In partnership with

The AI supply chain is in a phase of structural scarcity. This is not a temporary dip in supply; it is a multi‑year shortage in the components required to build AI factories, especially the advanced packaging that binds GPUs to high‑bandwidth memory and the HBM itself.

The constraint is simple: you cannot build an H100, MI300, or any comparable AI accelerator without advanced packaging and high bandwidth memory. Advanced packaging capacity at TSMC and high‑bandwidth memory output from vendors like SK Hynix are effectively sold out through 2026. The limiting factor is no longer demand for GPUs; it is access to the packaging and memory capacity that makes those GPUs real.

Fabrication is no longer the main bottleneck. Even if you secure leading‑edge wafers, those chips still need to move through scarce advanced packaging and be matched with high‑bandwidth memory that is already fully allocated. TSMC and the major memory houses are running flat out, yet demand for AI systems sits structurally above what the current capacity curve can support. That gap is persistent, not cyclical.

This is what structural scarcity looks like:

• Capacity expansions are slow, capital‑intensive, and themselves constrained by upstream tools and processes.

• The largest buyers have already pre‑booked the majority of incremental output via multi‑year agreements.

• New entrants and slower movers are left to compete over whatever residual capacity remains at the margin.

In this environment, the old playbook fails. Buyers cannot rely on spot markets, end‑of‑quarter deals, or opportunistic secondary channels. When output is pre‑sold, there is nothing to “spot” in the first place. Price becomes a weak lever because the real constraint is allocation, not willingness to pay.

The mandate for 2026 is capacity, not discount. Procurement teams need to behave like strategic financiers of their own AI infrastructure, not transactional buyers of commodity hardware. That means moving from short‑term purchasing to explicit capacity locking.

In practice, that shift looks like:

• Multi‑year commitments for GPUs, memory, and packaging capacity with clear volume and roadmap visibility.

• Direct relationships with foundries, memory suppliers, and integrators, backed by credible long‑term demand signals.

• Willingness to trade some pricing flexibility for guaranteed allocation and delivery priority.

The 2026 environment is a pressure cooker for anyone building or scaling AI infrastructure. Organizations that approach this as a standard hardware procurement cycle will find themselves stuck in waitlists while competitors with locked‑in capacity continue shipping products, models, and features. The supply chain is now a competitive weapon.

This is not a story about “once supply catches up, things go back to normal.” AI demand, packaging complexity, and HBM intensity are moving faster than capacity can be added. The companies that win this phase are the ones that treat advanced packaging and high‑bandwidth memory as strategic inputs to their business and lock in access ahead of time.

In a structurally constrained world, the correct question is no longer “How do we get the best price on GPUs?” The correct question is “What are we willing to commit so that we are still building when everyone else is waiting?”

Upcoming Events

Bay Area Startups Collectively Secured $50.8B MTD In February

February funding activity continued to set new records in week two, closing the week at $31.6B and taking the month to $50.8B. Six megadeals – including Anthropic 's $30B Series G – provided 98% of the total. The other five megadeals went to Inertia, SambaNova, Solace , Loyal and Simile.

US Market valuations surged in 2025, with median pre-money valuations the highest in a decade, exceeding even 2021 levels, per Pitchbook. But not all valuations are equal, some are stale: Pitchbook estimates that almost 25% of startups valued as unicorns in earlier years would have a current market value of less than $1B. And we have a new handle -"undercorns" - for those companies coined by Axios.

For startups raising capital: Stay on top of who's raising, who's closing and who's investing with the Pulse of the Valley weekday newsletter. Founders get the newsletter, database and alerts for just $7/month ($50 value). Check it out, sign up here.

Follow us on LinkedIn to stay on top of SV funding intelligence and key players in the startup ecosystem.

Early Stage:

• Inertia Enterprises closed a $450M Series A, the commercial fusion energy company, using laser-based fusion.

• VillageSQL closed a $35M Series A, a drop-in replacement for MySQL with extensions for the agentic AI era.

• Trener Robotics closed a $32M Series A, redefining robotics by combining advanced AI with pre-trained skill models that are expert at specific tasks.

• Simple AI closed a $14M Seed, builds voice AI agents for inbound and outbound B2C calls.

• Smart Bricks closed a $5M Pre-Seed, a frontier AI lab building agentic AI infrastructure for global real-estate investing.

Growth Stage:

• SambaNova Systems closed a $350M Series E, a complete solution purpose-built for AI and deep learning that overcomes the limitations of legacy technology.

• Solace closed a $130M Series C, a digital platform that connects patients with expert healthcare advocates who navigate the healthcare system on their behalf.

• Loyal closed a $100M Series C, an animal health company developing the first drugs intended to help dogs live longer, healthier lives.

• Bretton AI closed a $75M Series B, the leading AI platform for financial crime operations.

• Anthropic closed a $30B Series G, an AI safety and research company working to build reliable, interpretable, and steerable AI systems.

Micas Networks is a San Jose-based open networking company that builds high-performance networking solutions for hyperscale, cloud, and data center environments. The company develops a full portfolio of open network switches and infrastructure designed to support the demands of AI, cloud, and high-throughput applications.

What Micas Networks Delivers
• High-performance open networking switches from 1G up to 800G tailored for modern data centers.
• Solutions that support flexible network operating systems including SONiC, enabling customization and scale.
• Energy-efficient designs and options such as co-packaged optics to accelerate connectivity and reduce bottlenecks in AI clusters.
• A manufacturing base and R&D capability that supports rapid delivery and customization for enterprise requirements.

Why It Matters
As data centers scale to support AI training and inference, networking performance and efficiency become key determinants of overall system throughput. Micas Networks’ open networking approach gives builders flexibility and performance by combining robust hardware with adaptable software stacks.

Who It Serves
Cloud operators, hyperscalers, enterprises, and OEMs that require low-latency, high-bandwidth networking infrastructure to keep up with modern workloads and next-generation compute demands.

Learn more at micasnetworks.com.

Your Feedback Matters!

Your feedback is crucial in helping us refine our content and maintain the newsletter's value for you and your fellow readers. We welcome your suggestions on how we can improve our offering. [email protected] 

Logan Lemery
Head of Content // Team Ignite

Better prompts. Better AI output.

AI gets smarter when your input is complete. Wispr Flow helps you think out loud and capture full context by voice, then turns that speech into a clean, structured prompt you can paste into ChatGPT, Claude, or any assistant. No more chopping up thoughts into typed paragraphs. Preserve constraints, examples, edge cases, and tone by speaking them once. The result is faster iteration, more precise outputs, and less time re-prompting. Try Wispr Flow for AI or see a 30-second demo.

Start flowing free