The Neuron: AI Explained

A practical 5-level roadmap for getting real value from AI, from organizing Projects to building decision-making Agents. Hands-on demos show prompting best practices, creating reusable Skills, scheduling Automations, and connecting tools like Claude, ChatGPT, and Gemini. Live walkthroughs include building a JobSearchManager, uploading files, and turning tasks into repeatable workflows.

Brian Gerkey, CTO of Intrinsic and co-creator of ROS, is a robotics software pioneer focused on bringing AI to physical machines. He discusses physical AI moving off screens, Intrinsic’s Android-like platform for robots, vision breakthroughs that give sub-millimeter accuracy with cheap cameras, the simulation challenges of contact and friction, and why great robot ideas often come from non-robotics experts.

Katie Bavoso, Channel Insider contributor who covers MSPs and AI adoption. Victoria Durgin, Channel Insider editor and channel expert who maps distributors and resellers. They unpack the invisible IT channel that delivers AI to businesses. Topics include how AI flows through MSPs and marketplaces, tools built for partners, vertical specialization, integration and data hurdles, and why MSPs both protect and amplify AI hype.

Dan Shipper, CEO of Every and builder of AI apps like Proof and Cora, explains agent-native engineering and how small teams ship agent-first products. He covers Plus One for Slack, agent-run workflows that build trust, security and account strategies, and lessons from Proof's viral launch and stabilization. Practical tips include plan mode, model surfing, and the pirate-plus-architect approach to speed and stability.

Nick Heiner, head of RL environments at Surge AI who builds simulated workplace benchmarks, walks through the secret training grounds where agents learn real work. He covers what makes realistic environments, why many models fail messy real-world tasks, CoreCraft for e-commerce simulations, multi-agent market sims, and why rigorous evals and reward design are crucial.

Eamonn Maguire, a machine learning leader at Proton with a PhD from Oxford and CERN postdoc, built the privacy-first AI Lumo. He explains how encrypted inference and client-side indexing protect user data. He exposes why Big Tech can’t build private AI, warns about viral image trends and agent risks, and outlines Proton’s model routing, purge policies, and private memory designs.

Nicole Baer, Carta CMO and two-time founder with ~25 years in tech marketing, breaks down 2026 startup shifts. She covers how half of VC now backs AI-native companies. She explains fewer deals but bigger checks, the rise of solo founders, faster billion-dollar trajectories, and how AI is changing marketing, go-to-market, and fund administration.

Kari Briski, VP of Generative AI Software for Enterprise at NVIDIA, leads the Nemotron model family. She unveils Nemotron 3 Super and explains how a 120B model can perform like a 12B through routing and efficiency. Conversation covers multi-agent systems moving to production, OpenClaw as a system-level security and orchestration approach, and the rapid growth of open-model token use.

Dr. Qichao Hu, founder and CEO of SES AI who builds AI-driven autonomous labs for faster materials R&D. He explains how AI agents and robots compress an eight-year research cycle into weeks. They discuss lithium metal batteries, high-throughput wet lab testing, predicting lifetime from short tests, and building a vast molecular database to accelerate discovery.

Yaron Inger, CTO and co-founder of Lightricks and LTX, leads development of open-source video and audio generative models. He discusses LTX-2’s rise, why open weights matter for control and fine-tuning, and how local, consumer-GPU workflows enable new filmmaking tools. Topics include practical editing flows, integrating 3D/animation, distillation for efficient models, and possibilities for interactive, real-time educational video.