Luigi Bajetti

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Luigi Bajetti

Luigi Bajetti

@baiogi

Managing Partner & Founder @lombardstreetVC

Woodside, CA Katılım Ağustos 2009
711 Takip Edilen6.7K Takipçiler
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Eric Button
Eric Button@ericjacobbutton·
We have raised $7 million in funding, led by @Initialized to build the next generation of air traffic systems. We’re joined by investors such as United Airlines, Y Combinator, and other amazing firms and angels who I'll tag at the end of this thread
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Hunter Leath
Hunter Leath@jhleath·
The unexpected side of venture is that it grows your ambitions in a way that you don't expect. When I first started @archildata, I was hoping that organizations could use it to build a lower-cost way to run applications like Wordpress or genomic sequencing. This is pretty far from where we've landed! There are two cataclysmic changes coming to how we think about infrastructure over the next few years. First, the next wave of applications are *stateful* in way that tools like Kubernetes don't solve for. Secondly, the models that are going to underpin these applications overwhelmingly prefer to use the file system as the transactional system of record. This means that the world is in desperate need for a file system that provides a first-class developer (and agent!) experience to solve for these applications. If you look at what's available, though, XFS was released in 1994 and ZFS was released in 2005. These aren't going to be the right tools! People who don't work in file systems continue to operate under the assumption that these systems from the turn of the millennium are the best that we will ever get, and that's just not the case. I'm just *so* excited for what's to come with Archil, and we've only just started to lift the veil with releases like Serverless execution this week. Thank you to @Standard_Cap and our existing investors for their support and conviction to make this vision a reality. You can get an Archil disk today by running `npx disk create` and it's the worst version of the product that will ever exist. Onward!
Archil@archildata

Today, we're announcing our $11M Series A raise, led by @Standard_Cap in order to build the layer that connects AI to its data. The next generation of agentic applications are inherently stateful in a way that existing primitives don't solve for. Archil solves this for agents by giving them an infinite, high-performance file system that they can use to directly run bash and Linux programs.

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Sygaldry
Sygaldry@sygaldry_tech·
Today we're pleased to share that Sygaldry has raised $139M to build quantum-accelerated AI servers for AI data centers, delivering more compute per watt. We're hiring brilliant, curious, kind, and collaborative scientists, engineers, and more. bit.ly/48KBufk
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Sam Bhagwat
Sam Bhagwat@calcsam·
We’re excited to announce today that @mastra has raised a $22M Series A led by Spark Capital. This brings our total capital raised to $35M:
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Sam Bhagwat
Sam Bhagwat@calcsam·
Today, we’re launching the Mastra platform with tools to run your agents effectively at scale: • Mastra Studio: evals, logs, traces, datasets, metrics • Mastra Server: deploy agents + workflows • Memory Gateway: SoTA agent memory
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Exa
Exa@ExaAILabs·
Introducing Exa Deep: putting an agent inside every search For each query, an agent runs in a loop until it gathers all information, then returns structured output. Evals show Deep is Pareto optimal at 4-60s latency, ideal for quick, cost-efficient research!
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Guide Labs
Guide Labs@guidelabsai·
It’s official: the first large-scale inherently interpretable language model is here. Steerling-8B from @guidelabsai is the first and largest model that can trace every token it generates back to: →  Input Context → Training data → Human-understandable concepts In other words, we've successfully trained Steerling-8B to trace its outputs and explain what has impacted that decision for more reliable manipulation. This isn’t post-hoc explainability. Interpretability is built directly into the model. 🔓Steerling-8B can self-monitor for memorized content and suppress it at inference time without retraining. That makes interpretability a first-class design principle, not an afterthought. This is a major step toward models we can actually understand, debug, and trust. Over the coming days, we’ll be sharing investigations into what Steerling-8B’s interpretability enables in practice. Stay tuned as we dive deeper into our research & how we are building LLMs we can trust. 🚨 Try it LIVE and help improve it: Guide Labs: guidelabs.ai/post/steerling…  GitHub: github.com/guidelabs/stee… Hugging Face: huggingface.co/guidelabs/stee… Huge thank you to @TimFernholz and @TechCrunch for featuring this breakthrough. techcrunch.com/2026/02/23/gui… #Steerling8B #GuideLabs #AI #MachineLearning
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Exa
Exa@ExaAILabs·
Introducing Exa Instant: the first sub-200ms search engine. Faster than Google, it's custom built to power realtime AI products like chat and voice.
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FlutterFlow
FlutterFlow@flutterflow·
High-quality screens in seconds. Use it standalone. Export to FlutterFlow. Whatever works for you. Oh, and it's free. designer.flutterflow.io Let us know what you think!
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Blink.new
Blink.new@blinkdotnew·
Introducing the first vibe coding platform that builds agentic AI apps. Build AI that thinks, searches the web, executes code, and completes tasks end-to-end. One-shots Cursor, Perplexity, Gamma, and more. In celebration of our launch, we're giving away a free month to everyone who replies. Repost and reply “Blink” below and we'll DM you the credits 👇
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Exa
Exa@ExaAILabs·
Introducing Exa 2.1 We scaled our pre-training and test-time compute by an order of magnitude, unlocking frontier search API performance for both fast and agentic search. Deep dive below:
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Stable
Stable@useStable·
Meet me in the middle 🤝
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Exa
Exa@ExaAILabs·
Introducing Exa 2.0 Breakthroughs in our AI research and engineering have enabled us to build both the fastest search API (<350ms) and the highest quality search on the market. Product and technical deep dive below:
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Albedo
Albedo@Albedo·
Bringing space closer to earth
Topher Haddad@TopherHaddad

ANNOUNCEMENT: Albedo is going all-in on VLEO systems For years, the space industry has competed on resolution, altitude, and scale — bigger optics, higher orbits, more satellites. But what if the next advantage doesn’t come from going higher, but from getting closer? We started @Albedo to build the next generation of Earth-imaging satellites. What we built to take better pictures became something much bigger: a way to operate reliably in Very Low Earth Orbit (VLEO) — 275 km above Earth, where drag and atomic oxygen used to make long-duration missions impossible. This breakthrough changed our focus. From this point forward, we’re no longer selling commercial imagery. We’re building the infrastructure that makes an entire orbital layer operational and scalable. Our full effort is going into building the systems that make sustained flight in VLEO possible. The economics of getting closer Satellites today operate in three established orbit domains: GEO - Farther MEO - Middle LEO - Closer VLEO is roughly half the altitude of LEO. Getting this close to Earth doesn’t just improve performance; it also changes the economics of space. Satellites in VLEO can: → Capture higher-resolution data with smaller, cheaper payloads → Maintain stronger downlinks and uplinks at lower power → Deliver faster latency for real-time applications → Maneuver dynamically to balance endurance, precision, and autonomy The physics are simple: signal strength ∝ range², and for two-way systems, performance ∝ range⁴. Halving the distance delivers roughly 4× the signal power — or 16× for two-way systems — enabling smaller optics, lower-power transmitters, and lower mass. These efficiencies compound. Smaller spacecraft mean lower build and launch costs, faster iteration, and more frequent refresh cycles — a new economic curve for every market that depends on satellites, with a similar compounding cycle that transformed cloud infrastructure and semiconductors. Clarity’s proof through Solar Max Our first spacecraft, Clarity, has been on orbit for seven months through Solar Max, the most demanding period of the solar cycle. Clarity is performing 12% better than design predictions in drag efficiency, has executed 150 km of controlled maneuvers, and has maintained strong power generation while its solar arrays are exposed to atomic oxygen — a reactive element that corrodes conventional spacecraft materials at hypersonic speed. We’ve also uploaded 12 flight-software updates while in orbit, adding novel control modes and solving issues in real time. Clarity was designed for an average five-year lifespan at ~275 km, proving that long-duration, low-altitude operations are sustainable with the right architecture. VLEO isn’t experimental anymore. It’s operational. Our reliance on satellites requires redundancy LEO is crowded and vulnerable. VLEO offers the opposite: a naturally self-cleaning layer that clears debris in weeks, not years. Everyday life runs on space: ATMs to national security. As launch costs fall and cadence rises, redundancy shouldn’t mean “more LEO” — it means adding a second layer in VLEO. In testimony to Congress last year, John F. Plumb (Former Assistant Secretary of Defense for Space Policy) warned that a high-altitude nuclear detonation could render LEO unusable for up to a year. Diversifying architectures ensures continuity of communications, intelligence, and warning missions even under extreme conditions. VLEO sits below the radiation belts and in a naturally debris-clearing regime, making rapid reconstitution assured. What’s next for Albedo We’re dedicating our full engineering and operations teams to VLEO systems: buses, integrated satellites, and turnkey missions. These past few years proved the physics. Now we’re scaling the infrastructure that will make VLEO the next productive, sustainable orbit in space. If you believe the next edge in space isn’t higher but closer, please reach out. More to come.

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Sam Bhagwat
Sam Bhagwat@calcsam·
we raised a $13m seed round from 120+ of Silicon Valley’s top investors for @mastra, the leading TypeScript agent framework
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Hunter Leath
Hunter Leath@jhleath·
Today, I’m thrilled to announce that @archildata is publicly available in preview. Infinite, shareable disks that are instantly connected to your data and radically simplify your system architecture. You can get access to the same high-quality data infrastructure that the frontier labs use with a single click right now.
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Stable
Stable@useStable·
🚀 WE’RE BACK 🚀 Stable is relaunching on @ProductHunt today... and we’d love your support. Share your thoughts and experiences with Stable at the link below. Your input helps us grow and improve 🫶 na2.hubs.ly/y0ZB5j0
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Sygaldry
Sygaldry@sygaldry_tech·
Sygaldry is thrilled to be spotlighted by @Inc! Learn more below about CEO and co-founder @ChadRigetti and Sygaldry's novel approach to applying quantum computing to AI. inc.com/claire-cameron…
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