Podcast
AI News & Strategy Daily with Nate B. Jones
Hosted by Nate B. Jones · EN
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/
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46episodes
Episodes
Newest firstAll episodes
Which AI Model to Use for Any Task Without Overpaying
Jul 200:14:16Summary readyFor deeper playbooks and analysis: https://natesnewsletter.substack.com/What's really happening when every AI model suddenly looks replaceable?The common story is that model choice is the strategy, but the reality is that useful work comes from matching the model, the task, and the workflow surface.In this episode, I share the inside scoop on how to pick AI models without turning model selection into the whole job.Why daily-driver models are different from cheap workhorse models How to think about GLM, Kimi, Qwen, Claude, ChatGPT, and Codex What specialist tools are actually for Where harnesses and workflows matter more than raw model rankings Why fewer model choices can make teams fasterThis is for operators, founders, developers, and team leads who need practical AI work to keep moving even when the model landscape shifts underneath them.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.
SummaryHow to Build Your Own AI Memory With Claude or Codex
Jul 100:16:16Summary readyFor deeper playbooks and analysis: https://natesnewsletter.substack.com/What's really happening when agents stop being generic chatbots and start working from your memory, skills, and owned context?The common story is that AI agents are just another interface for automation - but the reality is that the ownership layer around memory, permissions, and workflow is becoming the product.In this video, I share the inside scoop on how an open personal agent stack starts to become buildable for normal people.Why memory changes what an agent can actually do How open skills turn repeated workflows into reusable methods What approval layers make agent ownership safer Where the personal agent stack starts to become practicalThis matters for operators, builders, marketers, and executives who want AI systems that work inside their actual context without handing away control of every account, secret, or permission.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.
SummaryThe AI Race Is Now About Context, Not Models
Jun 2900:17:13Summary readyFor deeper playbooks and analysis: https://natesnewsletter.substack.com/What's really happening when every major AI story starts pointing at context instead of raw intelligence?The common story is that the AI race is still only about who ships the newest frontier model -- but the reality is that the next advantage is who can connect useful intelligence to the context where work and life actually happen.In this episode, I share the inside scoop on why OpenAI's restricted ChatGPT 5.6 release, Apple's Siri strategy, Claude Tag in Slack, Codex adoption inside OpenAI, and GLM 5.2 are all part of the same hidden pattern.Why frontier slowdowns make context more valuable How Apple is trying to turn Siri into a personal-context assistant What Claude Tag reveals about workplace context and permissions Why Codex had to earn trust before people handed it sensitive work Where open models create pressure when frontier releases slow downFor builders, operators, executives, and AI power users, the point is not just which model is smartest. The point is which intelligence you trust with which context, and whether you can route that context without locking yourself into one provider.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.
SummaryGLM-5.2 Is Cheaper Than Claude. Why You Still Can't Switch
Jun 2800:17:35Summary readyCheap intelligence is here, but that does not mean the model is the bottleneck.In this briefing, I breakdown GLM 5.2, the cost pressure open-source models are putting on frontier labs, and why the next competitive edge is likely to come from the context and harness layer around AI work.The core question is not whether a cheaper model can answer a prompt. It is whether a team has enough of its own workflow, data, routing, and institutional context captured for that cheaper intelligence to matter.Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.
SummaryMake Your AI Agents Hand Off Work Without You
Jun 2600:22:03Summary readyFor deeper playbooks and analysis: https://natesnewsletter.substack.com/What's really happening when every AI tool becomes useful, but none of them know how to pass work to each other?The common story is that agents will become autonomous and take work off your plate - but the reality is that the bottleneck moves to handoffs, state, receipts, and review.In this video, I share the inside scoop on Open Engine: a practical way to make Claude, Codex, ChatGPT, OpenClaw, Hermes, and other agents act less like isolated subscriptions and more like a system you can operate.Why the human becomes the hallway when every loop lives in a separate toolHow a ticket or queue can carry work better than a chat threadWhat changes when a prompt asks for an answer but a ticket asks for a resultWhere agent handoffs need receipts, source material, stop points, and reviewHow Open Engine can work for teams, households, and real multi-agent workflowsThis matters for builders, operators, team leads, and anyone already using multiple AI tools. The next productivity jump is not just better models. It is better work movement: clear ownership, durable context, visible status, and a place where humans can review, accept, and build on what agents did.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.
SummaryBeyond Prompting: Building Loops That Carry the Load
Jun 2400:15:38Summary readyWhat's really happening when AI moves from one-off prompts to recurring agents that reduce the work sitting in your head?The common story is that better prompting is the path to better AI - but the reality is that most useful work is a recurring situation that needs memory, context, and boundaries.In this episode, I share the inside scoop on the "loop of loops" idea: how small AI workflows can notice each other, pass context, stop at the right moments, and bring you in only when judgment matters.Why a prompt is not the same thing as a loop How recurring jobs can hand off context without pretending to run your life What a school-trip workflow reveals about practical agents Where loops fit into research, open tasks, and daily attention How to spot one repeated job in your own life that could become a loopThis episode is for builders, operators, creators, and teams who want AI systems that carry real recurring load instead of adding another dashboard to manage. The shift is not magic autonomy. The shift is remembered workflows with clear state, useful triggers, and human boundaries.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.
SummaryClaude Fable 5: The Skill for Handing AI Whole Jobs
Jun 2300:18:11Tap to summarizeFable 5 is not just another smarter model. The important shift is that the bottleneck starts to move from model capability to our ability to imagine bigger, better-scoped work.Nate walks through five resets created by Fable 5: why benchmarks matter less than task size, why review queues and management matter more, and why the next edge belongs to people who can define whole jobs instead of writing tiny prompts.Full post: https://natesnewsletter.substack.com/p/claude-fable-5-how-to-use?r=1z4sm5&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true Hosted on Acast. See acast.com/privacy for more information.
Transcribe →Why Anthropic Actually Won the Month (Yes, Really)
Jun 2200:08:22Tap to summarizeFor deeper playbooks and analysis: https://natesnewsletter.substack.com/What's really happening in the OpenAI versus Anthropic race?The common story is that OpenAI had the winning week and Anthropic is on defense — but the reality is that talent, pre-training cadence, and recursive self-improvement may tell a very different story.In this video, I share the inside scoop on why Anthropic may be stronger than the headlines suggest, and why the most important AI story may be happening outside the model labs entirely.Why the obvious OpenAI victory narrative is incomplete How Anthropic's pre-trained model position changes the race What talent movement says about recursive self-improvement Why Midjourney's medical imaging bet matters Where AI energy is moving beyond OpenAI and AnthropicFor builders, operators, and AI strategists, the shift is not just who wins the model horse race. It is where intelligence, capital, and applied products start compounding into new categories.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.
Transcribe →Everyone You Know Is About to Try Claude (I Showed 3 People for 5 Minutes — All 3 Switched)
Mar 4Tap to summarizeWhat's really happening when millions of new users download Claude expecting a ChatGPT replacement and wonder why the spreadsheet features are missing? The common story is that AI models are interchangeable brands—but the reality is more interesting when constitutional AI produces measurably different behavior than reinforcement learning with human feedback.In this video, I share the inside scoop on why switching to Claude with the same habits misses the point:• Why Claude is more likely to tell you your plan has a hole in it• How describing your situation instead of your desired output changes everything• What extended thinking reveals about steering the chain of thought in real time• Where Cowork reframes the category from conversation partner to desktop workerFor anyone teaching a friend about Claude or learning it yourself, these differences shape how you think about AI over time—and that compounds.Subscribe for daily AI strategy and news.For playbooks and analysis: https://natesnewsletter.substack.com/p/millions-just-switched-to-claude© Nate B. Jones 2026 Hosted on Acast. See acast.com/privacy for more information.
Transcribe →You Don't Need SaaS. The $0.10 System That Replaced My AI Workflow (45 Min No-Code Build)
Mar 2Tap to summarizeWhat's really happening when Claude's memory doesn't know what you told ChatGPT and your phone app doesn't share context with your coding agent? The common story is that AI memory is getting better—but the reality is more interesting when every platform has built a walled garden designed to create lock-in.In this video, I share the inside scoop on why the architecture of agent-readable memory matters more than any individual tool:• Why your Notion workspace is beautiful for humans and useless for agents that search by meaning • How a Postgres database with vector embeddings runs for 10-30 cents a month • What MCP servers enable when one brain connects to every AI you touch • Where the compounding advantage lives for people who stop re-explaining themselvesFor anyone watching the agent revolution go mainstream, the gap between starting from zero and starting with six months of accumulated context is the career gap of this decade.Subscribe for daily AI strategy and news.For playbooks and analysis: https://natesnewsletter.substack.com/© Nate B. Jones 2026 Hosted on Acast. See acast.com/privacy for more information.
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