Vinod Valloppillil

Some things I learned working at Microsoft: 1/ large numbers everywhere. $100M ARR service isn't even a footnote on executive slide decks. Leadership time is too valuable, come back when you're $1B+. Msft ecosystem is so rich that $1B+ sales are common (it's ludicrous how much work goes into closing these). Azure has ~250 services, some are a few mil and stagnant, others in hypergrowth, some are cash cows, you see every quadrant of the growth-share matrix. Imagine the imperial navy with ships of vastly different sizes as far the eye can see 2/ more on immense scale-- the smallest of Azure services run on 10K+ VMs. Large services run on 1M+ (some maybe 10M+ VMs, idk). Msft is stamping one new datacenter into the ground every four days (!!!!), a bewildering rate. Demand is so high, even with all this buildout we're forever capacity constrained. Azure brings in $100B in revenue and is growing 40%+ annually (at this size!!) There are ~225K msft employees. You almost have to think in scientific notation, 10^4 is a tiny number here 3/ msft is totalitarian re serving the customer. It's counterintuitive to outsiders, but the warts in msft products fall out of this culture. For example, it would be easy to improve the Azure Portal. But in all my time working with customers and partners here, I haven't heard even one person complain about the portal UI. Msft invests $0.00 dollars in anything that doesn't serve the customer and is completely unapologetic about downstream implications of this mindset 4/ msft can reshape itself overnight (when it has the will). People argued whether we waited too long to adapt after Storm-0558/Midnight Blizzard hacks (with the benefit of hindsight, we definitely did). But once the leadership team privileged security, everyone's job changed in two weeks. LT tied every engineer's comp to security, centralized reporting of embedded security teams, every org reshuffled its roadmap. Within days everyone was pushing PRs with security fixes. I would have thought it inconceivable to mobilize 200K+ employees this fast 5/ Azure is complicated. Postgres depends on compute, networking, AKS (or EKS for you aws people), secrets, etc. AKS depends on compute, networking, some datastore (probably Cosmos but idk), a dozen other things. Cosmos depends on... you get the idea. When anything breaks, everything above can break too. Some construction crew accidentally cuts a fiber cable in Brazil South, or a dedicated hardware compression chip browns out in storage, or compute failure rate in west eu spikes for some reason, or a million other failure modes. Msft is relentless about improving this, idk exactly but fully loaded probably 50% of engineer time goes into resilience 6/ re lifers who work 20+ years here, SV sneers at this but I now see it differently. I was once on the bridge debugging some IO issue, we call storage, the guy diagnoses it in about a minute, we chitchat, turns out he built NT asyncio support. Or same story but with networking, the guy built NT tcp/ip stack. I used to have a boss here, we were bumping into some problem, she casually goes oh yeah, we hit that when I was working on .NET bytecode. The ex-DEC VAX/VMS database engineers built SQL Server, some are still here. I love bumping into these people 7/ I never *really* understood distribution until I got here. As an example, our team had a customer in Seoul w/ a deep performance problem. We had to fix it to unlock one of these giant contracts. We don't speak Korean, they don't speak English. Of course msft has specialists in Seoul who get to the customer site before you could even get on a plane. There is an office in every major city, a relationship with every major entity, legal experts in every jurisdiction. You can reach these ppl instantly. Claude tells me msft has ~180 offices in ~100 countries (!!) U.S. government has ~270 consulates in ~170 countries. So msft outposts aren't quite as vast as U.S. diplomatic network, but pretty vast 8/ in the 90s everyone was afraid of msft. The lore is that BillG was ruthless. He'd clone you, beat you via ecosystem/distribution strength, and moreover make the ecosystem stronger with the new product. I wasn't there to compare, but msft of today is ruthless about winning, has the will to adapt, and has the wherewithal to undertake colossal projects. Ppl see Teams bugs or whatever and completely misread the signals. Teams is less polished than Slack because msft doesn't care one iota about polish. It cares about winning, and is frighteningly good at it. Underestimate at your own risk

Announcing Today - a team knowledge base, curated by Copilot and agents - powered by SharePoint! Finally, the tech is here to build a feature I've dreamed of for a long time! Excited to see early adopter feedback. techcommunity.microsoft.com/…

Let the query decide: Introducing "auto", a new retrieval reasoning effort mode in Foundry IQ that recovers 97.6% of the evidence recall of the highest effort level while using 46.9% fewer query planning tokens. techcommunity.microsoft.com/…

Not sure if people realise Starlink has an incentive to sell any unused satellite capacity at anything above $0 in areas where constellation is not fully utilised... otherwise the satellites would generate no revenue when passing over those areas. Prices (adjusted for service quality) will undercut incumbents in countries with cheap but poor coverage (Africa, Asia..... India...) This is a massive contrast to the unit economics of terrestrial fibre/cable...

New Apple paper basically says progress in automated ML engineering has come from models and runtimes rather than the scaffolding built around them. It finds one well-prompted coding agent with shell and file access matched or beat 4 multi-agent ML systems, so skip the orchestration and start with a single session. Those systems add search trees, memory layers, and specialist agent teams. They were designed when a model could only write code, not run it. This paper re-ran every wrapper on 1 codebase with the same model, hardware, and 24-hour budget. Giving the model a shell instead of a chat box was the only change that clearly mattered. With GLM 5.2, the minimal agent medaled on 62.5% of Kaggle tasks against 47.1% for the best published harness. Adding parallel agents and a message channel actually dropped its medal rate from 55.7% to 33.3%. – arxiv. org/abs/2609.40303 Title: "How Much of a Harness Does a Strong Agent Need for Autonomous ML Engineering?"

Graphlit went offline yesterday. Five years. 50+ integrations, a temporal knowledge graph, durable agents, paying customers in production since 2023. The product worked. The business didn't. Both are true. Agents are still only as good as their context. That problem isn't going anywhere. The tech and IP are still available as an asset purchase, for now. Thank you to everyone who built on it.

We're launching the most accurate real time transcription model in the world... #1 !!! 55% faster and 60% cheaper than ElevenLabs. Come build agents on our platform!

In RAG there's a tug of war between outer and inner context. Do we imbue a chunk with context from the parent document? Or just the one sentence that directly answers a specific question? Knowledge isn't flat answers to questions. But layers of broad context / narrow specifics

i dont think post-training will make md files redundant i want to be able to read what my agent is working with and check if it makes sense (legibility) model weights are a black box. you cant read through them and check what the model has learned think about all the decisions in a company and how they depend on each other when you work with other people (or agents), you want those decisions and relationships written down somewhere so you can check them and agree on what they mean of course some procedural skills may become less useful. but you still need a surface where you map out what you know in a way thats verifiable for you pretty sure markdown will stay because its a format that both humans and agents can read, inspect and edit we just need to stop writing slop into md files context needs to be highly curated and checked against your actual expectations and understanding linked and TYPED markdown files let you model your knowledge / understanding in a graph damn it, just stop writing slop and start modeling your knowledge

Now that raw model performance isnt the biggest driver of usage anymore $MSFT has the perfect chance to be the “Muse” of enterprise as they can put together a product with the best harness and integrations. While $META has the strongest distribution with consumers, $MSFT has it with enterprises.

I’ve seen a couple of posts about this so wanted to demystify. Today, every Muse user gets a free computer in the cloud. It's a real computer, and we’ve designed the security architecture of the Muse Secure VM carefully so you and your Muse can do almost anything you could with a computer sitting under your desk while keeping you and the system safe from threats like prompt injection. We wrote about this at length in our security blog post – security.muse.ai. Activity in the “runtime cell”, which you share with your Muse is unfettered, but sensitive actions are all overseen by the Sentinel, which runs outside of that cell. Similarly, all sensitive secrets - like the passwords you enter into Muse’s secure credential storage - are also stored outside the runtime cell. The runtime cell gets its own root filesystem (including a full Ubuntu linux image) separate from the host filesystem where your other more sensitive data lives. Because it is isolated from the sensitive stuff that runs on the same box, this means that we can, and do, offer users full visibility and control over the files in the runtime cell. Just as you can when you install Linux on your home computer, you can poke around and see all the files that make the system work - both debian system files and the binaries and data files that implement the parts of Muse which run in the runtime cell. This was a very deliberate choice - your Muse Secure VM truly is your own computer in the cloud. You can install software in it, write and compile code, use the browser to surf the web: it is your own Linux box that you can operate as you choose with your Muse. Poking around in this computer doesn't give you any privileged access to Meta infrastructure, or to other people's data If I may geek out a little here for a second… As a kid I loved to take things apart to see how they worked. As a teenager I got into computers and soon found myself drawn to C:\WINDOWS\SYSTEM and the system registry, later Slackware’s /dev/, /proc/ etc – I could see how the system was laid out and as I explored what DLL files and .so files actually did, I gradually became able to meld the computer to my own will. We’re really proud to be able to put a real computer in millions of people’s hands with a similar level of transparency. We built a file explorer right into the Library tab of the UI. We want you to be able to see the markdown files Muse writes while it thinks about how to serve you better, and explore the internals of the system if you’d like to. So, when you ask your Muse to show you its entire filesystem, and receive gigabytes of files you’re seeing the full contents of the runtime cell. It’s yours to explore and enjoy! If you’re not a geek like me, or simply want to download the data that you personally have created directly with your Muse, we added a feature for that too in Settings > Data controls > Download your agent data.

Ben Thompson calls Meta's Muse a bearish signal for the frontier labs, because a not-state-of-the-art model now makes a product stickier than any chatbot "The key for the frontier labs, then, is to build those user touchpoints while they have superior capabilities." "However, this is where Meta's recent launch of Muse is a bearish signal. Muse is, by a significant margin, the best and most approachable personal agent product I have tried." "Meta deserves a tremendous amount of credit for the product work they have put in, as well as the massive infrastructure commitment entailed in providing users with a very capable virtual machine for free." "Oh, and of course they deserve credit for the Muse Spark model undergirding Muse." "That noted, Muse Spark 1.3, the most advanced Meta model, is still not state-of-the-art, and that is the bearish signal: it is good enough for a very good personal agent product, and critically, a personal agent is much stickier than a chatbot." "Once you have put all of your information into a personal agent and actually incorporated it into your day-to-day life, it is much more of a challenge to change to something else."

We’ve raised $80 million in Series A funding, co-led by the Valor Atreides AI Fund and Hummingbird Ventures, with continued participation from Conviction, Abstract, A*, and Grant Gordon. This brings our total raised to over $100 million. We started Watney by asking a simple question -- what can a robot enable in industries where the work remains valuable on an infinite horizon? We found an answer in the fundamental inputs to civilization: energy, matter, and intelligence. A robot will never be as charming as a barista or as personable as a housekeeper, but it can be more exacting than a surgeon. And, a breakthrough in one quickly becomes the capability of millions. We don’t imitate human motions or processes. We care about the new, differentiated capabilities robots can unlock. We work on problems where our choice of embodiment gives us an order of magnitude advantage, whether through precision, reliability, or scale. Compute is just beginning to transform society, but it’s constrained by execution. Since 2025, Watney has been serving the largest hyperscalers in the world, helping accelerate their compute rollout through an end-to-end deployment model. Across hundreds of thousands of hours in customer facilities, our systems have achieved more than four nines of reliability. They’ve enabled our customers to build data centers faster, at larger scales, and with more ambitious architectures. Today, we operate the largest fleet of dexterous robots running 24/7/365 across the United States. This is all to say, it's an exciting time at Watney. We’re all here because we want to see more ambition in the physical world. We are hiring across all domains. Join us.