@exm7777Oct 27

let me tell you something my friend this is not the time to cancel subscriptions this is not the time to play it safe this is not the time to "wait and see" right now is the time to go fucking ALL IN >max out your Claude sub >burn through your ChatGPT plan >spend all your tokens on OpenRouter and top up AGAIN it's time to experiment, to build and PRINT a shit ton of money

@alliekmillerOct 27

I don't think people realize how many pitches investors get today from people who "invented a new algorithm" or "solved the climate crisis" because of one conversation with ChatGPT.

@pmituOct 27

POWERPOINT JUST GOT ITS BIGGEST AI UPGRADE everyone on X is building with Claude and ChatGPT meanwhile, millions of businesses still run on PowerPoint Templafy just launched Document Agents: → creates, edits, and reviews presentations → knows your brand and company rules → works across PowerPoint, Claude, ChatGPT, and Copilot → cuts deck creation from 2 hours to 8 minutes, on average AI helps us create more stuff decreasing hours of boring work into minutes

@aakashguptaOct 27

Sam Altman asked ChatGPT why his baby keeps throwing pizza on the floor and laughing. Scientists at Johns Hopkins answered that 11 years ago, and honestly the answer is a little embarrassing for the guy who runs ChatGPT. If your kid ever did this to you at dinner, you were watching a physics experiment. Two researchers, Aimee Stahl and Lisa Feigenson, brought 110 babies into their lab, all around 11 months old, and showed them toys doing impossible stuff. Some of the babies watched a ball roll right through what looked like a solid wall. Others watched a toy car roll off a ledge and just hang there in the air. Then they handed the babies the toy. The wall babies grabbed it and banged it on the table, like they were checking whether it was actually solid. The floating-car babies kept dropping theirs on the floor. Each group went for whichever test matched the rule they'd just seen broken, and the babies who watched the toy act normal barely did either one. None of these kids could talk yet, and nobody had ever explained gravity to them. They still showed up with a pretty good idea of how stuff is supposed to behave, and the moment the world didn't match it, they went and got more data. So a baby dropping the same slice of pizza over and over is basically rerunning the experiment to make sure food still falls. Around that age they also start watching your face to figure out how they should feel about what just happened, which means your reaction is part of the experiment too. Here's where it gets uncomfortable for AI. Yann LeCun, one of the godfathers of modern AI, did the math on this. A 4-year-old has been awake for about 16,000 hours, and just through their eyes they've taken in roughly as much raw data as the biggest AI models get trained on. The kid's data comes as live video, with hands to poke things and a parent reacting to every move. LeCun thinks that's what today's AI is missing, and it's a big part of why he left Meta to build something different. So the guy running OpenAI asked a chatbot to explain the one learning machine nobody in AI knows how to build, and it's been sitting in a high chair in his kitchen this whole time.

@mtsliveOct 27

a16z's @droovg explains why ChatGPT and Gemini struggle to find the best startups to work for, and how Cosign is building the missing data layer: "One thing that LinkedIn will never do is introduce an MCP that allows you to have vast search access over the graph." "When I was in New York this summer, I wanted to start meeting people who I thought I might be able to work for one day." "So I Googled, who are the best startups in New York? Gemini gave me a pretty bad answer. I switched to ChatGPT, it also gave me a pretty bad answer. That whole data layer of information is kind of missing right now." "We have an iMessage agent. We also have a personal MCP that lets you connect your Muse, your Grok Bot, your Instinct to the platform, to make this truly the first agent-native professional networking platform." @cosign @a16z

@businessbaristaOct 26

Experian, a $35 billion business with roots dating back to 1826, is surprisingly AI-native. Its new Chief AI Officer, Vijay Mehta, broke down the credit bureau’s end-to-end AI strategy. Complete list of notes... Big takeaways:
 • Experian is well past proof of concept, with AI capabilities running in production throughout the company.
 • The next stage is what Mehta calls "reimagination." Redesigning how work gets done through delegation to agents vs. prompting chat bots. 
 • Adoption is close to universal. 85% of employees actively use the company's AI tools, 88% of developers use coding assistants, and employees built more than 6,000 custom GPTs by the first half of fiscal 2026.
 • They're seeing real ROI. It's measured in time savings, time to value, quality, velocity and traditional before and after financial metrics, not in adoption or token use. How they built the foundation:
 • Within months of ChatGPT's launch, they trained thousands of employees and put AI policies and guardrails in place.
 • AI traffic was routed through a control plane that gives them observability, monitoring and security.
 • They wrote a GenAI risk framework and built the Experian GenAI Platform, an internal system that lets employees build internal-facing & and customer-facing apps, while accessing company data securely.
 • They rolled out a coding assistant to their large developer base and built their own Experian GPT into products like a digital financial assistant and their Ascend platform.
 • They created a GenAI Center of Expertise, which now sits under Mehta's AI office.
 • Since then, AI has spread across software development, analytics and business operations. AI inside the employee experience:
 • MyCareer platform recommends learning and career moves and helps managers spot skills gaps.
 • Nadia, an internal AI coach, helps employees set goals, build development plans and prepare for performance reviews.
 • Nadia also gives leaders personalized coaching and 360-degree feedback. On models and cost:
 • "Not everybody needs the most advanced frontier model. Most workloads can be done with a free or very low-cost model."
 • He compares reaching for a frontier model by default to using a sledgehammer on a job that needs a much smaller tool.
 • They run a mix of open-weight models adapted to their own environment and frontier models accessed through AWS Bedrock.
 • The control plane routes each workload to a model based on the task, language, region and regulatory requirements. On agent safety:
 • Guardrails are designed into the architecture from the beginning instead of being added later.
 • Their Agent Operating System runs on that control plane, so it can sandbox, monitor and stop an agent process when necessary. "The ability to kill a process, the ability to kill a process, I will repeat that, we've got all of that built in."
 • Their risk profile differs from the frontier labs' because their systems work over a defined body of financial and identity data, without broad access to the internet. "We start with our corpus of data and we put controls around that. And we know exactly how the data is moving." What the CAIO role actually is:
 • Experian is a big company split into many business units. His job is one common AI strategy and direction: "to make sure that we are all marching in the same direction."
 • He accelerates the AI agenda both internally and externally.
 • Risk, security, compliance and partner choices all come together in the AI office. AI as the new middleman:
 • Consumers increasingly start their financial journey inside an AI assistant instead of going to Experian or a bank, so Experian is meeting them there.
 • It's the first personal finance app integrated with Google's Gemini. US consumers who connect their Experian accounts can ask Gemini about their FICO credit rating and what's affecting it.
 • Inside ChatGPT it has launched personal loan shopping, credit card shopping and an insurance marketplace.
 • On the enterprise side, ServiceNow is the first integration partner for its Agent Operating System. Under a multiyear partnership, ServiceNow agents tap Experian's Ascend data and decisioning from inside enterprise workflows.
 • It also launched Agent Trust, which verifies that an AI agent is actually connected to the consumer it claims to represent.
 • Could agents eventually skip Experian and get the data somewhere else? He says they can't reproduce it. Decades of longitudinal financial and identity data, plus its provenance and regulatory standing, are what matter when the output drives consequential decisions. "In order to be able to make a decision, you've got to have that trusted data source." His advice if you're early:
 • Train employees.
 • Set guardrails before deployment. "So much of safety and responsibility comes from the person interacting with the system."
 • Route AI traffic through a controlled gateway where usage can be observed and policies enforced. Which AI leader should I learn from next?