The tape last week split again: broader indices leaned soft into PPI/CPI and the next FOMC, while semis held up on company-specific news, where SOX finished higher even as mega-cap tech traded mixed. That is the same relative setup we have been tracking since memory broke out: hardware names responding to incremental AI infrastructure demand while the index still waits on the macro prints.
The research week was dominated by compute demand from a different angle. GPT-6 Astra is OpenAI’s first flagship with computer use as a core capability, and we read it as the Claude 3.7 moment for knowledge work: the demos moved from terminals into CAD, Excel, Blender and tax forms, and the addressable pool is an order of magnitude larger than coding. Multi-step reliability is still the gap, but the trajectory is visible, and OpenAI’s RSI note put numbers on the loop already turning inside the labs: agent hours at 3.1x human hours, with compute as one of the constraints that tightens as other bottlenecks ease. That framing matters more for the next pre-training cycle than any single benchmark.
Separately, the Anthropic-led slowdown debate is back on X. Our take is that release cadence is not the same as training cadence, and a single brake would miss how uneven the stack already is. Coding, math and cyber are remaking workflows where RL data and feedback loops exist; most other industries still lack workflow traces and a usable context layer. Finance is the familiar case. GPT chats and Notion notes are easy to log, while the research-to-EPS judgment path is not. If policy slows anything, the useful version is sector by sector, with more effort lifting the laggards than cutting the frontier to match.
Power and enterprise spend filled in the rest of the stack. We initiated on Delta: 2H26 re-acceleration is AI PSU plus VPD, with DC/DC still underweighted by the market at an estimated 8.3%/12.2% of revenue in 2026/2027 and >70% VPD share at $400-600 content per TPU. Enterprise AI Vol.3 went out with ten more samples: spend is still growing, but the questions have shifted to who needs the expensive models, whether time saved converts into revenue or real cost cuts, and how budgets get reallocated once caching, defaults and local models bite.
This Week’s Reports #
AI Slowdown by Sector — release pace is not training pace, and a uniform brake misses how uneven the stack already is. Our debut Column argues coding, math and cyber remake workflows where RL data and feedback loops exist, while most other industries still lack workflow traces and a usable context layer; if policy slows anything, the useful version is sector by sector, lifting the laggards rather than cutting the frontier to match.
GPT-6 Astra — computer use is the Claude 3.7 moment for knowledge work, and RSI is already turning the compute loop inside the labs. Astra is the first flagship with computer use as a core capability, OSWorld at 72.6%, and a visible path from coding’s trillion-dollar pool toward white-collar work an order of magnitude larger; OpenAI’s RSI note put agent hours at 3.1x human hours with compute as a binding constraint.
Delta Electronics — 2H26 re-acceleration is AI PSU plus VPD, and DC/DC is still underweighted. We initiate on 2308.TW as a grid-to-core AI power name: VPD takes DC/DC to about 8.3%/12.2% of revenue in 2026/2027 with >70% share and $400-600 content per TPU, while we model FY27/FY28 revenue growth of 53%/28%. Enterprise AI Vol.3 — spend is still growing, but the next budget round is gated by usage depth, model tiering and measurable ROI. Ten more enterprise samples show broad basic access with highly concentrated heavy users, production agents in a few names, and cost controls (defaults, caching, local offload) that often get reinvested rather than cutting the total AI envelope.
Premium Report Snapshot #
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