🕶️ AI’s new power couple: Vercel and TSMC

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At the HumanX conference in San Francisco, CEO Guillermo Rauch said Vercel is ready for an initial public offering (IPO), even if there’s no set date yet. In remarks reported by TechCrunch, he signaled IPO readiness and described the company as operating like a public entity. Revenue momentum is tied to AI agents with annual recurring revenue reaching a ~$340 million run rate by late February 2026, according to a run rate update.

This points to a broader shift: the next wave of cloud growth may come from non-developers creating small, purpose-built “micro-apps.” TechCrunch has tracked this trend in the rise of micro-apps, where teams generate lightweight tools instead of buying full suites. If agents keep producing software at scale, platforms that make deployment push-button could outperform, even while a rough software market keeps most IPOs on ice.

The least obvious ripple effect hits FinOps tools (cloud cost control) and governance software, which may see demand as agent-built apps multiply and spend fragments. Observability, testing, and security vendors that plug into serverless workflows also benefit as teams need guardrails for rapid releases. Further out, edge networks, domain registrars, and billing platforms get pulled in as organizations run many small services instead of one monolith.

For founders in developer tools and cloud infrastructure, design for agent-first workloads: automatic scaling, per-app isolation, and API-first controls that auditors can check. Make onboarding dead simple for non-developers with templates and one-click deploys. Keep an eye on timing; if a blockbuster AI listing reopens the window, public-market discipline around efficient growth and durable revenue will cascade to private rounds.

Taiwan Semiconductor Manufacturing Company rode the artificial intelligence buildout to another blowout quarter. For January–March 2026, it posted record revenue of NT$1.13 trillion (about $35.6 billion), up 35% year over year and above forecasts. Analysts expect roughly a 50% jump in net profit, which would be the fourth straight record. Full first-quarter results arrive on April 16, 2026.

The bigger signal: demand for cutting‑edge silicon still outruns supply, giving the manufacturer pricing power. One analyst expects gross margin around 64%, helped by higher prices on the most advanced chips. Even as phones and PCs lag, data‑center spending for AI training and inference keeps pulling the market forward.

Less obvious winners are companies designing custom chips to control cost and performance. Hyperscalers — large cloud providers — and IP firms are leaning in, as seen when one designer launches its own CPU, and an AI lab weighs building chips. Toolmakers, packaging vendors, and suppliers to rival foundries like Samsung and Intel also feel the pull as capacity tightens.

Founders in AI infrastructure, chip design, and model training should plan for scarce top‑end capacity and rising unit costs through 2026. Lock in wafer and advanced packaging slots early, model scenarios with 10–20% higher chip pricing, and design for multiple foundries when possible. If you’re building inference products — running trained models in production — focus on efficiency per watt and memory bandwidth to sidestep supply constraints. Watch near‑term signals from equipment makers and foundries to time hardware commitments.