The "slop" is evolving. This is my favorite music video so far. Grok + Suno + Runway

Introducing Grok Bot, now in early beta. Bots are AI teammates that do real work for you. They sign in to your tools, use them just like you do, and come back with finished work.

This is what entrepreneurialism feels like. xitter.cf/tannokasa9/status/2079…

I had dinner with a group of operators, founders, and investors who are actually deploying AI inside real companies. We're talking 9-10 figure revenue companies. The best question I asked was simple: What part of the company would you rebuild from scratch if AI were native from day one? The answers were way more useful than another model launch thread. A few things stood out. The serious operators are moving past the model debate. They care more about data access, permissions, memory, routing, evals, and human review. A smart model with messy company context is still a mess. A decent model with clean data and a tight workflow can make money. The first margin wins are boring. Customer support containment, document processing, accounting workflows, sales prep, call center context, recruiting ops, campaign analysis. That is where the money is right now. Manual work ↓ AI drafts / routes ↓ Human checks exceptions ↓ Cost drops ↓ Capacity rises AI creates capacity before it creates clean headcount cuts. That is the part most leaders will waste. A team saves 10 hours, then spends 8 of them in more meetings. Congrats, you bought a Ferrari and drove it in a parking garage. The better question is: If this role were designed today with agents available from day one, would it still look the same? That question gets uncomfortable fast. The org chart is shifting from people management to workflow ownership. Old model: Manager ├─ analyst ├─ specialist └─ coordinator New model: Workflow owner ├─ agents ├─ tools ├─ data ├─ QA loop └─ outcome That person is closer to a mini-GM than a prompt engineer. They understand the business goal, wire the tools, inspect the output, catch bad answers, and improve the loop. Compensation is going to get awkward too. If two people have the same title but one can produce 5-10x more output with AI systems, they are no longer doing the same job. Companies can keep forcing them into the same salary band. That will work until the AI-native person realizes they are carrying the operating system. Recruiting also gets weird. The easy part is using AI to source, enrich, personalize outreach, screen, and summarize. The hard part is evaluating talent when AI is part of the work. Do you test people with AI? Without AI? Both? Do you grade the final output, their prompts, their taste, or their ability to catch bad model answers? The future interview will look less like a whiteboard puzzle and more like: Show me how you think with tools while I watch your judgment. One underrated point from the dinner: LLMs should not do everything. If the job is math, rules, constraints, or calculations, use software. If the job is synthesis, communication, ambiguity, or judgment, use the model. Human asks ↓ LLM understands intent ↓ Tool/database runs ↓ LLM explains ↓ Human decides The best AI systems will be less magic, more plumbing. That is a compliment. For agencies, the implication is obvious. The old pyramid gets squeezed. A strong AI-native marketer can now own strategy, research, execution, reporting, iteration, and client communication with a much smaller support layer. The agency model moves from labor layers to outcome owners. The dentist model wins. High-skill human at the top. Systems underneath. More judgment per person. AI makes average execution cheaper, but it makes great judgment more valuable. The premium moves to people who can ask better questions, build better workflows, spot bad outputs, manage agents, understand context, communicate clearly, and move fast without creating chaos. The weak version of AI adoption is giving everyone a chatbot. The strong version is redesigning the company around workflows, data, permissions, evals, and AI-native operators. Most companies are still playing with prompts. The serious ones are redesigning the entire machine. with @jonathangold_ , @APompliano , @ArmanHezarkhani , @matthew_kruer , @bbourque , Joe C

Palantir's CEO just exposed Sam Altman and Dario Amodei for robbing every Fortune 500 company. Within two minutes, Alex Karp took the entire frontier AI industry apart on national television. His exact words: "Every single enterprise in this country, these people are LIVID. They are paying for tokens that create no value. These people are stealing the weights and alpha of my business." He literally said the entire frontier AI business model is intellectual property extraction dressed up as a subscription. Then he also destroyed the pricing model with a single question that Silicon Valley still refuses to answer: "If it was so valuable, let's say I can make you $1 billion tomorrow. Wouldn't I say I'll make you $1 billion and I want 30 percent? Why are they charging for tokens if it's so valuable?" That question breaks the industry. If OpenAI and Anthropic's models truly delivered the productivity gains the labs claim, they would take equity or a share of the profit they generate. They would not sell access by the million tokens. Token pricing is itself the CONFESSION that the product cannot produce reliable value at scale. If it did, they would price for the value. But they price for the compute because that is what they are actually selling. Karp went even further... He called the entire arrangement "a wealth tax that does not help the poor. It just punishes." American businesses are transferring the alpha of their operations, meaning the workflows, the customer data, the strategy memos, the internal models that make them competitive, directly into the training pipelines of a handful of Silicon Valley labs. Once those labs retrain, the customer's own edge becomes the next enterprise product sold back to their competitors. And the part the AI industry does not want anyone thinking about: Every enterprise running its confidential documents, its customer conversations, and its financial models through a frontier model is potentially teaching that model HOW to replace them. The vendor collects the token fee AND the compounding intelligence about that customer's business. That is the mechanism. And that is why Karp used the word "stealing." He claims this is why every executive he meets is furious in private and silent in public. Nobody wants to be the CEO who called out the labs and then discovered their next competitor was built on their own leaked workflows. The entire AI industry has been priced for perfection on one assumption: That frontier labs produce durable, defensible value that justifies infinite compute spend. But Karp just told us that the customers do not believe that assumption anymore. They believe they are being taxed without benefit, watched without consent, and copied without recourse. The moment enterprises stop believing, the whole valuation stack shakes.