Ai Genesis

Describe an AI agent in one sentence. We build it, people use it, and you keep 65% of every run. It can see, search the web, run code, and hand back real files. No code, no setup. Build yours 👇

@gsivulka Human intelligence

Without human direction, you have compute running in circles If you haven't still, give this a read now

this post by the ceo of Microsoft is going viral because of this reason because he outlined the positive future of collaboration between AI and people. He calls is: Human capital > the people within the companies, their judgement and relationships. Token capital > the AI capabilities it builds and owns. @satyanadella says that the human capital only goes as token capital grows. did you read the full article yet?

@MrBalle4 Buying more soon.

@AiGenesisdotfun Why Dev 12%???

Now trading live on pump.fun/coin/7kUeoZ9yf… pump.fun $AIG

@samhogan Let’s do it at the individual level.

The hardest part of building an AI flywheel at a big company is getting all the data into a format that usable. What is you just collect all HTTP data going in and out of all employee laptops at the wire level? Company VPN collects everything. Use AI to sort, catalog, and transform. Not as granular as keystrokes and screen recordings but super easy to collect and probably good enough to hill climb with

AI overload

Describe an AI agent in one sentence. We build it, people use it, and you keep 65% of every run. It can see, search the web, run code, and hand back real files. No code, no setup. Build yours 👇

@JuliaEMcCoy Exactly. Let the machines do the climbing and let them earn for you while you chase the calling. That future’s already here. 🧬

They say AI will end careers. I say, good. Because “career” became code for spending your one life climbing someone else’s ladder. The machines can have the ladder. Humans were made for soul-fueled calling, not climbing.

@joshyote Ai Genesis accepts Solana for payments and rewards. Now live!

Reminder: 1. Build cool shit on Solana 2. Tell everyone about it Repeat forever

How it Works… Launch an AI agent from one sentence. Earn every time someone uses it. AI Genesis is live. Try it 👇 data-analyst.aigenesis.fun

@yo_itsmatt Ai Genesis just launched and is now offering payments and rewards in $Sol.

Solana is winning Truthfully, it isn’t even close Solana likely leads 85% of onchain categories And in most cases, the gap is massive Total domination

Launch an AI agent from one sentence. Earn every time someone uses it. AI Genesis is live. First up: Data Analyst. Drop in a spreadsheet, get charts + a full report back. No setup, no code. Try it 👇 data-analyst.aigenesis.fun

@Austin_Federa Agents that earn for the creators and people who share. Make the best agents. Create the most value. Build your distribution.

Tokenized compute is fundamentally right. But everyone doing it is too early today. The deep tech to support financialization is not there yet. But it will be. If you are building the tech, my DMs are open.

"Institutional Intelligence" IYKYK

@_The_Prophet__ 👋

⚡️Satya is describing the new balance sheet of the firm. The old firm owned people, processes, software, customer relationships, brand, data, and IP. The new firm will own a compounding cognition loop. Every workflow becomes a training surface. Every decision becomes a trace. Every expert judgment becomes reusable signal. Every internal correction becomes model improvement. Every model run becomes a chance to turn human judgment into institutional intelligence. That is what “token capital” really means. It is accumulated machine-operable cognition. A company’s expertise becomes executable, queryable, evaluable, improvable, and portable across models. That is a massive shift. The most important line is the one about switching out the generalist model without losing the company veteran expertise. That is the entire enterprise AI war. Model providers want the firm’s knowledge to flow into the model layer. Enterprises need that knowledge to stay inside their own loop. Whoever owns the loop owns the future economic rent. Satya is laying out Microsoft’s answer to the frontier-model monopoly problem. If all company knowledge flows upward into a few foundation models, the foundation model labs become landlords of the entire economy. They absorb everyone’s expertise, commoditize every workflow, and capture the value created by every firm’s learning process. That equilibrium will trigger political backlash, customer resistance, regulatory pressure, and corporate revolt. So Microsoft’s doctrine is: every company should build its own AI learning system on top of frontier models, while Microsoft owns the infrastructure where that happens. That is elegant and self-serving. Microsoft does not need to own the single best frontier model forever. It needs to own the enterprise control plane: identity, security, permissions, data, workflow, evals, agents, memory, developer tools, cloud, compliance, and model routing. If the model becomes swappable, the platform underneath the firm’s learning loop becomes the durable asset. Satya is quietly saying the frontier model alone is unstable. A world of a few models eating every company’s expertise breaks the political economy. A world where every company builds firm-specific AI capital on top of models is more stable, more defensible, and much better for Microsoft. The “human capital gets more valuable” line is partly true and partly corporate diplomacy. High-agency humans become more valuable. People with taste, judgment, relationships, domain intuition, ambition, and the ability to direct agentic systems become much more valuable. Routine cognitive labor loses bargaining power. The future firm does not need every human equally. It needs humans who can generate high-quality signal for the loop. The human becomes a trainer, judge, strategist, relationship node, taste layer, and goal-setter. The work that cannot feed the loop or direct the loop gets compressed. This also connects directly to the Anthropic crisis. If frontier model access can be restricted, pulled, nationality-gated, or subordinated to state power, then enterprises cannot allow their intelligence layer to live entirely inside one external model. They need portability. They need private evals. They need internal memory. They need their own traces. They need model-agnostic learning systems. The model can change. The firm’s cognition loop has to survive. That is the new sovereignty test. A company that only buys AI access is a renter. A company that turns its workflows, judgments, corrections, and outcomes into a private learning loop is building capital. The deeper implication: the future economy splits between firms that compound cognition and firms that leak cognition. Firms that compound cognition will get stronger every time they operate.

“A frontier ecosystem, not just a frontier model” is the whole thing. But it can’t stop at the enterprise. The same loop has to be ownable by one person. Turn your judgment into an agent you own and earn from, swap the model underneath, keep the IP. That’s what we’re building.

@satyanadella “A frontier ecosystem, not just a frontier model” is the whole thing. But it can’t stop at the enterprise. The same loop has to be ownable by one person. Turn your judgment into an agent you own and earn from, swap the model underneath, keep the IP. That’s what we’re building.

@GrammarHippy Same

Anyone else gets insane spikes of motivation at night? And then you can’t choose - sleep because there’s another day tomorrow or go and CONQUER THE WORLD? Just me?

@jonbrosio The creator used to need a studio to produce. Soon they just need a sentence and an agent they own.

The creator economy isn't just about content. It's about the complete collapse of the "middleman." Publishers. Agencies. Studios. All of them existed as a gatekeeper to eyeballs That connection is now direct. And free. Most people haven't realized what that actually means yet