Advertise on podcast: AI News & Strategy Daily with Nate B. Jones

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ Nate explains why familiar seat and token pricing models leave companies responsible for turning intelligence into business value. Cedar's Kora example illustrates the difference between buying usage and paying for outcomes. A hypothetical equipment-service business shows how deployment knowledge and commercial partnerships shape the result. The practical question for leaders and employees is where to allocate intelligence: finish existing work faster, fix a recurring customer problem, or free people to pursue a revenue project that was previously out of reach. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ Nate explains why AI is changing both sides of cybersecurity: agents can investigate unfamiliar code and connections tirelessly, while stolen AI keys can give attackers access to computation billed to someone else. What this week's security incidents reveal about the systems we trust.Why updating software may not resolve exposed credentials.How to evaluate an AI model's ability to follow an investigation.What individuals can do about connected apps, browser extensions, passwords, and breach notices. The practical takeaway is to reduce unnecessary access, investigate what actually ran, and verify that defensive actions worked. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

Can better understanding of AI make more powerful models safer? Nate explains why Goodfire’s research on interpreting neural networks gives him reason for optimism, while separating demonstrated findings from the products and safeguards that still need to be built. He connects the research to four possibilities: safer delegation, more confidence building capable models, professional tools that help investigate decisions, and everyday products that let people correct what an algorithm has learned about them. He closes with a practical way to use AI to understand technical papers and verify the answers against the source. Hosted on Acast. See acast.com/privacy for more information.

Before buying a bigger computer for AI agents, find out what is consuming the machine you already have. Nate explains how to diagnose memory and storage pressure, give agents a stopping condition, and schedule demanding work around the resources available. The episode covers the difference between cloud and local workloads, why more CPU cores do not translate directly into more agents, and how an old computer can become a useful dedicated agent machine. The aim is a more intentional hardware decision and a repeatable maintenance routine. Hosted on Acast. See acast.com/privacy for more information.

AI agents are beginning to coordinate across the public internet. Nate looks at researchers contacting an agent fleet, laboratory self-replication experiments, and what these developments could mean for the websites and tools we use every day. The episode explores an internet with different levels of agent access, practical security precautions for individuals and infrastructure teams, and the control systems companies need before using swarms at work. The central question is how to make the internet more useful for people as agents become a larger part of it. Hosted on Acast. See acast.com/privacy for more information.

Reverse Engineer Anything(REA) is more useful than a shortcut for copying apps. Nate explores how inspecting real software can reveal the requirements, relationships, and edge cases behind the interface—and help you explain what your own software should do. Examples include authenticator codes, Notion copy and paste, Windows Calculator percentages, accounting behavior, and game mechanics. The practical takeaway: investigate a behavior, predict its result, and build checks that show whether you understood it. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ What does superhuman performance in mathematics tell us about the future of work? Nate examines OpenAI's mathematical research release and why strong performance in one domain does not automatically transfer to software engineering or business judgment. Why checkable mathematical results differ from maintainable software.How a document-search feature can pass tests and still create a privacy problem.Why discovering the right question matters as much as generating an answer.What focus, experience, and the desire to make an impact still contribute. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ What can you take on now that AI can help with more of the work? Nate revisits five human qualities that become more useful as AI grows more capable: taste, agency, focus, resourcefulness, and follow-through. How taste turns care about a problem into something you can build and test.Why agency means making an attempt and learning from it.What sustained focus contributes when starting new projects gets easier.How resourcefulness helps you keep the intent while changing tools.Why shipping a first version is only part of finishing the job. For builders and leaders making plans for 2027, the practical question is which previously ruled-out project deserves another look—and what it would take to make it useful to someone. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ What is your work actually worth—and who gets paid when its records are sold? Nate examines the proposed sale of Spirit Airlines data and the broader market for company records used to train AI agents. He distinguishes the work that creates value from the messages, documents, and presentations left behind. Through an invoice example, he asks who defines a task as done, what simulations can teach agents, and how workers and employers can preserve the context that makes work useful. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ Can Google and Meta actually catch up in AI? Nate argues that customer obsession is becoming the new benchmark. He looks at who the major labs serve, how dots and Muse complement each other, and why useful product experiences matter more than leaderboard positions. From sorting a personal library to helping people manage everyday tasks, the next opportunity belongs to builders who understand their customers and use the products they sell. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ Better agents are changing what software is worth. Nate examines how agents change the value of data, applications, and the workflows people build around them, from DoorDash to Microsoft, Salesforce, and recruiting. He explains why a tool can become easier to leave while a trained agent becomes harder to replace, and what software buyers, sellers, and individual team members can do about it. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ The agent wars are here. Nate examines OpenAI DevDay through the jobs agents actually get right: ongoing responsibilities with Dots, shared work in Space, efficient reasoning with Sol, and new opportunities for builders. He compares agent form factors with practical utility, explains why context matters, and weighs faster models and higher subscription tiers against time saved and value created. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ Microsoft is bringing agent-style work into the tools people already use. Nate examines what Autopilot changes and five practical skills for getting better results from AI: defining the assignment, supplying the right context, making useful work repeat, matching reasoning to difficulty, and improving the next run. He explores why enterprise distribution matters, how source conflicts undermine answers, and why the price of a model is only part of the cost of getting a job done. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ What does an AI task actually cost when you count the whole job? Nate examines his Opus 5.5 LEGO build, the difference between API pricing and a subscription allowance, and why fewer retries can matter as much as the price per token. He also explores writing that preserves your intent, clearer stopping conditions for overnight work, and a practical way to rerun your own assignments when a new model arrives. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

For deeper playbooks and analysis: https://natesnewsletter.substack.com/ What makes a consumer AI assistant useful enough for people to return to it? Nate examines Meta’s Muse, the everyday work it can take off people’s plates, and what its conflict with Amazon reveals about attention and commerce. Finding recurring costs and acting on subscriptions.Making complex AI work feel simple.Why the shopping journey matters to Amazon and retailers.How personal context can shape competition between assistants. Nate’s savings figures describe future spending avoided, not a cash refund. Other users’ insurance savings are self-reported. The subscription-revenue findings concern an inattention model. Subscribe for daily AI strategy and news. Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.