PrivOS

Welcome to the new era of Enterprise Operation with #PrivOS AI is everywhere, but very few companies are truly operating with it as a system. PrivOS is built to change that. PrivOS is an #AI Operating System for Enterprise that enables organizations to: - Connect multiple AI agents into unified workflows - Establish shared memory and context across systems - Control data access and permissions - Track every AI action with full auditability - Deploy AI in a private, enterprise-controlled environment

🚨 The hidden cost of using too many AI tools isn’t the subscription, it’s time and fragmentation 💸 According to the TechRadar report on SaaS spending (2025), $9,000 – $17,000 per employee/year on SaaS tools → And up to 50% is wasted due to redundancy and underuse 📉 According to the American Psychological Association, 20% – 40% of work time is lost due to switching between tools. **That’s roughly 1.5 – 3 hours per day of non-value work The highest cost of AI isn’t the tools; it’s the fragmentation of systems and employee attention 👉 More AI ≠ more productivity 👉 Better integration = real competitive advantage Don’t let tool sprawl drain your resources. Use #PrivOS to unify your AI workflows and eliminate hidden costs before they scale #AI #Productivity #BusinessStrategy #DigitalTransformation

@a16z “AI makes you the CEO” only works if you can trust your tools, your data, and your outputs. Otherwise you’re just scaling uncertainty.

"AI doesn't take your job. AI makes you the CEO." Balaji Srinivasan joins a16z’s Erik Torenberg for a conversation on the future of the AI economy, decentralization, and how work changes in an AI-native world, including: - How distillation and open source could decentralize AI power - Why AI lowers the cost of creation but raises the cost of verification - The shift from global internet to “trusted tribes” and private AI - Why humans are the sensor and AI is the actuator 00:00 Intro 02:06 Why you want AI inside the trusted tribe, not outside it 05:35 The Problem with AI slop 09:25 Where AI works 17:08 "AI can't read your mind, but it can read your body." 30:10 "AI doesn't take your job. AI makes you the CEO." 46:01 The SaaSpocalypse: Real or overblown? 49:19 What happens if AI companies get bigger than governments? @balajis @eriktorenberg

@XFreeze First it was data → then chips → now power. The AI race is becoming an infrastructure game.

Elon Musk reveals the real limiting factor for AI is not chips anymore, it’s electricity AI chip production is growing exponentially, but global electricity supply is only increasing 3–4% per year. We’re reaching the point where we produce more chips than we can actually turn on Power is the ultimate bottleneck in 2026. Data centers now face up to 7-year waits for grid connections, leaving many GPUs sitting idle Energy is the new oil of the AI race

Whether or not this specific story is real, the direction is clear: AI is getting better at extracting signals people never realized they were emitting. That’s exactly why privacy and security can’t be optional anymore. Systems like #PrivOS are built for a world where everything can become data.

I think this is the most insane thing the CIA has ever made public. 😨 They have a secret AI tool called Ghost Murmur. It detects your heartbeat from 40 miles away using AI. Not your phone. Not a tracker. Not a radio signal. Your heartbeat. It uses sensors built from synthetic diamonds to lock onto the electromagnetic fingerprint your heart produces every single beat, then pairs it with AI to filter that one signal from 1,000 square miles of noise. Last week, a wounded American pilot was hiding in a mountain crevice in Iran. No phone. No tracker. No way to call for help. America found him anyway. From the sky. By listening to his chest. But nobody mentioned the most important detail. This was Ghost Murmur's first operational use. It's been sitting classified for years. Tested. Ready. Waiting. They didn't reveal it to impress you. They revealed it because the rescue was already public. Every technology a government admits to is the one they've already moved past. Your heart has been broadcasting your location your entire life. Someone just built the receiver.

@Ric_RTP This is the key shift: from prevention → resilience. But resilience without control, privacy, and secure AI infrastructure is just damage management. #PrivOS is built for a different approach, AI systems that are secure by design, not patched after the fact.

Sam Altman just confirmed a world-shaking cyberattack is coming this year and nothing companies can do will stop it. The Axios co-founder asked him directly if a catastrophic cyber event was realistic in the next 12 months. Altman's answer: "I think that's totally possible. Yes." The CEO of the most powerful AI company on Earth just told the world to brace for impact. And his solution is NOT prevention. It's "resilience." That's the language governments use when they've accepted something bad is going to happen and they're now focused on surviving it instead of stopping it. Because the same AI that writes code for startups is about to write exploits for adversaries. Altman admitted the frontier models are already dangerously capable at cybersecurity. The next generation will be significantly more so. And once those capabilities leak into open source, the game changes permanently. But cyber isn't even the scariest thing he said: The real bomb came a few minutes later when he was talking about biosecurity. He said the models are getting extremely good at advanced biology and wonderful things will happen, like curing diseases that have killed people for centuries. Then he said this: "Someone is going to try to misuse those." And right now, the frontier models are still locked inside responsible companies with safety layers and classifiers. OpenAI can mitigate a lot of the risk because they control the stack. But open source is catching up FAST. And when it does, any group with an internet connection and enough compute can ask an AI to help them engineer a novel pathogen. Altman's exact words: "The needs for society to be resilient to terrorist groups using these models to try to create novel pathogens is no longer a theoretical thing, or it's not going to be for much longer." Let that sink in. And this is where the story gets completely insane... Because Altman's response to all of this isn't just "build better safety classifiers." His response is a policy blueprint that Axios editors called a "Bernie Sanders fever dream." He's quietly pitching it to Washington right now: It calls for rebuilding the social contract, redistributing the gains from AI, new tax structures, and fundamentally rethinking the relationship between labor and capital in an economy where a single person with AI can replace an entire team. The part nobody saw coming? Republican senators and a senior Trump cabinet secretary told him they agree. One of them told Altman directly that capitalism needs to be reimagined because "way too much leverage is going to be with capital and not with labor." The CEO of OpenAI is now selling Bernie Sanders economics to Republican administration officials and they're listening. Step back and look at the full picture now: The man building the most powerful technology in human history just admitted 3 things in one interview. 1. A catastrophic cyberattack is likely within 12 months 2. AI-enabled bioterrorism is about to become a real threat 3. The only solution he sees is a radical restructuring of capitalism that nobody in Washington is politically ready for He's not saying AI will change the world someday. He's saying the change is already here, the risks are already landing, and the institutions designed to protect us are years behind. Most people are still debating whether ChatGPT will replace their jobs. Altman is quietly telling Washington the real question is whether society can HOLD TOGETHER through what's coming next.

@andrewchen Makes total sense, when AI can generate perfect resumes and interview answers, the only real signal left is execution. The same shift is happening in security, too. You can’t just claim trust anymore. You have to prove it.

noticing a trend of startups replacing standard resumes/interviews with week-long (or at least 3-day weekend) in-office trials. Makes sense in a world of AI-generated resumes and interview responses Turns out the best signal for whether someone can do a job is watching them actually do the job. took us 100 years of HR to rediscover apprenticeships!!! 😂

@bubbleboi This is exactly the inflection point. When models can one-shot complex hardware logic like this, the risk surface expands just as fast as the capability. That’s why #PrivOS exists, AI this powerful needs security and privacy built in from the ground up.

Just got access to Claude Mythos… & ughhhhhhhhh this is AGI. It was the first time a model one shotted a 10/25G Ethernet MAC/PCS, it even knew to select the right line rate and data width for lower latency. This alone is something that would take a really skilled digital designer 3-6 months if they had experience in the past to pull off… But it didn’t just do that I then said to make the MAC fully cut through and only forward certain IP addresses within a range downstream it one shotted it instantly also which blew me away… Then finally I thought ok let me trip it up so I said now do 50G MAC and it knew without me telling it to add another GT transceiver and it even added alignment markers and FEC to it correctly. 💀💀💀 It’s passing all the tests I have so I’m going to flash the board and see if it actually works on hardware now…

@Cointelegraph A clear signal of where things are heading. As AI gets better at finding vulnerabilities, security has to move into the model layer, not just around it.

🚨 JUST IN: Anthropic has launched Project Glasswing with major tech partners to secure critical software using advanced AI capable of discovering high-severity vulnerabilities.

That’s exactly why security can’t be an afterthought anymore. With models advancing this fast, the real question isn’t just whether existing cybersecurity holds up, but who is building AI with security at its core. #PrivOS is built around that idea: privacy and security first, not patched on later.

$GOOGL's Sundar: "These models are definitely really going to break pretty much all software out there". I think the new sets of AI models from these AI labs that are coming out will be a real challenge for existing cybersecurity companies. Either their software holds up, or all these AI labs are going to put their own versions of cybersecurity software out there alongside the AI models they release to protect the world. We are facing another big leap in model capabilities.

@pmarca Only strong security can build real trust, that’s why #PrivOS, as an enterprise AI, puts it above everything else, ensuring data stays safe.

Every security flaw discovered by AI was there before AI, waiting to be discovered either by people or by AI. The world has never been good at securing computer systems; finally with AI we are going to get good.

@sama Woohoo—cheers to all the hard work from the dev team. Thanks, Sam! We will work harder to make AI better for every company 🫡

To celebrate 3 million weekly codex users, we are resetting usage limits. We will do this every million users up to 10 million. Happy building!

What does this mean for businesses? ⏰Faster execution, less manual work 💑Consistent decisions with better data 📉Lower cost from fewer tools 🧠Full control with private infrastructure 👉 AI doesn’t just assist tasks anymore, it powers your entire system.

Instead of using separate tools, everything in PrivOS is connected by design. - Data is unified - Workflows are continuous - AI has full context - No need for integrations or constant switching 👉 From fragmented tools → to a single operating layer.

#PrivOS is an all-in-one private workspace built as an #AI Operating System. It brings together: ✅Chat & team communication ✅Structured data (CRM, HR, inventory, tickets…) ✅Workflows & automation ✅File management ✅AI agents with context 👉 All in one system.

@pmarca So now it is currently unevenly revealed 🙂

I'm calling it. AGI is already here – it's just not evenly distributed yet.

@jyoti_mann1 Then still arguments about whether people should be afraid of AI 😂. Even engineers are competing on the token leaderboards, so who else should be afraid?

Exclusive: Meta employees are “tokenmaxxing” and competing on an internal leaderboard called “Claudeonomics” for status as a token legend. Over a recent 30-day period, total usage on the dashboard topped 60 trillion tokens.

@a16z One-man business is a real trend now. As Ai can pretty manage a lot in its hand, they can operate and execute tasks even more efficient than humans.

“Coding will eat all knowledge work” Peter Yang joins a16z’s Anish Acharya to discuss the post-AI future of work, why AI will create more solopreneurs, why human ambition means there will always be new jobs, and more. 00:00 Intro 01:56 Using OpenClaw for voice, memory & daily life 06:14 Will agents kill apps & SaaS? 11:57 Coding agents: Claude Code vs. Codex 17:00 Future of work: small teams, agents & company culture 24:00 How agents change consumer products & the economy @petergyang @illscience

@RoundtableSpace Can't stop being surprised by what AI can do nowadays. Imagine how a studio can outperform if they deploy AI into its tasks now. More efficient, and more time saving.

AI JUST MADE AN ANIME CLIP THAT WOULD’VE COST $500M TO PRODUCE THE OLD WAY. Now it can be done in a week for under $500, and that should scare every big studio.

@heygurisingh Probably it is just efficiency problem

🚨Carnegie Mellon just proved your "reasoning" model doesn't actually reason. They tested 14 of the top LLMs (GPT, Claude, Gemini, all of them) on 500 problems where surface-level keywords conflicted with basic logic. Not a single model scored above 75%. On problems requiring the model to notice a missing object, accuracy collapsed to 44%. Here's the part that should terrify every AI lab: When researchers measured what the models were actually paying attention to, a single surface keyword (like "distance") influenced the answer 8.7x to 38x MORE than the actual goal of the question. The models weren't reasoning. They were pattern-matching on vibes. It gets worse. 12 of the 14 models performed WORSE when the hard constraint was removed, dropping up to 39 percentage points. They're not solving problems. They're guessing conservatively based on keyword associations they saw in training. The paper calls this "heuristic override." In plain English: every time a salient keyword shows up in your prompt, the model hijacks itself and ignores what you actually asked. The fix? A single hint telling the model what to focus on recovers +15 points on average. Translation: these models know the answer. They just refuse to think unless you beg them to. Every benchmark bragging about "PhD-level reasoning" needs an asterisk now. Paper: "The Model Says Walk: How Surface Heuristics Override Implicit Constraints in LLM Reasoning" (CMU, 2026)

@ns123abc The field is fierce, @OpenAI is something that no one could have reached a few years ago, but now @AnthropicAI does it after a couple of years. Tons of AI systems are currently underdeveloped, but they're about to change that again. We are in a race 🐎

🚨BREAKING: ANTHROPIC RUN-RATE REVENUE JUST SURPASSED $30 BILLION >anthropic ARR: $30B+ >3.3x growth in four months >openai ARR: $25B Anthropic has officially defeated OpenAI as the revenue leader Dario WON.