Stay ConnectedThe Neuron is a daily newsletter with 700,000+ readers that covers the latest AI developments, trends and research; this is our podcast, hosted by Grant Harvey and Corey Noles. We aim to create digestible, informative and authoritative takes on AI that get you up to speed and help you become an authority in your own circles. Available Wednesdays and Sundays on all podcasting platforms and YouTube.
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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 problems
They’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/
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Sponsored 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 Fable
Also: 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 professionals
Join 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 next
If 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.
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