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Brent Wood commented on a post
1w
https://www.linkedin.com/safety/go/?url=https%3A%2F%2Fchamath.substack.com%2Fp%2Fdeep-dive-ai-effect-on-labor-market&urlhash=he5E&mt=au50skCwkexW7WhRr3EQfYA03oGt__ir86zBvdNzA59oUVbpKGlhdbsDCImFGV-Iu2oxsTtVcgR1aBFJEPC2F6h_NlsgThdIiG54F-H4pKI5bQy3Zg-BwnUSW59JTvLw_WSKoRqajEva5IAHeEbaEW2UkR0B&isSdui=true&lipi=urn%3Ali%3Apage%3Ad_flagship3_feed%3BCiiKCPyXQkaFdTCsqckadA%3D%3D
Brent Wood commented on a post
1w
There is a flip side if you are heavily leveraging AI. if you are counting on a company paycheck, and your are not absolutely needed, and AI can replace your function, you need to re-tool NOW. So yeah, maybe some fear is a motivator, but I would hope not paralyzing.
Brent Wood commented on a post
1mo
Largely agree. As a practical data point: I ported an OpenAI implementation to a multi-vendor model framework in 12 hours using Claude Code — swap a few environment variables and you're on an entirely different stack. From there, the natural evolution is a meta-layer that routes tasks to the optimal model, and beyond that, a fan-out architecture that queries multiple vendors in parallel and selects the best response.
With LLM-assisted code generation, the switching costs that used to make vendor lock-in terrifying are largely neutralized. The abstraction layer practically writes itself.
But the deeper point stands: none of that architecture matters if you haven't found product-market fit. If you're in signal-seeking mode, use whatever gets you to clarity fastest — OpenAI, Anthropic, doesn't matter. Get the signal. Then, once you know what you're building and for whom, layer in the vendor-agnostic architecture. Sequence matters. Engineering elegance is a second-order concern when the first-order question — does anyone actually want this — remains unanswered.
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