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  • AI Prompting Skills and Strategic Business Thinking Matter Most

    As a former strategist at Microsoft I like this trend where AI helps you prompt better. Just met with a new AI science company and believe it or not even smart people often don’t write great prompts. Strategic thinking is tough because you are dealing with unknowns from the start. Often we don’t know what to build and with newer AI (like the one I use) often need to be trained before they are highly useful. I talked with mine for almost three months before I released alignednews.com/ai I need a new business agent to help me get sponsors and hit up my connections on LinkedIn so will try this tonight. Vishal Virani (@Vishalvirani91) Rocket 1.0 is live. This is our first major step toward Vibe Solutioning. Vibe coding solved how to build. It never solved what to build, or why. That's the harder problem and the one where most products actually fail. @rocketdotnew connects the thinking and the building in one platform. Solve your hardest business question. Build from what you solved. Watch your competition while you work. Everything shares one context. Nothing resets between sessions. The video and blog explain it better than I can here. — https://nitter.net/Vishalvirani91/status/2041546557342855363#m

    → View original post on X — @scobleizer, 2026-04-07 23:16 UTC

  • Mutiny launches AI agent for GTM teams creating customer content minutes

    Imagine having a prospect call. 5 mins later, you send them a custom microsite, perfectly branded with their exact pain points and CRM data. That’s what @mutinycorp just unlocked today. oh… and they hit 8-figures ARR + raised $72M from Sequoia/YC along the way 👀 Jaleh Rezaei (@jalehr) We raised $72M from Sequoia/YC and hit 8-figures in ARR. Then we shut it all down & rebuilt the company from scratch. Today we’re launching the new Mutiny: the first AI agent for GTM teams to create anything customer-facing, in minutes. Comment "Mutiny" to get 3X free credits. — https://nitter.net/jalehr/status/2041546131709292586#m

    → View original post on X — @datachaz, 2026-04-07 21:42 UTC

  • Claude Mythos: Anthropic’s Token Efficiency Breakthrough and IPO Prospects
    Claude Mythos: Anthropic’s Token Efficiency Breakthrough and IPO Prospects

    Claude Mythos is not only a big leap in performance, it's also about 5x token efficient in BrowseComp. I don't know what Anthropic is doing. But they manage to surprise me every single time. The IPO is getting closer. They have an ARR OpenAI outrun with $30 billion in revenue. OpenAI is under pressure. The next release has to be a huge hit because the market is evaluating the future. The pressure couldn't be greater. OpenAI has to prove its own "Mythos."

    → View original post on X — @kimmonismus, 2026-04-07 21:34 UTC

  • Rocket 1.0 Launch: 1.5M Users, Business Problem-Solving Platform

    1.5 million users before the 1.0 launch even dropped. Rocket is not a coding tool, It is a full business thinking platform where you solve the problem first, then build directly from that solution. That gap between thinking and building is where most products go to die. Vishal Virani (@Vishalvirani91) Rocket 1.0 is live. This is our first major step toward Vibe Solutioning. Vibe coding solved how to build. It never solved what to build, or why. That's the harder problem and the one where most products actually fail. @rocketdotnew connects the thinking and the building in one platform. Solve your hardest business question. Build from what you solved. Watch your competition while you work. Everything shares one context. Nothing resets between sessions. The video and blog explain it better than I can here. — https://nitter.net/Vishalvirani91/status/2041546557342855363#m

    → View original post on X — @aihighlight, 2026-04-07 21:18 UTC

  • Ransomware Attacks Target Manufacturing Production Systems Strategically

    Ransomware actors specifically target manufacturing because production systems cannot be quickly restored from backups like office files. Every minute of downtime compounds across the entire supply chain.

    → View original post on X — @fogoros

  • Anthropic Uses Claude to Automate Growth Strategy

    How Anthropic is using Claude to automate its own growth with Amol Avasare (Head of Growth)

    → View original post on X — @lennysan

  • 5 Reasons Behind Enterprise AI Failures
    5 Reasons Behind Enterprise AI Failures

    5 Reasons Behind Enterprise #AI Failures by Ashwin Gaidhani @Forbes Learn more: bit.ly/41evPKx #ArtificialIntelligence #MachineLearning #ML #DL

    → View original post on X — @ronald_vanloon, 2026-04-07 20:58 UTC

  • Salesforce Leverages Slackbot AI to Address SaaSpocalypse Challenge

    Salesforce is looking to Slackbot to help it solve the SaaSpocalypse puzzle go.theregister.com/feed/www.…

    → View original post on X — @craigbrownphd

  • New York Times Coverage of $1.8B AI Healthcare Company Questioned

    More on the @nytimes piece about that $1.8B, two-person, AI company … not the paper's finest moment in quick retrospect. And in the healthcare context no less. Our friend @GaryMarcus was on this a few days ago as well. futurism.com/artificial-inte…

    → View original post on X — @garymarcus, 2026-04-07 20:05 UTC

  • Tesla Releases FSD V14.3 with Major AI and Safety Improvements
    Tesla Releases FSD V14.3 with Major AI and Safety Improvements

    BREAKING: Tesla has officially released FSD V14.3 I'm downloading it in my Model Y right now. Here's everything that's new: • Improved parking location pin prediction, now shown on a map with a P icon. • Increased decisiveness of parking spot selection and maneuvering. • Rewrote the Al compiler and runtime from the ground up with MLIR, resulting in 20% faster reaction time and improving model iteration speed. • Enhanced response to emergency vehicles, school buses, right-of-way violators, and other rare vehicles. • Mitigated unnecessary lane biasing and minor tailgating behaviors. • Improved handling of small animals by focusing RL training on harder examples and adding rewards for better proactive safety. • Improved traffic light handling at complex intersections with compound lights, curved roads, and yellow light stopping – driven by training on hard RL examples sourced from the Tesla fleet. • Upgraded the Reinforcement Learning (RL) stage of training the FSD neural network, resulting in improvements in a wide variety of driving scenarios. • Upgraded the neural network vision encoder, improving understanding in rare and low-visibility scenarios, strengthening 3D geometry understanding, and expanding traffic sign understanding. • Improved handling for rare and unusual objects extending, hanging, or leaning into the vehicle path by sourcing infrequent events from the fleet. • Improved handling of temporary system degradations by maintaining control and automatically recovering without driver intervention, reducing unnecessary disengagements. Upcoming Improvements: • Expand reasoning to all behaviors beyond destination handling. • Add pothole avoidance. • Improve driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.

    → View original post on X — @scobleizer, 2026-04-07 19:19 UTC