Kyle Harrison
← Portfolio Ideas

Technological Innovation

How breakthroughs happen and propagate

The study of how technology advances, what makes a breakthrough (vs. incremental improvement), and how markets, social behavior, and institutional structures shape the pace and direction of innovation. Includes analysis of specific technologies and sectors, identification of emerging trends, and understanding the interplay between invention (technical possibility) and adoption (market/social reality).

17 Essays
41 Books
22 Saved
0 Projects
Latest Saved
B
Ben Pouladian @benitoz

Today, SanDisk replaced Atlassian in the Nasdaq-100. A NAND manufacturer took the seat of a Jira vendor. That is the regime change in one headline. Read it twice. For 15 years, the Nasdaq-100 was a monument to asset-light software. High gross margins, negative working capital, zero cleanroom capex, Rule of 40 as scripture. SanDisk is the anti-Atlassian. Fabs, fluorine chemistry, EUV-adjacent lithography, 232-layer stacks, wafer yields measured in basis points. Actual physics. And here is the part nobody on fintwit is pricing in. The US graduated 24,547 electrical engineering bachelor's in 1986-87. In 2020-21, we graduated 16,914. Four decades later. Still below the Reagan-era peak. Not flat. Down. Computer science over the same window went from roughly 39k to 109k. Call it 2.8x. The two lines on the chart do not just diverge, they mock each other. I say this as an electrical engineer. UCSD, Fainman's ultrafast nanoscale optics lab, silicon photonics, micro-ring resonators. I know exactly what it takes to train someone who can actually move a process node, close timing on a mixed-signal die, or debug a yield problem at 3am. It is not a weekend cohort. It is a decade minimum, and most of that decade happens inside a fab or a tape-out cycle, not a classroom. An entire generation of smart kids was correctly told to chase software. That is where the returns were. TAM expansion, zero marginal cost, stock comp that prints. Nobody was writing Substacks about NAND process engineers in 2015. Nobody was telling their kid to go learn III-V epitaxy instead of React. Now the regime has flipped and the pipeline is a ghost town. You cannot bootcamp a device physicist. You cannot GPT your way into an analog layout. You cannot vibe-code a 232-layer charge trap stack. The training loop is a PhD plus a decade of tribal knowledge locked inside TSMC, Micron, Hynix, Samsung, Applied Materials, and maybe a dozen labs that actually still teach this stuff. When SanDisk wants to double enterprise SSD output, the binding constraint is not capital. The market will fund it at any multiple you can type into a DCF right now. The constraint is humans who know how to make the stack yield. And those humans are already employed, already vested, and already being counter-offered. This is the Memory Wars thesis with a labor-market overlay. The software guys spent 15 years telling us hardware was a commodity. Now the commodity has pricing power and the "real engineers" are the ones walking into comp negotiations with leverage for the first time in a generation. Pricing power accrues to whoever already has the talent locked up. That is the incumbents, and anyone with a serious university pipeline. Everyone else is about to learn that CHIPS Act money does not manufacture device physicists. It just bids up the ones who already exist. SanDisk entering the NDX is not the story. SanDisk entering the NDX while the US graduates fewer EEs than it did under Reagan, that is the story. Source: NCES Digest of Education Statistics, Tables 325.35 and 325.47. Bachelor's degrees only.

The Great Divergence: US bachelor's degrees in Computer Science vs. Electrical Engineering, 1985-2021. CS climbs from ~39k to 108,503 (2021-22). EE declines from a 1986 peak of 24,547 to 16,914 (2020-21).
Apr 11, 2026
M
Meer | AI Tools & News @Meer_AIIT

This guy literally scraped 25,000 comments to uncover which AI tools are actually making people money (and saving hours).

Sep 3, 2025
M
Mario Gabriele @mariogabriele

What AI startups should you keep an eye on? 🤖 🔥 We asked some incredible investors and founders for their picks. Here are 13 companies pushing the AI frontier 👇 1. Factory (@factoryai_) Factory is creating AI coding "droids" designed to take care of an engineer's annoying busywork. These agents can independently tackle routine tasks like code review and debugging. - @markiewagner, Delphi Labs 2. Lamini (@laminiAI) Lamini makes it easier for enterprises to adopt AI. Its LLM engine helps create and fine-tune customized, private models. It also has a neat partnership with Databricks, making it even easier to get up and running. - @tjack & @james_c_wu, First Round 3. Sereact Sereact is revolutionizing warehouse automation, leveraging AI to train its robot arm to understand and adapt to real-world settings. From picking electronic devices to soft fruits, its arm navigates spatial and physical nuances v well. - @nathanbenaich, Air Street 4. Mistral Mistral, founded by impressive AI talent, is developing superior open-source language models. In time, this could create a Cambrian explosion of specific, compelling use cases. A potential European challenger to OpenAI. - @spolu, Dust 5. Poolside Poolside, co-founded by ex-CTO of GitHub, is another player in the AI-programming space. Its approach is to create a dedicated foundation model focused on one usecase: code generation. - @matangrinberg, Factory 6. NewLimit (@newlimit) NewLimit is using ML to change the game in epigenetic reprogramming. Their approach could be transformative for treating intractable diseases. It's a highly technical but pragmatic team at the helm. - @SimonDBarnett, Dimension 7. Runway (@runwayml) Runway is building a new creative suite with AI. It brings professional-grade video creation to anyone, anywhere. Already Fortune 500 companies and major movies are using its software. - @graceisford, Lux 8. Labelbox (@labelbox) Labelbox helps companies better leverage big data and AI. By making it easy to select, annotate, and assess data, Labelbox makes it easier to experiment with using AI models like GPT-4. - @Roberman, SoftBank 9. Dust Dust leverages LLMs for enterprise productivity. The startup is building a "team operating system" designed to augment (not replace) knowledge workers. - @KostaBuhler, Sequoia 10. Abnormal Security We've seen a surge in AI-powered fraud. As these sophisticated attacks rise, so does the need for AI defenses. Abnormal Security offers a solution, using AI to counter AI threats. - @saammotamedi, Greylock 11. Lance (@lancedb) Multi-modal AI is revolutionizing industries, but data management remains a challenge. Lance offers a solution, optimizing storage and handling for this unstructured data, increasing performance, reducing costs. - @saarsaar, CRV 12. Glean (@glean) Glean uses AI to provide unified, contextual search across all apps. It's quickly becoming more than just a tool - it's an intuitive work assistant that enhances productivity, breaks down silos, and adheres to data governance requirements. - @josh_coyne, KP 13. Alife (@alifeIVF) Alife is revolutionizing IVF with AI-powered tools. It's enhancing decision-making at crucial stages like ovarian stimulation & embryo selection, making fertility treatments more accessible and efficient. - @rebeccakaden, USV Fin! There's a lot more insight and detail in the piece, linked below. Jump in and subscribe for more glimpses of the future :) https://t.co/RE0HBQWjRl

Jul 24, 2023