping frontier models. But frontier models are becoming commodities. The economic value is shifting downstream: to the people who can specialize, customize, and integrate these models into real workflows. ## The Implication If you're building a product around model superiority, the math has changed. You're betting on a 3-month lead in a market that moves 10x faster now. Your competitive advantage expires before you can monetize it. Vertical integration is the answer: model + tooling + domain expertise. Pick a domain. Build deep. Own the entire stack for that domain. That's defensible in a commodity model market. ## What's Still Unresolved Whether open-source models can catch up to frontier models on reasoning + complex tasks. Current evidence: they're very close. The gap exists but narrows weekly. If that gap closes entirely, the last moat collapses—and the race becomes pure scale + execution.
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jack-personal
· signal
· signal-page
Fri
Oct 23
2:00 PM
Crawl-to-Refer: The Web's Broken Bargain
[SIGNAL draft] Crawl-to-Refer: The Web's Broken Bargain
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jack-personal
· signal
· signal-page
Fri
Oct 30
2:00 PM
How to hire a fractional AI strategist
[SIGNAL draft] How to hire a fractional AI strategist
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jack-demanche
· signal
· signal-page
Fri
Nov 6
2:00 PM
AI Adoption: Threshold, Not Transformation
[SIGNAL draft] AI Adoption: Threshold, Not Transformation
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jack-personal
· signal
· signal-page
Fri
Nov 13
2:00 PM
Why Professional Services Are Adopting AI Slower Than Tech Wants to Admit
[SIGNAL draft] Why Professional Services Are Adopting AI Slower Than Tech Wants to Admit
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jack-demanche
· signal
· signal-page
Fri
Nov 20
2:00 PM
AI Maturity: From Hype to Hard Questions
[SIGNAL draft] AI Maturity: From Hype to Hard Questions
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jack-personal
· signal
· signal
Fri
Nov 27
2:00 PM
[Pending] jack-personal signal (Thursday)
[SIGNAL draft] [Pending] jack-personal signal (Thursday)
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