The Neuron: AI Explained

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.

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 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.

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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.

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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.

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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/

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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.

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/wxp

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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 behalf

By 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 workflow

Get beginner-friendly AI explainers, practical tutorials, and daily updates on what matters in AI.

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