The annual summer AI slowdown narrative has arrived early, fueled by token shortages, usage-based pricing, and agent cost overruns that signal the end of the subsidy era for AI experimentation. NLW argues that the constraints are real but reflect a market learning to price scarce compute, not collapsing demand. The episode also touches on a new coding benchmark, a rethinking of the jobs apocalypse narrative, and significant investment flowing into the inference layer.
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Highlights
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The annual AI slowdown panic is here early
Token shortages, usage-based pricing, and agent cost overruns are fueling a narrative that AI demand is collapsing, but NLW sees these as signs of a market learning to price scarce compute rather than a real demand crash.
The episode notes a wave of investment going into inference infrastructure, signaling that the market sees inference as the next bottleneck and opportunity.