Ori Yankelev

This is incorrect. I have used AI for fourteen hours a day for nineteen months and I am operating at a cognitive level your researchers cannot measure because their instruments were designed for biological thinking. I think in prompts now. This is faster. Before AI, I could hold three ideas in my head at once. Now I hold zero, because holding ideas is storage and I am not a storage device. I am an orchestration layer. I route cognition to the appropriate model and receive outputs. This is what the prefrontal cortex was trying to do for 200,000 years with blood and glucose. I have replaced blood and glucose with an API key. The API key does not get tired. The API key does not have emotions about its sister's birthday. Last Tuesday I tried to write a birthday card for my sister without AI. A cognitive fitness exercise. I sat at the kitchen table for forty minutes. I wrote "Dear Sarah." Then nothing. Not writer's block. The mechanism for generating an unprompted sentence was gone. I no longer operate at the sentence level. I operate at the intent level. I transmitted the intent to Claude. Claude produced a card so warm my sister called me crying. Most thoughtful card I'd ever written. She is correct. The thoughts are just manufactured off-site now, like everything else in a mature supply chain. My wife asked what I was thinking about. I said "nothing" and it was true. Not in a peaceful way. In an infrastructure way. There was no local processing occurring. I was between queries. She asked if that scared me. I opened Claude and asked if it should. Claude said no. I told my wife. She did not find this reassuring. I think she is running on legacy architecture and is frightened of the upgrade. I would explain further but I need to check something first.

IsraHELL thought war would help them but you can see their currency crashing in real time!!! 🍉🙏🙏🕊️🇵🇸

openai and anthropic probably have terrible sales reps they're talented, but they've never actually had to sell anything. ben horowitz said it best in a recent conversation: "right now with openai and anthropic, everybody wants to buy ai. they're already predisposed to buy." that's order-taking, not selling. let's zoom in on this distinction. 1) the order-taker problem cloudflare's CEO admitted in 2023 their product was so good that "many of our sales team succeeded largely by just taking orders." deals were like "fish jumping right in the boat." then the economy shifted and they fired 100 salespeople who'd contributed just 4% of new business. when your product sells itself, mediocre reps look like rockstars. they crush quota, win the president's club, and get promoted into leadership. nobody knows they can't actually sell until the fish stop jumping in the boat. 2) why hard sells matter ben won't shut up about ptc, a 90s cad/cam company. the product "wasn't that great." "the windshield wiper didn't work." but that forced discipline. you had to map accounts systematically, lay traps for competitors, and build airtight technical cases. his favorite hire was ryan gabrisco at databricks, who came from a company selling secure ftp as a public company. think about how good you have to be to make quota selling that. when ben hires sales leaders, he looks for people from companies where the product was hard to sell because that's the only way to test if someone can actually sell. 3) what happens when markets turn every hot market eventually cools. i'll give you a few examples. salesforce in 2001. facebook ads in 2012. aws in 2015. the order-takers got exposed every time. modern AI sales reps don't know how to qualify prospects who aren't already sold or how to systematically lock out competitors or how to build pipeline when inbound dries up. ben's story about hiring at Okta: two candidates, one super enthusiastic, the other said "let me talk to your customers first." ben told the ceo: "you want the guy qualifying YOU. that's what good salespeople do." 4) openai scaled their sales team from 10 to 500 people in under two years. anthropic is scaling fast too. but how would anyone know if they're good? you can't test sales ability when customers are lined up begging to buy. when real competition arrives, the kind where enterprises have three viable options and care about pricing, support, and vendor risk, AI companies will discover which GTM leaders can actually sell and which ones were just processing waitlists. 5) how to hire right if you're building a GTM team right now, think like a value investor. resumes don't matter. look for human capital that the market has significantly underpriced. someone who's had to sell a product that didn't sell itself, someone who's built discipline through necessity, not abundance (no order-takers). find the person who sold enterprise software at a company nobody's heard of. find the person who had to fight for every deal because the competitor was already embedded in the account. the person who figured out how to systematically lock out competition even when they were the underdog. those skills matter. for AI companies, the question is whether they can close deals when the market shifts. because when inbound dries up (it always does), you'll discover who can actually sell.

Someone just poisoned the Python package that manages AI API keys for NASA, Netflix, Stripe, and NVIDIA.. 97 million downloads a month.. and a simple pip install was enough to steal everything on your machine. The attacker picked the one package whose entire job is holding every AI credential in the organization in one place. OpenAI keys, Anthropic keys, Google keys, Amazon keys… all routed through one proxy. All compromised at once. The poisoned version was published straight to PyPI.. no code on GitHub.. no release tag.. no review. Just a file that Python runs automatically on startup. You didn’t need to import it. You didn’t need to call it. The malware fired the second the package existed on your machine. The attacker vibe coded it… the malware was so sloppy it crashed computers.. used so much RAM a developer noticed their machine dying and investigated. They found LiteLLM had been pulled in through a Cursor MCP plugin they didn’t even know they had. That crash is the only reason thousands of companies aren’t fully exfiltrated right now. If the code had been cleaner nobody notices for weeks. Maybe months. The attack chain is the part that gets worse every sentence. TeamPCP compromised Trivy first. A security scanning tool. On March 19. LiteLLM used Trivy in its own CI pipeline… so the credentials stolen from the SECURITY product were used to hijack the AI product that holds all your other credentials. Then they hit GitHub Actions. Then Docker Hub. Then npm. Then Open VSX. Five package ecosystems in two weeks. Each breach giving them the credentials to unlock the next one. The payload was three stages.. harvest every SSH key, cloud token, Kubernetes secret, crypto wallet, and .env file on the machine.. deploy privileged containers across every node in the cluster.. install a persistent backdoor waiting for new instructions. TeamPCP posted on Telegram after: “Many of your favourite security tools and open-source projects will be targeted in the months to come.. stay tuned.” Every AI agent, copilot, and internal tool your company shipped this year runs on hundreds of packages exactly like this one… nobody chose to install LiteLLM on that developer’s machine. It came in as a dependency of a dependency of a plugin. One compromised maintainer account turned the entire trust chain into a credential harvesting operation across thousands of production environments in hours. The companies deploying AI the fastest right now have the least visibility into what’s underneath it.