Jay Ma

💭 Y Combinator CEO says YC startups launch with 95% of their code written by AI 😮. Harness Field CTO Martin Reynolds brings valuable insight to the conversation with LeadDev around this trend and its impact on software developers. "Having a human in the loop will continue to be vital. The future of coding will involve a combination of human creativity and AI-driven efficiency." Read more on how AI is reshaping engineering roles ⬇️. https://lnkd.in/gnRmrWxS

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Columbus, Ohio has 13 percent growth in company formation YoY. We also just passed Chicago as the 5th largest concentration of data centers worldwide. Construction is accelerating. #ohiotech -

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Here’s a helpful Bay Area Eng compensation guide for startups, created by Deedy Das This resource is valuable for any engineer asking: “How much should I be paid?” It’s also a great way to see the tradeoff between equity ownership and later-stage security: Equity ownership value by stage, relative to Seed: - Series A: 63% of seed - Series B: 40% of seed - Series C: 26% of seed - Series D: 17% of seed Source: Pave, TopStartups, Levels fyi, Carta

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A Founders Guide to The Long Build™ - Physical AI Thesis Part III This one is for the builders. In this final post, my partner Will Porteous and I along with insights from builders in the trenches and investors who play the long game share our guide for founders building intelligence in the real world. A few core takeaways: • Sim before steel: Runway is precious, model the system behavior • Capital intensity is not the enemy — misaligned capital is • Build complete solutions before you talk platform • Hardware opens the door, software wins the room • Trust is earned through resilience, not hype

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You don't need a $2M pre-seed to start building deep tech. When I started building Lamina Labs (Y Combinator P26), I had no funding, no team of 10 engineers, and a vision that required serious GPU compute and AI infrastructure. So I did what any desperate founder would do. I cold emailed. I wrote to Ankit Gupta, who was building the YC student credits program. I told him I was going all in on building a deep tech project, why it needed serious compute, and the commitment I was putting behind it. I sent that email at 10:50 AM on November 14th. He replied at 10:52 AM. Two minutes. That reply changed everything. Thank you Ankit Gupta, that early access was the unlock. From there, it was months of grinding through architecture after architecture. Rewriting core pipelines more times than I can count. Shipping, breaking, rebuilding. Just me, Claude Code, and Codex running in parallel, the closest thing an early founder has to a 10-person engineering team, except they never call in sick. AI coding agents are the single greatest force multiplier available to founders right now. I'm not exaggerating. The leverage is unreal. Here's the thing most people get wrong: you don't need a massive round to get something real off the ground. You need compute credits, the right AI tools, and the willingness to grind through hundreds of iterations until the architecture clicks. If you're a student or early founder sitting on an idea that feels too ambitious, just start. Email the people building the programs. Apply for every credit you can find. Reach out to people you think won't respond. They will. The infrastructure to build serious things as a solo or two person team has never been more accessible. The funding comes after you've already started building something real. Because someone gave me that first unlock, I want to do the same: I'm giving away 5 x $50 Claude Code credits. And whoever ships the best project with that gets $200 in Claude credits from me personally. I know firsthand how much potential $200 in credits has for a builder who's willing to grind. Just comment below with the link to the coolest thing you've built. I will DM you myself.

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Many in AI are asking when robotics will have its “ChatGPT moment.” Ken Goldberg - professor of engineering at my alma mater, UC Berkeley, and co-founder of Ambi Robotics - argues it will come from pairing frontier AI with “good old-fashioned engineering.” We cover where robots excel today (high-throughput, repeatable tasks), where they stall (deformable objects, clutter, uncertainty), and why sim-only approaches break without real-world data and feedback. Listen in on our full conversation here! https://lnkd.in/gGk8rwnx

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"LLMs aren’t the only kind of AI", "One of the biggest, most important one is physical AI. AIs that understand the laws of nature" Not me, but Jensen Huang at CES26. The switch from being able to calculate language and simulate talking about things to understanding how things do things will unlock vast value. Matrix multiplication and reinforcement learning is transforming how knowledge work is done. The next step will impact how work is done at all. For the builders who figure it out and the investors who get it, LLMs will be the warm-up act.

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I've been building AI companies since 2014. Node — an AI company using LLMs years before ChatGPT existed (acquired by SugarCRM). Fireside — a creator operating system co-founded with Mark Cuban. Now I'm General Partner at Digital Indies, and this week my AI agents built 5 autonomous systems while I was in meetings: → A company from scratch. No instructions, no check-ins. → A self-learning engine that monitors markets and teaches itself. → An outbound pipeline. Finds leads, writes emails, sends, follows up. 0% bounce. → A trading portfolio with autonomous signal detection. → A content system. One idea → native posts for 5 platforms. For the first time, it's faster to build than to talk about it. That's what we're building at Digital Indies — an operating system on top of AI agents that takes the technical guesswork out. So founders, creators, and operators can get value without worrying about the rest. The future isn't learning to code. It's learning to architect. What would you build if your AI agents could work while you sleep?

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Cursor Developer Anysphere Becomes Fastest-Growing Startup in History AI-powered IDE startup Anysphere, the company behind Cursor, has raised $900 million at a $9.9 billion valuation — marking one of the most rapid growth trajectories ever seen in Silicon Valley. Highlights: • Backers include Thrive Capital, Andreessen Horowitz, Accel, and DST Global. • This is the third round in 12 months; in December, Anysphere was valued at $2.5B. • The company doubles its ARR every two months, now exceeding $500 million. Bloomberg calls it the fastest-growing startup ever. https://lnkd.in/e9pj_GrP #Anysphere #Cursor #AItools #DeveloperTools #StartupFunding #ARR #VentureCapital #Bloomberg #SiliconValley #AIIDE

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A YC startup faked its AI—by naming a real person Adam. We unpack one of the wildest recent tech pranks: game devs thought they were using cutting-edge AI from a YC company called Adam—turns out “Adam” was a real guy manually editing models. Startup “Adam” tricked users w/ fake AI videos & branding It all started as an April Fools prank… then went viral Founder used AI avatars, cloned voices & even mocked up a fake TechCrunch post Jason steps in after the founder (briefly) used his likeness without permission Sinister? Yes. Brilliant? Maybe. But too real to be funny. #AI #Startups #YC #TechScandal #Deepfakes #ThisWeekInStartups #GameDev

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The hot stuff in startups and ai labs right now for those not in sf is computer use rl environments for X where X is ecomm, finance etc. Computer use means ai that controls the browser, rl environments means training usually post because only 6 companies can afford to do pre, and for X means trying to copy what a human does like checking out on amazon or making a dominos order If you guys heard of mercor they are at $900mn/yr annual run rate, they took scale ai’s contracts from ai labs after scale ai got meta acquisition. There are now about 20 startups in sf that are now taking mercors contracts from ai labs under the next new thing: “computer use rl env for x” Crazy thing is some of these 20 companies that are building computer use rl environments for x are started by new grads and hiring like crazy. So sometimes they dont care even if you know anything related (rl env, ml infra, etc) they just want the most directionally cracked people and betting on raw intelligence and agency and are willing to pay same at quant base (if you are really good). “So do you need a masters for any of this?” HELL NO. trust. Happy to make an email intro to anyone interested just msg me on LinkedIn Thoughts on this?

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Google's latest Gemini update is not about hype. It targets the things that break real work. Here is what is new: 🔹 Ultra-low latency: up to 40% faster time to first token 🔹 2M+ token context window: process large inputs without losing the thread 🔹 Deeper multimodality: native audio, video, and image cross-reasoning 🔹 Stronger multi-step reasoning: fewer contradictions, cleaner logic chains Better models do not fix bad processes, though. The biggest wins come when you pair stronger reasoning with stronger inputs, clear briefs, defined constraints, and a proper review step. Without that, you get more confident wrong answers. You can access it today through the Gemini API, Vertex AI, the Gemini app, or NotebookLM. The right route depends on your needs and what you are building. We have broken it all down, what's new, where to use it, and how to get reliable outputs. Link in comments 👇 #AI #Gemini #GoogleAI #MarketingStrategy #AIForBusiness

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BIG news !!! NVIDIA buying Groq in a huge yet creative 20B USD cash licensing deal!!! Other than Google's TPUs, Groq is/was the most notable attempt on building an alternative that is AI-first to NVIDIA's #GPUs (using an architecture that allows for much more efficient scheduling). Grok's founder actually came from the Google TPU team. That's a strong addition to the Nvidia portfolio. Nvidia demonstrates clear commitment to maintain its dominance in the AI compute space, and an interesting signal for anyone working on an alternative... Less competition isn't great, but more options at scale is 🤷🏻‍♂️ On a personal note, I am a bullish investor in NVIDIA and an early investor in Groq - so quite happy 😀😇 https://lnkd.in/dt5qWuxa #compute #ai

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Allen Zhu (GSR Ventures): The AI app boom is imminent — the next ByteDance, Kuaishou, or Rednote was likely founded this year. At the 2025 Inclusion Bund Conference, Allen Zhu delivered a clear, unsentimental read on where AI is headed: the real opportunities are beyond the model. Key takeaways for builders & investors Model plateau → miniaturization. Under the Transformer paradigm, core “intelligence” gains are tapering; wins will come from UX and cost. Expect smaller, cheaper models, smarter data curation, and edge deployment. Apps are shifting text → voice → video. Token consumption is exploding in real use cases. Voice is breaking out now; ultra-low-latency video (~1s) could trigger the next wave. Moats live outside AI. Think workflows, editing/polish, proprietary/regulated data, operations, and specialized hardware (e.g., capture devices, smart name badges). Do the “boring, dirty work” others avoid. Agents: go vertical or get absorbed. Generic agents lack defensibility and will be eaten by advancing base models. Build sticky, domain-specific agents tied to real processes and outcomes. Commercialization > vibes. Retention is king. Beware “vibe revenue.” In SV, many VCs wait for ~$2M ARR post-launch; in China, sub-12-month paths to ~$5M ARR are becoming the bar. China founders’ edge & go-global. Strength in To-C experience design and hardware supply chains; look to Japan/SEA/MENA to avoid direct “model wars” and compete on execution. From UNIQUE RESEARCH’s tracking of thousands of AI apps globally, we see the same arc: the model dividend is flattening; winners are those who embed AI into specific scenarios, compress latency/cost, and build non-technical moats in data, workflow, and user insight. Bottom line: Don’t chase generic model horsepower. Ship products that deliver outcomes in real workflows—and measure yourself by retention, renewal, and unit economics. https://lnkd.in/gC63AABv

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While OpenAI signed $1.15 trillion in compute contracts through 2035, DeepSeek trained a frontier model for $6 million. This was 2025’s central question : are we building on bedrock or quicksand? The top 10 posts of 2025 examined some of these topics : Are we in a bubble echoing the telecom crash, or building the next internet? Do traditional exit paths still work when secondaries dominate & IPOs vanish? How do you design tools when the user is AI, not human? 2025 forced a reckoning with reality. 1. How AI Tools Differ from Human Tools (https://lnkd.in/d9qcnbyz) : I consolidated my 100+ AI tools into unified, parameter-rich interfaces based on Anthropic’s research. The counterintuitive finding : AI systems need complex tools with complete context, while humans need simple, chunked interfaces. Claude’s success rate approached 100% after the redesign. 2. Back to Text (https://lnkd.in/dWcy53fv) : How AI Might Reverse Web Design : I watched an open-source agent book flights by navigating airline websites, extracting data from visual chaos. If AI thrives on pure text, the future of the web might look exactly like it started : simple text, but for robots instead of humans. The better AI performs, the fewer websites we’ll visit. 3. Circular Financing (https://lnkd.in/d8-KMGZf) : Does Nvidia’s $110B Bet Echo the Telecom Bubble? : Nvidia’s vendor financing totals $110B in direct investments plus $15B+ in GPU-backed debt, 2.8x larger relative to revenue than Lucent’s exposure in 2000. But unlike the telecom bubble, Nvidia’s top customers generated $451B in operating cash flow in 2024. The merry-go-round has paying riders. Read the full post here : https://lnkd.in/d8Xw6tJt

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I had a wonderful time joining Alec Crawford on the AI Risk Reward podcast. We spoke about how AI should enhance rather than replace human creativity, what it means to build ethical, human-centered AI systems, and the future of work. We even discussed how AI acts as a mirror to our collective unconscious. 🎧 Listen to the full episode here: https://lnkd.in/g6Y9b9Yp ▶️ Watch on YouTube: https://lnkd.in/grtJ3FC6 #AI #GenerativeAI #Creativity #AIethics #AIinBusiness #Podcast

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Nemotron 3 Super is here. The new Super model is a 120B total, 12B active-parameter model that delivers maximum compute efficiency and accuracy for complex multi-agent applications such as software development and cybersecurity triaging. Thanks for sharing Chorouk Malmoum 💚

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