The Neuron: AI Explained

Anthropic just released Claude Fable 5.1, its newest frontier model for long-running coding, research, and agentic work.So naturally, we’re putting it to the test LIVE. 🤖Early testing suggests Fable 5.1 is faster, easier to work with, and capable of handling massive coding projects, long-form writing, and autonomous agent tasks more efficiently. Every even found that it used less than half as many tokens as Opus 5 in one internal test.But it has some quirks too. It can blow past word counts, create unnecessary subagents, and occasionally keep working when you tell it to stop.Today, Grant and Corey from The Neuron are testing those claims for themselves.We’re putting Fable 5.1 through:🧠 Complex research and knowledge work💻 Coding and long-running agent workflows✍️ Writing, editing, and instruction following🤖 Autonomous tasks where Claude runs on its own🛑 Constraint, budget, and STOP tests🆚 Whatever else the live chat wants us to tryAnthropic also cut cached-input pricing by 75%, potentially making long-running Claude agents significantly cheaper to operate.Can Fable 5.1 actually become the model you hand a giant task and walk away from?Let’s find out live.UPDATE: Our write-up on this livestream, with time-stamps: https://theneuron.ai/news/claude-fable-5-1-can-do-the-work-the-hard-part-is-managing-it/🔗 Anthropic announcement:https://www.anthropic.com/claude-fable-and-mythos-5-1🔗 Every’s Fable 5.1 Vibe Check:https://every.to/vibe-check/fable-5-1-vibe-check📩 Subscribe to The Neuron for AI news, tools, and practical experiments without the hype:https://theneuron.ai/

AI companies spend enormous effort making models safer, but the model tested in the lab isn't necessarily the system a company eventually deploys. Alice CEO and co-founder Noam Schwartz joins Corey and Grant to explain why prompts, tools, memory, permissions, data, and agent-to-agent interactions create an entirely new security surface. They dig into the growing “trust gap” around enterprise AI, why prompt injection may become a permanent cat-and-mouse game, what open-weight models change for defenders, and why Schwartz believes the real security boundary has to exist at every layer of an AI system. The bigger takeaway: as AI moves from answering questions to taking actions, traditional cybersecurity may need to merge with fraud prevention, threat intelligence, and trust and safety.OpenAI security incident: https://openai.com/index/hugging-face-model-evaluation-security-incident/Alice: https://alice.io/Alice on agentic AI security: https://alice.io/blog/key-security-risks-posed-by-agentic-ai-and-how-to-mitigate-themAlice open-weight research: https://alice.io/blog/okay-here-is-how-to-build-a-bomb-millions-download-dangerous-llmsSubscribe to The Neuron newsletter: https://theneuron.aiSponsored by Dell Technologies and NVIDIA. Learn more at https://www.techrepublic.com/hubs/the-enterprise-guide-to-scalable-ai/

AI tools are shipping faster than most normal humans can figure out what half of them actually do.So Thursday, August 20 at 10 AM PT / 1 PM ET, we’re going LIVE to translate this week’s biggest AI launches into plain English. 😸The goal: understand what these tools actually are, who they’re for, what’s useful vs. hype, and which ones are worth trying.No three developers yelling model benchmarks at each other for an hour. Instead, we’re covering:🤖 Qwen 3.8: What a powerful open model is, why you might use one instead of ChatGPT or Claude, and when that makes sense.💻 Unsloth Studio: Run and experiment with AI models on your own computer, even if you’ve never touched a terminal.⌨️ Cursor Origin: Cursor wants to host your code too. Here’s what that could mean for people building websites, apps, and internal tools with AI.🛠️ DeepSeek Harness: What an “agent harness” is, why everyone keeps talking about them, and whether they matter outside hardcore coding circles.💬 Buzz: Imagine Slack or Discord, except AI agents can join the workspace, collaborate with humans, and do work.🐦 Berd: One desktop home for your AI agents, projects, skills, tools, and models. You can also give your agents little animated bodies. Please emotionally prepare yourself.Plus, we’ll cover the other notable models and tools that dropped this week.And if OpenAI drops Astra before we go live? We’ll cover that too. If it’s incredible, great. If it belongs in the “cool, another model” bucket, that’s part of the roundup too.📅 August 20 @ 10AM PT / 1PM ETBring your questions. No PhD required. 😸TOOLS / LINKS:Qwen 3.8: https://qwen.ai/blog?id=qwen3.8Unsloth: https://unsloth.ai/Cursor: https://cursor.com/changelog/origin-code-hostingDeepSeek: https://github.com/deepseek-ai/deepseek-harnessBuzz: https://buzz.xyz/Berd: https://berd.xyz/OpenAI: https://openai.com/index/pacing-model-development-cyber-capabilities/

AI can write code, summarize documents, and hold a conversation. But it still struggles with the structured data businesses rely on to predict churn, fraud, demand, pricing, and risk. Alexandre Pasquiou explains why language models flatten the relationships inside spreadsheets, how tabular foundation models learn from rows and columns, and why Neuralk believes one general model could replace hundreds of custom predictive systems. The conversation also covers Seldon, AI agents, enterprise adoption, and Alexandre’s prediction that tabular foundation models will power every predictive workload by 2030.Learn more about Neuralk: https://www.neuralk.ai/Subscribe to The Neuron newsletter: https://theneuron.ai

Want to make better AI videos but have absolutely no idea what you’re doing?Perfect. Neither did most of us at first. 😹Join The Neuron LIVE this Thursday at 10 AM PT for a total beginner’s guide to AI video generation and video prompting, featuring the team behind the newly announced LTX-2.5.We’re going hands-on with the new model while learning the fundamentals of actually prompting video models effectively.What we’ll cover:🎬 How video prompting is different from image prompting✍️ How to write your first good AI video prompt🎥 How to control shots, motion, subjects, and scenes🧠 What video models actually understand when you describe a scene🛠️ A live demo of the brand-new LTX-2.5❓ Live Q&A with members of the LTX teamNo previous AI video experience required.If you can describe the video you want to make, we’ll show you how to turn that idea into a much better prompt.And because this is live, bring your weird prompts, difficult questions, and video ideas. We’ll put the model through its paces together.📅 Thursday, August 13⏰ 10 AM PTLearn more about LTX-2.5🔗 Explore LTX-2.5: https://ltx.io/model/ltx-2-5📰 Read the announcement: http://ltx.io/newsroom/introducing-ltx-2-5🤗 LTX-2.5 on Hugging Face: https://huggingface.co/Lightricks/LTX-2.5

AI can now read DNA like language, generate working biological sequences, and help scientists identify disease-related mutations. Radical Numerics CEO Eric Nguyen explains how genome language models work, why his earlier model Evo helped scientists design CRISPR systems and bacteriophage genomes, and how the company’s newer model, Omnii, combines DNA with RNA, proteins, and other biological signals. The conversation explores personalized medicine, gene therapy, AI-designed biological threats, “deepfake viruses,” and whether the same technology that creates new biology can also defend against it.Learn more about Radical Numerics: https://www.radicalnumerics.ai/

This is the #1 request we get every week: how to actually use agents to save time in your business.We’re bringing in James McAulay, founder of The Agent Accelerator, for a practical crash course on what AI agents are, how they work, and how beginners can start using them to get real work done.James has spent the past year building at the front lines of the agent economy. After helping ElevenLabs grow from $110M to more than $300M in annual recurring revenue, he launched a fully AI-native business that reached $80K in monthly revenue by its third month and recorded its first $200K+ month by month five.He did it without a single employee or a dollar spent on paid ads. Instead, James delegates work to multiple AI agents every day.Through The Agent Accelerator, James now teaches founders, CEOs, and their teams how to become AI-native. The program has trained more than 400 people across 100 companies, including startups, 200-person organizations, and the UK Government. Participants report automating an average of five hours of manual work every week after four weeks.In our session, James is going to teach: EVERYTHING you need to build helpful, proactive agents in Claude Cowork/CodeHe'll walk through the following concepts: • Quick primer on agent foundations: how do we move from prompting a chatbot to delegating Agentic work• Starting your second brain: the key files that make the biggest difference• Tips & tricks for optimizing Claude's behavior with CLAUDE.md• Skills - where to find good ones - how to create great ones• And his 4-level framework for proactive agents that work without being prompted in Cowork and CodeFormat will be a blend of James teaching concepts, screensharing, and showing demos of his own setup.Whether you have experimented with a few AI tools or have no idea where to begin, this session will help you understand what agents can realistically do and how to start using them.Learn more about James and The Agent Accelerator:https://agentaccelerator.ai/

What happens when the most capable AI lives in the cloud, but the work you want it to do is too private, expensive, or repetitive to send there every time?Dr. Olena Zhu, Head of AI Solutions & Ecosystem for Intel’s Client Computing Group, joins Corey Noles and Grant Harvey to explain Intel’s vision for hybrid AI: systems that route each task to the right place, whether that is a local model on a PC, a larger model on an edge server, or a frontier model in the cloud.The conversation explores why cloud-only AI may be difficult to scale, how an orchestration layer decides where work should run, and how Intel’s new SuperClaw beta combines local and remote intelligence. Dr. Zhu also explains how hybrid agents could conduct deep research without exposing confidential data, why routing and auditability matter when agents fail, and why the next wave of useful AI may come from specialized agents built for specific jobs.Listen for a practical look at the tradeoffs among capability, privacy, cost, reliability, and control, and what it could mean when powerful AI agents begin running partly on the computers we already own.Try Intel SuperClaw: https://aibuilder.intel.com/#/superclawIntel AI Builder: https://aibuilder.intel.com/Intel SuperClaw GitHub: https://github.com/intel/intel-ai-builder/tree/main/superclawIntel’s SuperClaw overview: https://newsroom.intel.com/opinion/solving-the-agentic-ai-trilemma-cost-scale-and-data-securitySubscribe to The Neuron for daily AI news and analysis built for humans: https://www.theneurondaily.com/Sponsored by Nerdio: Get a demo of Nerdio Manager for Enterprise today:

Update! The definitive follow-along walkthrough guide is ready! Check it out here: https://theneuron.ai/explainer-articles/how-to-publish-an-ai-built-iphone-app-to-the-app-store/Building an app with AI is getting easier. Getting it through Apple's doors is still a different adventure.Join Corey Noles and Grant Harvey live on Thursday, July 30 at [10AM PT / 12PM CT / 1PM ET] as they walk through what it actually takes to move an AI-built app from a working prototype into TestFlight and the Apple App Store.In this livestream, we'll cover:📱 Setting up App Store Connect🧪 Preparing your app for TestFlight📝 Creating your App Store listing🖼️ Making screenshots and store assets🔒 Answering Apple's privacy questions🚀 Uploading and submitting your build✅ Navigating Apple's review process⚠️ The mistakes, delays, and confusing steps we ran into💡 What we'd do differently next timeWhether you're using AI coding tools, no-code platforms, or building from scratch, this beginner-friendly walkthrough will help you get your app across the finish line.💬 Bring your questions and click Notify Me so YouTube reminds you when we go live.🔔 Subscribe to The Neuron for practical AI news, tools, tutorials, and conversations that help you understand what matters and what to do with it: https://www.youtube.com/@theneuronai?sub_confirmation=1📰 Read The Neuron Daily:https://www.theneurondaily.com/

AI can now help almost anyone turn an idea into a working prototype. But what happens when that vibe-coded experiment needs to become secure, reliable software that real customers can trust—and pay for?Corey Noles and Grant Harvey speak with Deap Ubhi, Global Director of Technology for Startups at AWS, about AWS Startup Advisor, an AI-powered builder assistant designed to bring AWS architecture, security, cost, deployment, and scaling guidance directly into a founder’s workflow.Deap explains why generative AI has compressed startup iteration cycles from months into days or hours, how nontechnical founders can test ideas before making major technical investments, and why human judgment, product taste, and focus matter even more when building becomes dramatically easier. The conversation also explores the crucial leap from proof of concept to production, including the infrastructure, authentication, resilience, observability, and security decisions that first-time builders may not know to ask about.Listen to hear how Startup Advisor works inside tools including Claude Code, Cursor, Codex, VS Code, and Kiro—and why the next generation of founders may start with an AI coding agent and a virtual AWS solutions architect on their shoulder.For more practical conversations about how AI is changing work, business, and technology, subscribe to The Neuron and The Neuron: AI Explained.https://www.theneurondaily.com/Explore AWS Startup Advisor:https://aws.amazon.com/aws-startups/advisor/Learn more about the launch:https://aws.amazon.com/aws-startups/from-idea-to-revenue-at-startup-speed-with-ai/The Neuron Academy helps professionals build practical AI skills they can use right away, with lessons on prompting, workflows, and real workplace use cases. Check out https://theneuronacademy.com/ today!

Join Grant Harvey and Corey Noles live on Thursday, July 23, for a show-and-tell featuring the apps, games, extensions, and delightfully specific tools they’ve built with AI, plus tips to help you build your own without burning through as many tokens.Corey will demo:☕ Bean Counter, which tracks how many cups of coffee he has saved🗂️ Tab Crusher, a Chrome extension for conquering tab overload✍️ Threadline, his editorial operating system for writers🎮 Circle Back, a gamified task-management app🍽️ On Deck, which answers Corey’s eternal question: What should I eat next?Getting AI to choose his next meal is Corey’s personal AGI benchmark. Pizza arriving through a voice command remains the final boss.Grant will show:🌊 FlowState, a focused writing app🎛️ Orchestrator, a local command center for managing AI chats through APIs🎬 LTX CineScript, a system that turns a script into an edited film🐿️ Sqwirl World, a RuneScape-style mini MMO starring squirrels🧪 Plus other experiments, prototypes, and tools built to solve very specific problemsThey’ll explain what each project does, how it was made, how they got it live through trial and error, and what they’ve learned over the past year and a half as non-technical builders creating software with AI.Building your own apps is one of the best ways to learn what AI can actually do. Your idea may not become the next breakout product, but it can save you time, solve a persistent headache, and be a lot of fun to create.Whether you want to build an internal tool, automate an annoying task, or finally create the weird app living in your head, this session will show you what is possible.

Autonomous surgery may sound futuristic, but automation already plays an important role in procedures requiring extraordinary precision. Mathias Unberath of Inner Logic joins Grant Harvey to explain how AI could help surgical robots understand anatomy, respond to unexpected events, and gradually take on more responsibility in the operating room. They explore which procedures could be automated first, how robots can learn to recover from mistakes, and why these systems may expand access to care without eliminating the need for human surgeons.For more information please visit Inner Logic: https://semaphorsurgical.com/innerlogic/ Subscribe to The Neuron newsletter: https://theneuron.aiSponsored by Dell Technologies and NVIDIA. Learn more at https://www.techrepublic.com/hubs/the-enterprise-guide-to-scalable-ai/

Neuron Live is back and we are going deep on Microsoft’s big move in AI agents. 🤖This week, we’re joined by Bryan Goode, Corporate Vice President of Business Applications Marketing at Microsoft, to unpack Microsoft Agent 365, the new control plane for AI agents.Agent 365 is Microsoft’s answer to a question every company is about to face: how do you actually deploy, manage, and secure AI agents at scale? Think of it as a registry, an access control layer, and a security system for your entire fleet of AI agents, whether you built them in Copilot or brought them in from elsewhere.On the live, we’ll cover how agents work inside the Copilot ecosystem, what Agent 365 actually gives IT teams, and how to think about getting started with agents at your company. 💻👀If we’re lucky, Bryan will walk us through a live demo defining a use case, building an agent in Copilot from scratch, deploying it through Agent 365, and tracking how it performs in real time. If you’ve been wanting to build your first AI agent but didn’t know where to start, this is the one to watch live. Subscribe for weekly AI coverage from The Neuron and more livestreams like this.💌 https://theneuron.ai

 What if neural networks are less like mysterious black boxes and more like systems we can inspect, debug, and eventually design with intention?In this episode of The Neuron: AI Explained, Corey Noles and Grant Harvey talk with Eric Ho, Cofounder & CEO of Goodfire, an AI interpretability company working to understand what’s happening inside neural networks. Eric explains why models may contain meaningful internal structures — including features, representations, circuits, and curved manifolds — and how mapping those structures could make AI systems safer, more reliable, and more useful.They discuss why models may “think in shapes,” how Goodfire uses AI to interpret other AI systems, what neural geometry can reveal about hallucinations and model behavior, and why interpretability could change how companies train and control their own models.They also get into consciousness, robotics, multimodal models, the bitter lesson, and why Eric thinks more people should be looking under the hood of the most consequential technology of our time.Subscribe to The Neuron for more grounded conversations about how AI actually works: https://www.theneuron.ai/Sponsored by SAS AI Governance: Visit https://www.sas.com/en_us/solutions/ai/governance.html?utm_source=other&utm_medium=cpm&utm_campaign=sas-vpl-gbc-gps-global#The Neuron Academy helps professionals build practical AI skills they can use right away, with lessons on prompting, workflows, and real workplace use cases. Check out https://theneuronacademy.com/ today!

AI agents are not just coming for laptops, inboxes, and office workflows. Samsara Cofounder and CTO John Bicket says they’re also coming for fleets, drivers, dispatchers, safety teams, and the physical infrastructure that keeps the world moving.Recorded on-site at Samsara Beyond 2026 in Las Vegas, this conversation explores how Samsara is layering AI onto dash cams, telematics devices, asset trackers, vehicle data, and operational workflows. John explains how Agent Studio helps companies build useful AI tools without overwhelming frontline teams, why physical operations create different challenges than software-only environments, and how AI can help turn raw vehicle and safety data into coaching, risk reduction, maintenance insights, and real-time decisions.Corey, Grant, and John also dig into AI ride-alongs, privacy concerns around in-vehicle cameras, why driver safety programs need to be framed around trust instead of surveillance, and what the day-to-day work of dispatchers, drivers, and maintenance leaders could look like three years from now.Subscribe to The Neuron for more practical conversations about how AI is changing real businesses, not just demos.https://www.theneuron.ai/

Join Grant Harvey and Corey Noles from The Neuron live on Thursday, July 9 at 10AM PT as we test OpenAI’s new GPT-5.6 model family in real time: Sol, Terra, and Luna.Instead of just reading benchmark charts, we’re going hands-on with the use cases people should actually try first.We’ll test:🛠️ Building a working mini-app from a messy product idea🧹 Refactoring a broken codebase without babysitting it🧠 Using Ultra mode as a project manager with subagents⚙️ Automating one annoying weekly workflow🥊 Testing Sol vs. Terra vs. Luna on the same job🔍 Running the same prompts head-to-head against FableAlso: OpenAI just announced a 10AM PT livestream on July 9 for the next generation of ChatGPT Voice, reportedly featuring an upgraded bidirectional voice model, real-time capabilities, new voice samples, and voice orb colors tied to accent settings.So we’ll also react to what OpenAI shows, explain what “bidirectional voice” actually means for normal users, and test where voice might finally become useful for work instead of feeling like you’re leaving a voicemail for a robot receptionist.By the end, you’ll know what to try first, which model to use for which task, and whether GPT-5.6 or the new ChatGPT Voice actually changes your daily AI workflow.📩 Subscribe to our newsletter: https://www.theneuron.ai

Most AI image tools give you a prompt box and a result. ComfyUI gives creators the pipeline underneath - the models, parameters, nodes, and repeatable workflows that can turn visual AI from a toy into production infrastructure.In this episode of The Neuron, Corey Noles and Grant Harvey talk with Yannik Marek, co-founder and original creator of ComfyUI, about why node-based workflows matter, how open-source visual AI is moving into real creative production, and what teams gain when they can inspect, modify, and repeat every step of generation.They cover how diffusion models work in plain English, why Comfy is useful for VFX, gaming, animation, e-commerce, and creative studios, and how Comfy balances open-source values with Cloud, API, and Enterprise products. Yannik also shares practical hardware advice for running models locally, where open models are catching up fastest, and why the future of creative AI may depend less on a universal prompt box and more on visible, controllable workflows.Try ComfyUI at comfy.org, and subscribe to The Neuron for more grounded conversations about AI in practice.https://www.theneuron.ai/The Neuron Academy helps professionals build practical AI skills they can use right away, with lessons on prompting, workflows, and real workplace use cases. Check out theneuronacademy.com today!

This week on The Neuron: AI Explained, Grant and Corey break down the strangest week in frontier AI so far: Fable 5 relaunching and getting yanked almost immediately, OpenAI’s GPT-5.6 rollout arriving in a weird half-launch state, and the bigger question underneath all of it.What happens when governments can slow, restrict, or pause the most powerful AI systems right as the economy starts depending on them?We’ll get into why these false starts matter beyond Silicon Valley drama. If U.S. labs keep getting caught between safety fears, export controls, and uneven release rules, China may get more room to catch up through open-source models, faster iteration, and fewer distribution bottlenecks. Meanwhile, businesses betting on AI have to plan for a world where the “best model” might disappear, degrade, get delayed, or become unavailable to half their stack overnight.So this episode is our guide to navigating the current AI chop:Why Fable 5’s relaunch and takedown became a warning shotWhat GPT-5.6’s limited launch says about frontier model accessHow restrictions could reshape the U.S. vs. China AI raceWhy every company needs an open-source backup strategyHow AI uncertainty could ripple into the broader economyWhat we’d do now as builders, buyers, workers, and AI-curious professionalsJoin us for a strategic read on what’s changing, what’s fragile, and how to make smarter decisions while the AI ocean gets weird.

OpenAI and Thrive Holdings built Tax AI, a Codex-powered agent that helps prepare complex tax returns while preserving evidence for accountant review. In this episode, Corey and Grant talk with OpenAI’s John de Wasseige and Arthur Fernandes Araujo about how expert corrections become structured signals, how Codex turns repeated failures into evals and scoped engineering tasks, and why the best AI deployments still need humans close to the work. They also dig into what this pattern could mean for bookkeeping, audits, IT help desks, and other expert workflows where the system can measure what “right” looks like.Relevant links:OpenAI Tax AI case study: https://openai.com/index/building-self-improving-tax-agents-with-codex/OpenAI Codex: https://openai.com/codex/Harness engineering: https://openai.com/index/harness-engineering/Thrive Holdings: https://www.thriveholdings.com/Crete: https://www.cretepa.com/Subscribe to The Neuron newsletter: https://theneuron.ai

Humanoid robotics challenges go beyond movement and servo motors. The hardest problems are often AI problems. Bringing intelligence into the physical world means dealing with gravity, friction, uncertainty, and real consequences. Mistakes can break hardware.This week on Neuron Live, we’re joined by Nikita Rudin, Co-founder and CEO of Flexion Robotics, to unpack what it actually takes to build intelligence for humanoid systems.What we’ll cover:🤖 Training control policies and perception models🧪 Bridging simulation and the real world (sim-to-real)🛠️ Robotics training pipelines and the embodied AI stack🔮 Where humanoid and physical AI is headed nextIf large language models are the brain in the cloud, what does intelligence look like when it has to walk, grasp, and not fall over?Expect a deep dive into embodied AI, physical AI, and the systems powering the next generation of humanoid robots.

Larry Meadows, Head of Product Strategy & Evangelism for HP's Workforce Experience Platform (WXP), joins us to break down how HP is using AI to predict and prevent IT problems before employees ever notice them. We get a live demo of the platform—from AI-powered software recommendations across 50M+ devices to automated remediation in 3–4 clicks—and dig into the global memory crisis, shadow AI risks, and why IT leaders are drowning in portals. Whether you manage a fleet of 50 devices or 50,000, this one's worth your time.HP WXP: https://www.hp.com/wxpThe Neuron newsletter: https://theneuron.ai

Confused by AI Skills, Projects, Gems, Custom GPTs, and Agents?You're not alone. It's important to separate which is best for which use-case, because each has a place depending on what you're trying to get done. In this beginner-friendly live episode, we break down what these AI terms actually mean, who creates them, and when everyday users should use each one.Think of this as your plain-English map to the new AI assistant world:✅ Projects = places to organize ongoing work✅ Gems & Custom GPTs = reusable custom assistants✅ Skills = reusable instructions and workflows✅ Agents = AI systems that can take actions on your behalfBy the end of this live session, you'll understand the practical difference between creating a custom assistant, organizing work in a project, giving AI a repeatable skill, and letting an agent complete tasks for you.What You'll Learn:🔹 What an AI Skill is🔹 What an AI Project is🔹 What Google Gemini Gems are🔹 What Custom GPTs are🔹 What AI Agents are🔹 Which one beginners should start with🔹 The simple framework for choosing the right tool for your workflowGet beginner-friendly AI explainers, practical tutorials, and daily updates on what matters in AI.📩 Subscribe to our newsletter: https://www.theneuron.ai

AI can write code, pass exams, and summarize the web, but ask it to reason through a real-world image, and the magic often breaks. Andrew Dai, co-founder and CEO of Elorian, joins The Neuron to explain why visual reasoning may be one of the biggest unsolved problems in AI.Andrew spent years at Google Brain and DeepMind, including work connected to Gemini and sparse mixture-of-experts systems. Now, he’s building Elorian around a simple but powerful idea: if AI is going to understand the physical world, it needs more than text-based reasoning layered on top of images.In this episode, Corey and Grant talk with Andrew about why frontier models struggle with counting, navigation, design, engineering, charts, and physical reasoning; why scaling language models hasn’t solved vision; what a “visual chain of thought” might look like; and how better visual reasoning could accelerate robotics, satellite analysis, product design, and mechanical engineering.Sponsored by Dell Technologies and NVIDIA. Learn more at techrepublic.com/hubs/the-enterprise-guide-to-scalable-ai/.Sponsored by Outshift: Visit https://outshift.cisco.com/?utm_campaign=fy26q3_outshift_ww_paid-media_ioc-neuronai-outshift_podcast&utm_channel=podcast&utm_source=podcast to learn more about the Internet of Cognition.Subscribe to The Neuron for more conversations with the people building the future of AI.

Live from Microsoft Build, Corey Noles sits down with Scott Hanselman for a hands-on Neuron LIVE episode about AI-augmented software development, how it differs from just "vibe coding", and the surprisingly practical things people can now build with tools like GitHub Copilot and more.Scott is one of the best technical explainers in software: a longtime Microsoft and GitHub developer, teacher, speaker, author, blogger, and podcaster who has helped millions of developers understand new technology without making it feel impossible to learn.This episode turned into a live demo tour of what AI coding can already do, led by Scott's own use-cases. Corey and Scott walked through a series of examples showing how AI can help people build useful apps, prototypes, workflows, and small tools from everyday ideas, including Scott's own vibe-coded tools Baby Smash (https://www.babysmash.com/), which lets babies press random buttons for fun shapes and sounds, and Tiny Tool Town (https://www.tinytooltown.com/), which showcases random, cool tools Scott found around the web. But in the coolest demo of all, Scott shows how to take an open source tool and create software a personal blood sugar tracking app for his own diabetes management. If that doesn't get your idea blood flowing for what you can do with AI, we don't know what will! https://www.theneuron.ai/

In this episode of The Neuron, Corey Noles sits down with Mustafa Suleyman, CEO of Microsoft AI, at Microsoft Build 2026 to unpack Microsoft’s next AI chapter: seven new MAI models, a push toward in-house model development, and the idea of Humanist Superintelligence.Mustafa explains how Microsoft is thinking about AI that can reason, code, generate images, transcribe speech, and power real products—without turning the future into a vague AGI race. The conversation gets into what “humanist” means in practice, why Microsoft is building models from the ground up, how AI agents may reshape work, and what it takes to keep increasingly capable systems useful, controlled, and aligned with human goals.You’ll learn why Microsoft is investing in its own model family, how MAI-Thinking-1 and MAI-Code-1-Flash fit into the stack, why Suleyman frames superintelligence around human control, and what builders and operators should watch as agents move into real workflows.Sponsored by BeyondTrustCheck it out at: https://www.beyondtrust.com/products/identity-security-insights/assessment?campid=701Vw00000drII6IAMSubscribe to The Neuron for practical AI conversations with the people building what comes next.

Everyone is talking about Mercury-alpha, the mystery model that many believe could be GPT-5.6.In this live discussion, we're separating fact from speculation and unpacking what would actually matter if OpenAI releases a new flagship model this week.We'll cover:🔹 What Mercury-alpha is (and why people think it's GPT-5.6)🔹 The biggest rumors and evidence so far🔹 What a new OpenAI model would need to deliver to move the industry forward🔹 How Mercury-alpha fits into the broader AI agent race🔹 Codex, Hermes Desktop, and the rise of coding and desktop agents🔹 What all of this means for AI users, builders, and businessesJoin us live, bring your questions, and help us figure out whether Mercury-alpha is the next major leap in AI or just another chapter in the internet's favorite pastime: model-name archaeology.👇 Drop your predictions in the chat:What do you think Mercury-alpha actually is?📩 Subscribe to The Neuron for daily AI insights: https://www.theneurondaily.com/

How do you prove there’s a real human on the other side of the screen when AI can generate faces, IDs, accounts, agents, and entire swarms of bots?Tiago Sada, Chief Product Officer at Tools for Humanity, joins The Neuron to explain why proof of human may become one of the internet’s most important trust layers. Tools for Humanity is building the technology behind World and World ID, a system designed to verify that someone is a real, unique person without requiring them to reveal their identity across the web.Tiago breaks down why CAPTCHAs, phone numbers, KYC, and AI-detection systems are starting to fail; how World ID uses in-person verification, cryptography, and zero-knowledge proofs; and why the future internet may need to distinguish between humans, bots, and agents acting on behalf of humans.We also discuss concert ticket scalping, Tinder verification, Zoom deepfake protection, enterprise fraud, gaming bots, and why AI agents may need a kind of digital “power of attorney.”Subscribe to The Neuron for clear, practical conversations about AI and the future of technology: https://www.theneuron.ai/This episode is sponsored by Guru. https://www.getguru.com/?utm_source=theneuron&utm_medium=podcast&utm_campaign=silver-bundle-june2026

AI agents and automation sound complex, but they’re really about one simple idea: helping you spend less time on repetitive work and more time on the things that need your judgment.In this beginner-friendly Neuron Live, we’ll break down what AI agents are, how automation actually works, and how to start using both without getting overwhelmed.You’ll learn:🤖 How AI agents are different from regular chatbots⚙️ What actually happens inside an automation workflow🧰 Where tools like ChatGPT, Claude, Make, ClickUp, and other AI assistants fit in💼 Practical ways to use AI at work and in everyday life🔁 How to spot tasks that are worth automating⚠️ Common mistakes beginners make with AI workflows✅ How to decide what should stay human and what AI can help withNo coding experience required. No jargon.Just a clear, practical conversation about how to make AI more useful, more responsible, and less intimidating.Join us live, bring your questions, and leave with a better understanding of how to make AI do more than just answer prompts.Subscribe to our newsletter: https://www.theneuron.ai/

What if the next big AI breakthrough is not a bigger model, but a completely different kind of computer?Jeff Shainline, co-founder and CEO of Great Sky, joins The Neuron to explain how his team is building brain-inspired AI hardware using superconductors, photonics, and analog computation. Great Sky’s architecture, called Superconducting Optoelectronic Networks, or SOENs, is designed to move beyond the traditional GPU roadmap by co-locating memory and processing, communicating with light, and mimicking some of the high-connectivity dynamics found in biological brains.In this conversation, Jeff breaks down why today’s chips can struggle with fast, multimodal inference; why transformers may be powerful but inefficient for some future workloads; how Great Sky’s system differs from quantum computing; and why early applications could include fusion reactors, particle physics, video understanding, content moderation, and eventually new model architectures that do not map neatly onto today’s hardware.Subscribe to The Neuron for grounded, practical conversations about where AI is going next—and what actually has to work before the hype becomes real.

Voice agents are moving from “cool demo” to real product infrastructure.In this livestream, we’re joined by Ben Cherry of LiveKit to break down what it actually takes to build real-time AI agents that can listen, respond, interrupt, call tools, and work in production.LiveKit is an open source framework and developer platform for building voice, video, and physical AI agents in production.We’ll talk through the stack behind real-time AI experiences, then build and test a live demo together on The Neuron.In this live demo, we’ll cover:🎙️ How LiveKit helps developers build voice, video, and physical AI agents⚡ What makes real-time agents different from normal chatbots🧠 How voice agents handle latency, interruptions, speech, and tool calls🛠️ Why production-ready AI agents are much harder than a weekend demo🚀 What builders should know before shipping voice AI to real usersAnd yes, we’re doing a live demo, which means there is at least a small chance the agent talks back at exactly the wrong time. Perfect television.Guest: Ben Cherry, LiveKitLiveKit: https://livekit.com/Ben on LinkedIn: https://www.linkedin.com/in/bcherry-product-engineerBen on GitHub: https://github.com/bcherrySubscribe to The Neuron for clear, useful AI news, demos, and explainers for people trying to understand where this tech is actually going.https://www.theneuron.ai/

What happens when AI stops simply giving answers and starts producing proofs a computer can verify?In this episode of The Neuron, Corey Noles and Grant Harvey talk with Tudor Achim, Co-Founder and CEO of Harmonic, the company behind Aristotle — a formal reasoning system built to generate machine-checkable mathematical proofs. Tudor explains why math may be the clearest test case for moving AI from “trust me” to “check me,” and why formal verification could matter far beyond Olympiad benchmarks.They discuss what “mathematical superintelligence” actually means, why Tudor thinks solving a Millennium Prize problem would be a meaningful threshold, and how Lean-based proofs could change the way mathematicians collaborate. They also explore Aristotle’s real-world use cases, from open math problems to verified software, chip design, scientific computing, and the future of AI-assisted discovery.Plus: why Tudor thinks formal math has reached a “zero to one” moment, why specs may be the bottleneck in verified software, and why humans still need to direct the questions AI systems try to solve.Subscribe to The Neuron and sign up for The Neuron Daily at theneuron.ai.

May is Mental Health Awareness Month, and as AI becomes more embedded in our daily lives, one of the biggest questions we face is whether these systems can responsibly support emotional and psychological well-being.AI chatbots are increasingly being used for emotional support, but recent lawsuits faced by OpenAI and earlier ones targeting character.ai and Google's AI Overviews, as well as clinical reports, and internal research have raised valid concerns about their impact on vulnerable users.What does it take to build an AI system specifically designed for mental health from the ground up? Is that even possible?In this LIVE episode of The Neuron Podcast, Corey Noles and Grant Harvey speak with Daniel Reid Cahn, co-founder and CEO of Slingshot AI, about Ash, an AI application purpose-built for therapeutic support. Slingshot has raised $93M from a16z, Radical Ventures, and others to develop a foundation model for psychology trained on structured therapeutic conversations across modalities such as CBT, DBT, and psychodynamic therapy.We discuss the limitations of general-purpose chatbots in mental health contexts, recent controversies surrounding AI and psychiatric risk, and what differentiates a system designed to provide structured therapeutic engagement compared to one being used in a way it was never intended to be. The conversation also explores a broader question: Can AI meaningfully expand access to high-quality mental health care, and where should clear boundaries remain? Or should we keep our counseling where we always have, on a couch with a box of Kleenex and a hug nearby?🔗 Try Ash:https://www.talktoash.com/📌 About The Neuron PodcastThe Neuron breaks down the biggest stories in AI for 580,000+ daily readers. Our podcast goes deeper with the leaders, founders, and researchers shaping the future of AI. New episodes every week.Subscribe to The Neuron newsletter — theneuron.ai

Genspark went from AI search startup to autonomous AI agent platform, hitting $250M ARR in 12 months with no paid ads until they bought a Super Bowl spot. Co-founder and COO Wen Sang joins Corey and Grant to explain what "AI employee" actually means, demos Genspark Claw live (including buying us coffee mid-interview), and lays out his big thesis: legacy software is becoming infrastructure while AI agents become the new interface between humans and work. We get hands-on with Workspace 4.0, Claw, and a custom agent built live for the show.• Genspark Workspace 4.0 announcement: https://www.genspark.ai/blog/genspark-ai-workspace-4• Genspark sb-git: https://genspark.ai/sb-git/intro• OpenAI's customer story on Genspark: https://openai.com/index/genspark/• Forbes AI 50 (2026): https://www.forbes.com/lists/ai50/• Marc Benioff on Salesforce Headless 360 (referenced by Wen): https://x.com/Benioff • Andrej Karpathy's "wiki for agents" idea (referenced as inspiration for sb-git): https://x.com/karpathy• Wen on the DealMaker Show: https://alejandrocremades.com/wen-sang/Try Genspark for free: https://genspark.aiSubscribe to The Neuron newsletter: https://theneuron.ai

New to AI and not sure where to start?Join us live Thursday for The AI Starter Kit: What to Try...and What to Ignore.This beginner-friendly session will help you cut through the noise and focus on the AI tools, habits, and prompts that actually matter. By the end, you’ll know what to try first, what not to worry about yet, and how to ask better questions when you get stuck.In this session, we’ll cover:🚀 The best first steps for AI beginners🛠️ What tools and features are worth trying now🙅 What you can safely ignore for the moment💡 Simple ways to get better answers from AI🔍 How to troubleshoot when AI gives you something unhelpfulWhether you’re brand new to AI or still figuring out how to use it well, this live session will give you a practical place to start.

Can AI move from predicting proteins to actually designing new drugs? Isomorphic Labs is trying to answer one of the biggest questions in science.In this episode of The Neuron, Corey Noles and Grant Harvey talk with Rebecca Paul, Head of Medicinal Drug Design at Isomorphic Labs, and Michael Schaarschmidt, Foundational AI Research Lead.They explain why drug discovery is so slow, expensive, and failure-prone—and why AI drug design is much more complicated than “generate a molecule and ship it.” The conversation covers AlphaFold, structure prediction, molecule generation, binding models, clinical failure rates, human trust in AI systems, and the long-term hope of designing drugs for targets once considered “undruggable.”In this episode:Why drug discovery can take more than a decadeWhat people misunderstand about “AI-designed drugs”How medicinal chemists actually use AI modelsWhy biology is harder than text, images, or codeWhat it would take to make drug discovery faster and cheaperThe dream of designing a drug candidate in one iterationWhy “undruggable” proteins may not stay undruggable foreverAdditional resources:Technical report blog Best resource for learning about the capabilities that we are buildingIsomorphic Labs websiteBest destination for learning more about Iso and joining our team in London, Lausanne or Cambridge, MASubscribe for more grounded conversations on how AI is changing science, work, and the world.For more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

Join us Thursday as we break down OpenAI’s new Workspace Agents and what they mean for the future of work.We’ll cover:⚙️ What workspace agents are🤖 How they differ from regular chatbots🏢 Where they fit into real team workflows🚀 How to start working with them effectively🔄 What agentic AI means for workplace automation📈 Why teams are shifting from one-off prompts to repeatable AI-powered processesWhether you’re experimenting with ChatGPT at work, leading AI adoption, or trying to understand where OpenAI is taking agents next, this session will help you see what’s possible and what to watch for.Tune in for a practical, hands-on deep dive into the future of AI at work.Sign up for The Neuron newsletter: https://www.theneuron.ai/

Google just acquired an AI startup that lets anyone create real music, music videos, and custom instruments — no experience required. In this hands-on episode, Corey sits down with Kendall Rankin from Google to demo Flow Music (formerly Producer AI), the generative music tool now living inside Google Labs. They build a garage rock song about AI from scratch, generate a music video with VEO, and dig into what "amplifying human creativity" actually looks like when the tool can do most of the lifting. Listeners walk away with a clear view of where AI music tools fit in an artist's workflow, why watermarking (SynthID) matters, and how to try it for free.Try Flow Music: https://producer.ai Google Labs: https://labs.google SynthID (watermarking): https://deepmind.google/technologies/synthid/ Subscribe to The Neuron newsletter: https://theneuron.ai

OpenAI dropped GPT-5.5, so we did the only reasonable thing: went live immediately and tried to break it.In this off-the-cuff Neuron Live, Corey and Grant walk through OpenAI's GPT-5.5 release notes, benchmark claims, rollout details, and early access reactions before testing the model live across coding, reasoning, creativity, web research, and absurd prompt challenges. We also compare a few GPT-5.5 responses against Claude Opus 4.7, test Codex, build a new version of Cat Doom, and ask the important questions, like whether a sentient vending machine that only dispenses expired tuna salad deserves to live.In this episode, we cover:• What OpenAI says is new in GPT-5.5• GPT-5.5’s improvements in coding, computer use, research, and knowledge work• Early benchmark results across Terminal-Bench, GDPval, Frontier Math, BrowseComp, and scientific research tasks• Why token efficiency may matter as much as raw intelligenceGPT-5.5’s rollout across ChatGPT, Codex, Plus, Pro, Business, and Enterprise• Live Codex testing with a one-shot Cat Doom game buildCreative stress tests involving palindromes, time-traveling potatoes, dystopian vending machines, and Lord of the Rings product reviews• First impressions of whether GPT-5.5 feels meaningfully different from GPT-5.4 and Claude Opus 4.7This was not a formal benchmark. It was a first-contact livestream: messy, fast, weird, and exactly the kind of test we like.Subscribe for more AI breakdowns, live model tests, beginner-friendly explainers, and weirdly useful prompt experiments from The Neuron.Sign up for The Neuron newsletter: https://www.theneuron.ai/Follow along for more AI news, analysis, and live experiments.

Grant and Kyle dive into a comprehensive review and live test of the newly released Claude Opus 4.7, a cutting-edge large language model. This session explores its capabilities for coding and game dev, specifically referencing the "Renaissance / Plan Final Fantasy Tactics RPG Game" project. Discover how this ai model performs under pressure and its potential impact on game design workflows.🔴 LIVE at 9:30AM PT / 12:30PM ETAnthropic just dropped Claude Opus 4.7, and we’re putting it through the gauntlet in real time.Join Grant Harvey (Lead Writer at The Neuron) for an unscripted, warts-and-all test of Anthropic’s newest flagship model.What we’re testing- Advanced coding on tasks Opus 4.6 struggled with- New higher-resolution vision support for images up to ~3.75 megapixels- File system-based memory across multi-session work- The new xhigh effort level, which sits between high and max- Claude Code’s new /ultrareview slash command- Auto mode for longer, less-interrupted agent runsWhy this mattersOpus 4.7 is the first model Anthropic is releasing with its new automatic cyber safeguards, following last week’s Project Glasswing announcement.It’s also the direct upgrade path from Opus 4.6 at the same price:- $5 per million input tokens- $25 per million output tokensIf you build on Claude, this is likely the model you’ll be using next.What’s changing under the hood- New tokenizer, where the same input can map to more tokens depending on content type, roughly 1.0x to 1.35x- State-of-the-art score on GDPval-AA, a third-party evaluation of economically valuable knowledge work- Better instruction following, which means prompts written for earlier models may now behave differently- Improvements across finance agent evals, document reasoning, and long-context tasksBring your hardest prompts. We’ll run them live and show you what breaks, what shines, and whether it’s worth migrating today.Watch part two, where Grant covers Codex for (almost) anything: https://youtube.com/live/OiRkwm3-og0📰 Full writeup in tomorrow’s newsletter: 🐱 Subscribe to The Neuron (700K+ readers): https://www.theneuron.ai

AI can reason about text and images, but it still struggles to understand the physical world. In this episode, Grant sits down with Peter Wilczynski, Chief Product Officer at Vantor (formerly Maxar Intelligence / Digital Globe), to unpack why spatial intelligence is emerging as critical AI infrastructure. Peter spent years at Palantir building ontology systems and mapping tools for defense operations before joining Vantor, where his team has built a 100M+ square kilometer 3D model of the entire Earth at 50cm resolution. We dig into how satellite imagery becomes machine-readable through embedding models, why "ground truth world models" are fundamentally different from hallucinated ones, the Raptor GPS-alternative system, simulation and digital forensics, the future of augmented reality, and why the physical world might be the most important thing AI still doesn't understand.Vantor: https://vantor.comTensorGlobe Platform: https://vantor.com/product/platform/Vantor rebrands from Maxar Intelligence (Business Wire): https://www.businesswire.com/news/home/20251001760322/en/Vantor-Rebrands-from-Maxar-Intelligence-Unveils-AI-Powered-PlatformSubscribe to The Neuron newsletter: https://theneuron.ai

Brandon Baum — better known as heybrandonb to his 25M+ followers — built a YouTube empire making cinematic, effects-heavy videos that look like they cost millions but were born in a bedroom during COVID. In this episode, we get into how he went from 2 views to a million followers in a month, why he shoots everything on iPhones with a custom 3D-printed dual-phone rig, how AI tools like Firefly Boards have replaced his Post-it Note wall, and why he thinks the atmosphere is "ripe for change" in Hollywood. We also talk about what content is actually performing now (hint: it's not spectacle anymore), his plan to seed original IP on social before taking it to theaters, and why he's building custom AI agents to offload his admin so he can just be creative.Brandon B's YouTube channel:https://www.youtube.com/@heybrandonbAdobe Firefly Boards: https://firefly.adobe.com/LM Studio / Ollama (referenced in OpenClaw discussion): https://lmstudio.ai/ https://ollama.com/Subscribe to The Neuron newsletter: https://theneuron.ai

Let’s build with v0 in real time. We’re going LIVE with Tom Occhino, Chief Product Officer at Vercel, to explore vibe coding and take a hands-on look at v0, Vercel’s AI-powered development platform for building apps faster. We’ll show v0 live and walk through how it turns a simple prompt into a real, shippable interface. Tom will also explain what “vibe coding” actually looks like in practice, including how teams are using it today and where it fits into modern development workflows. What we’ll cover:⚡ You’ll see a live build using v0, from the first prompt to a working app.🧠 We’ll break down what vibe coding means and why so many teams are experimenting with it.🔐 Tom will share how Vercel thinks about AI-assisted development, including security, developer experience, and scale.🧭 We’ll talk about product, community, and where the Vercel ecosystem is headed next.❓ We’ll wrap with live Q&A and take questions from the chat. If you’re building products, shipping web apps, or thinking about how AI fits into your workflow, this session will give you a clear, practical look at what’s possible.Links: • Try v0: https://v0.app/• Vercel platform: https://vercel.comCheck out these template to get inspired: https://v0.app/templatesHow to prompt with v0: https://vercel.com/blog/how-to-prompt-v0 📬 For more AI news and deep dives, subscribe to The Neuron newsletter: https://theneuron.ai 🎙️ New to streaming or looking to level up? Check out StreamYard and get $10 discount! 😍 https://streamyard.com/pal/d/5214856690925568

A team of former Google DeepMind researchers just raised $2B to build America's answer to DeepSeek. In this episode, we sit down with Ioannis Antonoglou (Yannis), co-founder and CTO of Reflection AI, who helped create AlphaGo—the AI that beat the world champion in the game of Go back in 2016. Yannis breaks down what Reflection is building, why they're releasing frontier-level AI models as open-weight, and how mixture-of-experts architecture lets massive models run efficiently. We dig into reinforcement learning, the US vs. China open source gap, sovereign AI, coding agents, and why open science might be the fastest path to the most powerful AI on the planet.Reflection AI: https://www.reflection.aiReflection AI raises $2B at $8B valuation (TechCrunch): https://techcrunch.com/2025/10/09/reflection-raises-2b-to-be-americas-open-frontier-ai-lab-challenging-deepseek/Previous Neuron coverage of DeepSeek: https://www.theneuron.ai/newsletter/deepseek-returns https://www.theneuron.ai/newsletter/10-wild-deepseek-demosSubscribe to The Neuron newsletter: https://theneuron.ai

This video is a re-upload from our livestream on YouTube. Most people are still using ChatGPT the way they used Google in 2005: type a question, get an answer, close the tab.In 2026, that’s like owning a professional kitchen and only using the microwave.In this episode, Grant and Corey walk through The Neuron’s 5-Level AI Proficiency Stack — a framework for going from “I use ChatGPT sometimes” to “AI saves me 10 hours a week.”No coding required. No hype. Just the actual progression that separates casual users from people getting real, compounding value out of AI every single day.The 5 Levels:🔹 Level 1: Projects — Why your first move isn’t prompting. It’s onboarding.🔹 Level 2: Prompting — The simplest formula that actually works🔹 Level 3: Skills — Turn one good conversation into a reusable superpower🔹 Level 4: Automations — Set it, schedule it, forget it🔹 Level 5: Agents — AI that decides what to do and when to do itTools mentioned:• ChatGPT Projects: https://help.openai.com/en/articles/10169521-projects-in-chatgpt• Claude Skills: https://support.claude.com/en/articles/12512176-what-are-skills• Claude Cowork: https://support.claude.com/en/articles/13854387-schedule-recurring-tasks-in-cowork• OpenAI Codex: https://developers.openai.com/codex/app/automations• Gemini Opal: https://blog.google/innovation-and-ai/models-and-research/google-labs/opal-agent/• Gemini Scheduled Actions: https://support.google.com/gemini/answer/16316416📩 Read the full deep dive:https://www.theneuron.ai/explainer-articles/how-to-actually-use-ai-in-2026-the-complete-guide/

Brian Gerkey is the CTO of Intrinsic, the robotics software company that started inside Alphabet and now sits inside Google, working directly with DeepMind and Gemini. Brian co-created ROS (Robot Operating System), the open-source platform used by over 1 million developers that powers everything from factory robots to NASA's Astrobee on the International Space Station. In this episode, Grant talks with Brian about "physical AI" — what happens when AI leaves the screen and starts controlling robots in the real world. They cover why 80% of US manufacturing facilities still have zero automation, how Intrinsic's platform acts as the "Android of robotics," the breakthroughs in AI-powered perception that let robots see with sub-millimeter accuracy using cheap cameras, the challenges of simulating physical contact (friction is a nightmare), and why the best robot application ideas often come from people who know nothing about robots.Subscribe to The Neuron newsletter: https://theneuron.aiIntrinsic: https://www.intrinsic.ai/ROS (Robot Operating System): https://www.ros.org/AI for Industry Challenge: https://www.intrinsic.ai/events/ai-for-industry-challengeIntrinsic joins Google (Feb 2026): https://www.intrinsic.ai/blog/posts/intrinsic-joins-google-to-accelerate-physical-ai

Most businesses don't buy their AI services directly from OpenAI or Google—they buy it through a massive, invisible distribution network called "the channel." Victoria Durgin and Katie Bavoso of Channel Insider join Corey and Grant to explain how this hidden industry works, why AI is shaking it up unlike anything before, and what it means for businesses trying to adopt AI in 2026.Subscribe to The Neuron newsletter: https://theneuron.aiChannel Insider: https://channelinsider.com

In this episode of The Neuron Podcast, Corey Noles and Grant Harvey sit down with Dan Shipper, CEO of Every, to talk about agent-native engineering—the framework his team uses to build and ship AI-powered products at a pace most companies can't match.Dan walks us through what happened when his AI document editor Proof went viral (and then went down), why he believes the way we build software is fundamentally changing, and how Every's small team manages to ship and maintain an entire suite of AI tools: Spiral (automatic style guides from your writing), Sparkle (AI writing cleanup with custom folders), Cora (AI research assistant, now on iOS), Monologue (AI-powered journaling with notes), and Proof (the agent-first document editor that broke the internet for a day), as well as their new to be revealed on Friday: Plus One (a hosted AI agent for Slack).Whether you're a founder, developer, or just someone trying to understand what "agentic" actually means in practice—this conversation is the real-world playbook.Subscribe to The Neuron newsletter: https://theneuron.aiProducts mentioned:• Every: https://every.to• Spiral: https://spiral.computer• Sparkle: https://sparkle.computer• Cora: https://cora.computer• Monologue: https://www.monologue.to/• Proof: https://proofeditor.ai• Plus One (the new one!): https://every.to/plus-one

Nick Heiner leads RL environment development at Surge AI, the bootstrapped company that hit $1.2B in revenue training models for OpenAI, Anthropic, Meta, and Google. In this episode, we break down reinforcement learning environments—the secret training grounds where AI agents learn to actually do work. Nick shares why even the best models fail 40% of real workplace tasks, what happened when 200 Wall Street experts graded GPT-5 and Claude, and his prediction that a $1B company with one human employee could exist by 2030.A Special Thank You To Our Sponsor For This Video: Dell AI Factory with NVIDIA. Learn more at https://dell.com/yourwaytoaiResources: • Surge AI Research – Hierarchy of Agentic Capabilities: https://arxiv.org/abs/2601.09032 • Surge AI Blog: https://surgehq.ai/blog • Nick's Sonnet 4.5 Review: https://surgehq.ai/blog/sonnet-4-5-product-take • Nick’s Substack: https://nickheiner.substack.com/ • SurgeHQ’s enterprisebench: https://surgehq.ai/blog/enterprisebench-corecraft • Nick’s hilarious Gemini 3.1 review: https://nickheiner.substack.com/p/gemini-31-pro-not-leading-edge-also  • Hemingway-bench AI Writing Leaderboard https://surgehq.ai/blog/hemingway-bench-ai-writing-leaderboard • LMArena is a cancer on AI: https://surgehq.ai/blog/lmarena-is-a-plague-on-ai • Dell AI Factory with NVIDIA: https://dell.com/yourwaytoaiSubscribe to The Neuron newsletter: https://theneuron.ai

Proton—the company behind the world's largest encrypted email service with 100M+ users—just launched Lumo, a privacy-first AI assistant. We sit down with Eamonn Maguire, who leads Proton's ML team and built Lumo from the ground up. Eamonn has a PhD from Oxford and a postdoc at CERN, and he breaks down how Lumo's encryption actually works, why Big Tech's business model prevents them from building private AI, the real privacy threats hiding inside viral AI trends like Ghibli-fication, and whether AI agents are safe to connect to your bank account. Listeners will learn how encrypted AI handles your data differently, what open-source models power Lumo, and why "set-and-forget" agents are still more hype than reality.🔗 Links & Resources:Lumo by Proton: https://lumo.proton.me Proton: https://proton.me Lumo 1.3 (Projects): https://proton.me/blog/lumo-1-3 Lumo for Business: https://proton.me/blog/lumo-business Proton Sheets: https://proton.me/blog/sheets-proton-drive CLI for Proton Pass: https://proton.me/blog/proton-pass-cli Reserve your child's email: https://proton.me/mail/born-private/email Subscribe to The Neuron newsletter: https://theneuron.ai 

Carta CMO Nicole Baer joins Corey and Grant to break down the real state of startups in 2026. With half of all venture funding now flowing to AI-native companies and seed deals at a six-year low, the startup playbook has fundamentally changed. Nicole shares Carta’s data on solo founders, the new billion-dollar timeline, why the Bay Area’s grip is tighter than ever, and how AI is reshaping everything from marketing to fund administration.Carta State of Startups 2025 Report: https://carta.com/blog/state-of-startups-2025/Carta Data & Insights (free): https://carta.com/data/Subscribe to The Neuron newsletter: https://theneuron.ai