AI News & Strategy Daily with Nate B. Jones
Nate B. Jones
Daily AI strategy and news for the AI curious, builders & executives. I'm Nate B. Jones, a 20-year product leader, AI strategist, and your guide through the noise. Most AI content is hype or generic advice. I cut through both with frameworks and workflows you can use immediately. Whether you're an executive making AI decisions or a builder implementing solutions, you'll get practical guidance, tested in real organizations. New videos every day on YouTube. Deeper analysis + exclusive playbooks → https://natesnewsletter.substack.com/ Hosted on Acast. See acast.com/privacy for more information.
Episodes
Mentioned books
Oct 4, 2026 • 36min
How AI agents are changing the way you buy software
AI agents are rewriting the value of software, from DoorDash and recruiting platforms to Salesforce, Microsoft, and payroll systems. The discussion explores why interfaces may become disposable while trusted data, compliance, institutional knowledge, and customized workflows endure. It also examines Meta’s business ambitions, AI labs’ push for distribution, and why teams must document the hidden ways they use AI.
30 snips
Oct 3, 2026 • 39min
OpenAI DevDay 2026: Dots, ChatGPT Space, and GPT-6.1 Sol
OpenAI DevDay spotlights agents built for real work: Dots handles recurring responsibilities, Spaces brings people and AI into shared projects, and GPT-6.1 Sol targets efficient reasoning. The discussion explores context-rich assistance, meeting workflows, model selection, premium plan economics, decision APIs, enterprise adoption, and a new builder economy inside ChatGPT.
18 snips
Oct 2, 2026 • 26min
Microsoft's Autopilot Agent: 5 AI Habits to Build at Work
Microsoft Autopilot is bringing agent-style work into familiar workplace tools. Explore why enterprise distribution and proprietary data may outweigh raw model power, how to define assignments and supply reliable context, and when to automate recurring processes. The discussion also covers evidence checking, right-sizing reasoning for risk, and building feedback loops that make AI work better over time.
30 snips
Sep 30, 2026 • 25min
Claude Opus 5.5 Review: Easier to Steer, Fewer Tokens
A 514-piece LEGO logo built from code puts Opus 5.5’s visual skills and token efficiency to the test. The discussion examines true task costs, including retries, file reads, and human effort, plus writing that preserves intent and overnight assignments with clear stopping conditions. It also covers AI-assisted model development and a practical framework for comparing releases on real work.
29 snips
Sep 29, 2026 • 31min
An AI assistant added up my subscriptions: $5,350 a year. The prompt guide to get your own list in about 20 minutes.
An AI assistant uncovers costly subscriptions, negotiates bills, coordinates family schedules, and tackles everyday admin. The discussion explores why simple design and personal context build trust, how assistants could become shopping gateways, and why Amazon may see them as a threat. Also examined: transaction fees, subscription inertia, and the race to become the next platform layer.
31 snips
Sep 27, 2026 • 33min
How to Scale AI Developer Productivity Across a Team
What makes AI-assisted coding scale beyond one fast developer? This discussion explores shared agent workspaces, durable project history, human accountability, automated checks, reliable handoffs, and safer multi-agent collaboration. It also examines how to remove outdated process, diagnose team bottlenecks, and measure shipped customer value instead of pull-request volume.
28 snips
Sep 24, 2026 • 46min
NVIDIA World Models Explained: What Developers Can Build
Ming-Yu Liu, NVIDIA’s Cosmos Lab VP, explores how world models help robots understand environments, simulate scenarios, and take physical action. They unpack the gap between language and physical AI, the challenges of real-time robotics, and why physics remains difficult for black-box models. The conversation also covers verification, specialized models, robotic skills, and why tasks with measurable results may advance fastest.
34 snips
Sep 22, 2026 • 42min
AI-Native Workplace: What Real AI Adoption Asks of You
What happens when AI can operate across your computer, navigate legacy systems, and turn recurring work into shared automation? This conversation explores context-driven adoption, agents sharing digital workspaces, voice input paired with visual output, and the evolving roles of orchestration, experimentation, taste, and human judgment. Real-world examples include unexpected creative tools and a costly tax error caught through expanded context.
58 snips
Sep 21, 2026 • 33min
You cannot tell which parts of your software should stop calling an LLM. My Jev guide has a prompt that scans your projects and names them.
What if software could understand messy language yet make only a simple choice? This discussion explores JEV as a fast, affordable classification layer for support routing, tax documents, research triage, agent safety, browser orchestration, and meaning-aware spreadsheets. It also covers testing JEV against LLMs and humans, plus how cheaper judgment could reshape which decisions teams automate.
59 snips
Sep 20, 2026 • 31min
AI Cost to Serve: Which Customers You Can Now Afford
AI agents may be getting smarter, but wider adoption can send costs soaring. This discussion explores redesigning workflows before automating them, routing routine requests to cheaper models, and matching tools to model capability. It also examines outcome-based evaluations, removing handoffs, and measuring business value beyond token bills.
