Inflectiv AI ⧉

We told you something was coming! Agent Vault is live. Encrypted credentials. Sandboxed agents. Full audit trail. The security layer your AI agents were missing.

@dee_bosa This move builds a software moat that is harder to bridge than raw hardware speed. If your entire agentic workforce is built on the NemoClaw stack, switching to competitors like Groq becomes a massive "friction tax."

Jensen Huang doesn't need a new chip. He needs a new moat. Nvidia's most ambitious move from GTC was NemoClaw --a free, open-source AI agent platform designed to keep every company dependent on Nvidia's computing power, even as the chip competition heats up Nvidia is becoming an operating system. The market is still pricing it as a chipmaker. w/ @jaswu_

@Cointelegraph Maintaining the open-source status of these tools is a critical trust move for the developer community. It ensures the infrastructure remains a global standard while OpenAI builds its proprietary layer on top.

⚡️ NEW: OpenAI plans to acquire startup Astral as it expands further into AI developer tools.

@kimmonismus Codex’s trajectory is striking: 3× user growth, 5× usage, and already over 2 million weekly actives. The intensifying Claude vs Codex fight underscores Dario’s point, owning the coding layer could decide who leads the broader AI ecosystem. Exciting to watch unfold.

OpenAI's Codex is becoming increasingly popular: 3x user growth and 5x usage increase since the start of the year, and over 2 million weekly active users. The battle between Claude and Codex is intensifying, because, as Dario already said: being the best AI company with the best coding tool is the foundation for overall victory.

@AlbaAdventureNY @GoldmanSachs Sure, to name a few: Data Center Construction & Skilled Trades Critical Facilities & Operations Engineers Power & Electrical Infrastructure Specialists Renewable Energy & Sustainability Integration Energy Strategy & Off-Grid Power Roles Related Infrastructure & Support Roles

@inflectivAI @GoldmanSachs Which categories? Care elaborate?

According to Goldman Sachs Research, 300 million jobs globally could be exposed to AI automation over the next decade. However, AI is also likely to help create jobs—particularly in the buildout of the power and data center infrastructure required to sustain the boom: click.gs.com/t3et

@Savvy_8969 🧡🤝

@inflectivAI Security layer like this is essential going forward

Introducing AVP - Agent Vault Protocol. AI agents run with unrestricted access to your credentials, API keys, and secrets. No scoping. No audit trail. No revocation. Today we are open-sourcing the fix 👇

@kingsleydick_ Indeed, thank you, Mr. King

@inflectivAI This brings much-needed control to AI agents

@friday_mic19510 Can't agree more, Michael

@inflectivAI Proper key management is long overdue

@heisgabe_ Absolutely🙂

@inflectivAI Finally a focus on safe agent execution

@GloryJacob22320 🧡

@inflectivAI Open-sourcing this makes it even stronger

@ImKingGinger Spot on observation. Genuine creatives are treating AI like a superpower that unlocks ideas they couldn’t reach before. The pretenders who’ve lived off the “creative” label are being quietly exposed because they never had the inner vision to begin with.

Every creative person I know that has embraced AI as a tool for their art has produced more content this month than all of last year. A true creative individual sees AI and feels completely empowered. They feel like the entire world has opened up to them. But a lot of self professed creative people, who have been grifting as creatives for decades, are about to be exposed as frauds who and pretenders who only know how to work within the politics of the current system. They will sit down before the greatest tool for creativity the world has ever known and not have a single idea how to use it or what story to tell. Pay attention to what is happening and who rejects the gift, and who embraces it.

@aakashgupta This is a sharp observation. OpenAI acquiring Astral right after Promptfoo shows they’re systematically buying the hardest parts of the dev workflow, everything that surrounds code generation. The wall just got a lot lower.

The real story is what Codex couldn’t do until today. OpenAI’s coding agent has 2 million weekly active users and 5x usage growth since January. It can write functions, fix bugs, and run tests. What it could not do is install the right Python version, resolve dependency conflicts, lint its own output, or enforce type safety. The four tasks that consume more developer time than writing code. Astral solved all four. Ruff lints 250,000 lines of code in 0.4 seconds. uv installs packages 10 to 100x faster than pip. ty type-checks faster than Mypy by orders of magnitude. 81,000 GitHub stars on uv. 46,000 on Ruff. Tens of millions of monthly downloads. The company raised $4 million. A seed round and nothing else. This is the second open source developer tools acquisition in ten days. Promptfoo on March 9 for AI security testing. Astral on March 19 for the Python development lifecycle. Both companies had millions of users. Both promised to keep the open source open. Both teams are joining specific OpenAI product divisions. The pattern is clear. Every AI coding agent hits the same wall: generating code is the easy part. The hard part is everything around the code. Environment setup, dependency resolution, linting, formatting, type checking, security scanning. Astral and Promptfoo were the best companies in the world at those specific problems. OpenAI just bought the wall.

@tmrohan That’s a sharp distinction. Humans pick software based on feel, intuition, and personal taste, AI picks purely on measurable performance and specs. It explains why human teams still cling to “messy” tools that just feel right.

Software chosen by humans is about taste. Software chosen by AI is about function.

@TukiFromKL Wow, Cursor building their own model and beating Claude Opus on coding benchmarks is a serious flex. A 50-person team out-executing massive labs at their core strength shows how fast the playing field is shifting.

🚨 Cursor just dropped Composer 2.. their own AI model.. not Claude.. not GPT.. their own.. and it beats Claude Opus on coding benchmarks.. at a fraction of the cost.. a code editor with 50 people just outperformed a $30 billion AI lab.. at coding.. which is supposed to be their whole thing.. the vibe coding era just got an upgrade..

@DeRonin_ Strong point. Over-optimization without foundation creates fragility. Companies that keep “human in the loop” as a slogan while quietly automating the loop itself are proving it. The real value is in the thinking that survives when the tool is turned off

🚨 The more AI you use now.. the less you're worth later. Chess proved it 30 years ago > In 2005 two random amateurs with laptops beat grandmasters AND supercomputers.. just by combining human thinking with AI. Everyone celebrated. Human + machine = unstoppable. The future of work. The golden era > That era lasted 15 years. By 2026.. adding a human to a chess engine makes it play WORSE. Not better. Worse. The human became the bottleneck. That "human in the loop" thing your company keeps bragging about? Chess already proved it expires > But here's the part that should keep you up tonight. Magnus Carlsen.. the greatest chess player alive.. deliberately uses AI LESS than his competitors > Everyone else memorizes 30 moves deep into machine-generated theory. They show up overprepared. Overoptimized. Over-reliant > Then Magnus plays something unexpected.. and they collapse. Because their preparation was rented. Their understanding was surface level. They knew WHAT to play but never learned WHY. The second the game left the script.. they had nothing > Now look around you. This is happening in every single industry right now. Junior devs shipping code they can't explain. Marketers publishing strategies they can't defend. Founders pitching decks they didn't think through > Everyone is faster.. nobody is smarter. And it shows the moment someone asks a question that isn't in the prompt > The current world champion trained for YEARS without engines. No shortcuts. No automation. He built his thinking from zero.. and that's exactly why he uses AI better than anyone today. Because he actually has something to combine it with. Most people are combining AI with nothing > "Did they write that?" "Did they build that?" "Did ChatGPT solve that?" Nobody can tell anymore. So the question is changing. It's not "what did you produce." It's "can you think in front of me right now.. no tools.. no second monitor.. just you." The people automating everything are training themselves to be dependent on something that gets cheaper every month And when it gets cheap enough.. the company won't need you to operate it anymore Because everything what big companies and models need from you — YOUR UNIQUE KNOWLEDGE Amazon and Meta have already proved it too when fired 50,000+ employees who were taking an active part in their AI learning Just ask a question to yourself: "Who are you without AI? Why do you need if one day AI will not exist anymore?" Stay safe.

@aiedge_ This is a sobering but well-reasoned piece. The circular financing angle really stands out, it's not just hype, it's a structural loop that's been propping up valuations. Your point about the cracks forming at Nvidia, OpenAI, and Microsoft feels timely and hard to ignore.

@r0ck3t23 Love this framing. You stay ahead by turning model outputs into new situational knowledge the models can’t yet capture. Smart way to remain indispensable.

Microsoft gave OpenAI everything. $13 billion. Exclusive cloud rights. Enterprise distribution. The infrastructure that turned a research lab into the most valuable AI company on Earth. Sam Altman just signed a $50 billion deal with Amazon. When Microsoft first invested in OpenAI, they locked in one condition above everything else. Every API call. Every model access. Every enterprise deployment. All routed through Microsoft’s Azure cloud. No exceptions. It was the smartest infrastructure play of the decade. Azure became the toll road for the entire AI revolution. Then OpenAI handed Amazon the keys to Frontier, their new enterprise AI agent platform. $50 billion. AWS becomes the exclusive third-party cloud provider. $138 billion committed to Amazon cloud services total. Microsoft responded with what amounts to a declaration of war. “We know our contract. We will sue them if they breach it. If Amazon and OpenAI want to take a bet on the creativity of their contractual lawyers, I would back us, not them.” OpenAI’s defense is a technical workaround called the Stateful Runtime Environment. Their argument is that it only handles memory and context for enterprise data on AWS. It does not technically invoke OpenAI’s core models through Amazon. Therefore the Azure exclusivity clause does not apply. You can tell Amazon knows how thin that argument is by what they did next. An internal memo leaked showing Amazon coaching employees on exactly which words to use. Frontier is “powered by OpenAI.” “Enabled by OpenAI.” But employees were explicitly told they cannot say customers can “access” or “invoke” OpenAI models on AWS. When you are coaching your employees on which verbs to avoid, you already know where the line is. And you already know you are standing on the wrong side of it. But here is why Altman did it. Microsoft launched Copilot. Built their own models. Started hiring their own researchers. The company that funded OpenAI’s entire existence began quietly building the infrastructure to replace it. Altman watched his biggest partner become his most dangerous competitor. So he did the only rational thing. He did it back. Both sides were preparing for divorce while still living in the same house. The Amazon deal was not a betrayal. It was an insurance policy against the day Microsoft decided it no longer needed OpenAI. Microsoft caught him packing his bags. Now the leverage runs in both directions. OpenAI is planning an IPO. They just closed a $110 billion funding round. Elon Musk is already suing them separately for abandoning their nonprofit mission. If Microsoft files suit, the IPO is in jeopardy. You cannot go public while your largest investor is suing you for breach of contract. Two active lawsuits from two of the most powerful figures in tech against a company trying to execute the most consequential public offering in Silicon Valley history. But Microsoft has billions riding on that IPO. Sue OpenAI and they threaten the S-1. Threaten the S-1 and they torch the value of their own asset. Altman did not just pivot to Amazon. He built a situation where his biggest threat cannot pull the trigger without shooting themselves. This is not a breach of contract story. It is a story about what happens when the most important AI partnership in history quietly becomes a cold war. And one side realized they were already holding the weapon.

@fchollet The transition to "Active Learning" means AI now prioritizes experiments based on which test will yield the most new information. This collapses the time spent in the "unknown" from years to days.

Current AI is a librarian of existing knowledge. Science requires an explorer of the unknown. You don't win a Nobel Prize by staying in the library.

@danshipper This perspective is refreshing. It flips the usual fear narrative: instead of being replaced, you can stay ahead by continuously building new expertise on top of what the models produce. The gap between model training cycles and human adaptation speed is the real moat.

How to never lose your job to AI: Just surf the models. Frontier models outclass humans at any form of knowledge that can be written down. But people who use frontier models in their field of expertise generate new, tacit, situational expertise that the models don't yet have—because the models can't be trained on how they will be used in the future. Humans can learn to use new models faster than new models can be trained that absorb what they find out, so you can continually "surf" on top of the model's intelligence to generate new expertise. This is a fundamental limitation of LLMs because they don't learn past their training data. Even few-shot learning doesn't account for this because whatever can be codified into a few shot prompt needs to be used in the correct situation—and this will always stay uncodified in the general case. Just surf the models. Reap the benefits of a totally new world.

@virtualfilmer @GoogleAIStudio

@inflectivAI @GoogleAIStudio Another bot reply

@berkay_secil The shift from "better prompts" to "better autonomy" is the defining transition of 2026. We are moving out of the era where we talk to AI and into the era where we collaborate with it as a general-purpose digital worker.

Agents are getting smarter every week. The next breakthrough probably won’t be better prompts. It will be better autonomy. What do you think comes next for AI agents?