Everyday AI Podcast – An AI and ChatGPT Podcast

Everyday AI

The Everyday AI podcast is a daily livestream, podcast and free newsletter where we help everyday people grow their careers with AI. The Everyday AI podcast is hosted by Jordan Wilson, a former journalist who's now the owner of a boutique digital strategy company with 20 years of martech experience.  Our main focus is to help you keep up with AI trends to make your job easier. Get your work done faster. Increase your output.  Start Here Series Inner Circle Connect- Make sure to sign up for our daily newsletter at: https://youreverydayai.com- Email us: info@youreverydayai.com- Connect with Jordan on LinkedIn: https://www.linkedin.com/in/jordanwilson04/In the Everyday AI podcast, we'll cover all things artificial intelligence, machine learning, and practical tips on how to use both in your daily life. We'll include a touch on a variety of topics, software and applications. We may be covering the latest AI news from Microsoft, Google, Facebook, Adobe and social channels like Snapchat, Tiktok, and Instagram. Or, we may be diving into software like ChatGPT, Midjourney, Bard, or Runway ML. 

  1. 2h ago

    Ep 870: Open Source Surge? Does GLM-5.2 Make Open Source an Enterprise Priority? (Start Here Series Vol 29)

    Is the open model GLM-5.2 really Opus 4.8 level? 🤯 You mighta missed this, but over the past few weeks, three distinct forces have all converged at one:  ↳ Chinese open models are near frontier SOTA ↳ Microsoft is reportedly considering open models to run Copilot ↳ Enterprises everywhere are talking token efficiency as AI costs soar So while many are watching GLM-5.2 as an isolated model, it's important we dive deeper on its wider implications. Open Source Surge? Does GLM-5.2 Make Open Source an Enterprise Priority? -- An Everyday AI Chat with Jordan Wilson Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: Open Source AI's "ChatGPT Moment"GLM 5.2 Model Benchmarks & PerformanceEnterprise Adoption Drivers for Open AIMicrosoft Evaluating DeepSeek for CopilotToken Maxing to Token Efficiency ShiftGLM 5.2 Infrastructure vs. Consumer UseAutonomous Workflow Overshoot ExplainedCapability Gap and Workflow ChallengesEnterprise Scenarios for Open Source ModelsFuture of Task-Specific SOTA AI Models Timestamps: 00:00 Open source AI catching up 04:52 Enterprise shift to DeepSeek models 08:57 Comparing AI model performances 12:46 Running AI models locally 14:17 Open source model cost efficiency 17:37 Cost challenges with AI models 21:05 Agentic task token consumption 25:05 Introducing the Start Here series 27:58 Impact of AI on Job Roles 32:29 Evaluating Open Source AI Models 36:00 Considering open source models 37:09 Future of open source AI Keywords:  open source AI, open source AI models, GLM 5.2, z AI, Zhipu AI, Chinese open source models, DeepSeek, Microsoft, enterprise AI, token maxing, token efficiency, AI spend, AI deployment, open weight models, proprietary AI models, AI benchmarks, Artificial Analysis Intelligence Index, enterprise infrastructure, agentic workflows, coding tool use, autonomous agents, long context window, coding capabilities, API costs, AI privacy considerations, model distillation, data privacy, compute requirements, GPU infrastructure, AI hardware, API hosting, Hugging Face, AWS, AI cost reduction, Copilot Cowork, Azure security, Anthropic, OpenAI, Claude Opus, multimodal models, task-specific AI models, model capability gap, autonomous workflow overshoot, agentic tasks, non-agentic tasks, state of the art open models, model fine-tuning, small language models, AI adoption barriers, frontier models, AI job automation, workflow transformation, AI subsidies, token billing, Stanford AI study, AI industry trends Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 870: Open Source Surge? Does GLM-5.2 Make Open Source an Enterprise Priority? (Start Here Series Vol 29)

  2. 1d ago

    Ep 869: AI SuperApps: Why Every Company is Racing to Create One and What They are (Start Here Series Vol 28)

    Ready for the AI buzzword for the rest of 2026?  Superapps.  No, not China’s WeChat.  The AI Superapp era is much different, and it’s about to hit the business world hard. So, if you aren’t sure what an AI Superapp is or if your company should be using one, this is an episode you can’t miss.  AI SuperApps: Why Every Company is Racing to Create One and What They are — An Everyday AI Chat with Jordan Wilson Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: AI Super App Race: OpenAI, Anthropic, MicrosoftWhat Is an AI Super App? ExplainedAgentic Shift: Chatbots to Autonomous CoworkersSuper App Harness vs. AI Model as MoatThree-Pane Super App Interface InnovationCodex vs. Cursor vs. Claude BenchmarksEnterprise Desktop Integration and Super App StrategySuper App Security, Risks, and Best Practices Timestamps: 00:00 Super app race and ChatGPT integration 06:04 Emergence of desktop super apps 08:41 Codex as the leading super app 11:22 Shift to AI desktop super apps 14:13 The AI super app's proactive updates 17:26 Token efficiency in super apps 21:29 Future of AI model usability 27:03 Anthropic's role in AI development 30:19 Google's Gemini 3.5 and Anti-Gravity Launch 33:13 Risks and responsibilities with AI apps 34:31 Cautionary advice on AI usage 38:03 Introduction to AI super apps Keywords:  AI super app, AI superapps, super app era, desktop super app, agentic AI, autonomous coworker, agentic context carry, agentic work future, AI execution layer, super app harness, model moat, code interpreter, Codex, OpenAI super app, Microsoft super app, GitHub Copilot, Anthropic, Claude Code, Claude Cowork, Google anti gravity, Gemini 3.5 Flash, Cursor, desktop agentic coworker, unified memory, files automations, approvals and automations, browser control, computer use, three pane interface, context engineering, prime prompt polish, token efficiency, user experience, read-write access, autonomous workflows, desktop AI companion, schedule automations, approval workflows, cross-app integration, enterprise adoption, permission controls, role based access, sandboxing, expert-driven loop, AI safety, risk management, computer automation, enterprise AI strategy, AI model integration, productivity automation Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 869: AI SuperApps: Why Every Company is Racing to Create One and What They are (Start Here Series Vol 28)

  3. 2d ago

    Ep 868: Tokenmaxxing is over: The New Era of Token Efficiency and how Your Company Should Adapt (Start Here Series Vol 27

    More tokens = more ROI, right? 🤔 Maybe.  But probably not.  Maybe one of the weirdest AI trends that has oddly stuck in 2026 is tokenmaxxing -- the practice of individuals and companies racing to use as many AI tokens as possible and equating it with business progress.  Reality check: token efficiency is the real rage.  So, how do you measure token efficiency and how can your company avoid the cost pitfalls of tokenmaxxing?  Join us as we break it down. Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: AI Token Maxing: Rise and FallDefining AI Tokens and TokenizationFour Main Types of AI Token UsageAI Agentic Loops and Token ConsumptionCorporate Token Leaderboards and Meta ExampleRisks of Unmonitored Token Burn in EnterprisesToken Subsidies and AI Pricing TrendsMeasuring Token Efficiency versus Token VolumeBenchmarking Models: Cost per Intelligence OutputShifting from Model Selection to Harness EfficiencyBest Practices for Enterprise Token OptimizationMonitoring AI Agents for Token and Cost Control Timestamps: 00:00 Rethinking AI token usage 05:46 Token usage misconceptions in companies 09:15 Using token incentives 10:48 Tech companies adding usage limits 13:21 Understanding model token usage 17:16 Agentic models and tool use 22:21 Experimenting with token efficiency 25:18 Measuring AI's economic impact 29:11 Comparing AI intelligence and cost 30:36 Cost concerns with Anthropics' AI models 35:20 Importance of token efficiency 38:03 Takeaway from Microsoft CTO chat Keywords:  token maxing, token efficiency, AI token usage, AI tokens, token consumption, large language models, agentic loops, AI spend, token cost, model subsidies, subsidized AI plans, enterprise AI strategy, context window, prompt engineering, API usage limits, output tokens, input tokens, reasoning tokens, tool use tokens, scheduling agents, agentic AI, model harness, Claude Opus, OpenAI GPT-5.5, Gemini 3.1 Pro, Anthropic models, artificial analysis intelligence score, DeepSuite benchmark, cost per intelligence, modular AI architecture, API overages, context window size, scheduled agents, human-in-the-loop, expert-driven loop, output monitoring, benchmarking AI models, economic value from AI, efficiency metrics, measuring ROI, AI model performance, cost per output, chain of thought, AI tool integration, AI cost management, long-running agents, dynamic data integration. Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 868: Tokenmaxxing is over: The New Era of Token Efficiency and how Your Company Should Adapt (Start Here Series Vol 27

  4. 3d ago

    Ep 867: 2026 LLM Cheat Code: 10 Essential Steps To Get the Most out of Any AI Chatbot (Start Here Series Vol 26)

    This is the Everyday AI episode we probably shoulda done a while ago.... 👇 Because as different as ChatGPT, Gemini, Claude and others actually are under the hood, they have really started to copycat each other over the past 6 months.  Which means we finally have a set of concrete best practices to get the best outputs from any LLM.  Join us as we boil thousands of hours of experience into a 30-ish minute crash course that you can't afford to skip out on.  2026 LLM Cheat Code: 10 Essential Steps To Get the Most out of Any AI Chatbot -- An Everyday AI Chat with Jordan Wilson (Start Here Series Vol 26) Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: LLM Landscape: Cookie Cutter Model Trends10 Essential Steps for AI ChatbotsChoosing the Right AI Operating SystemSelecting Optimal AI Chatbot SurfacesImportance of Paid AI Chatbot PlansUnderstanding LLM Context Window LayersContext Engineering and Prompt Best PracticesIntegrating Files, Apps, and Company DataAI Chatbot Privacy, Permissions, GovernanceTransparency, Observability, and Reasoning ArtifactsVerification, Iteration, and Workflow Automation Timestamps: 00:00 Keeping up with AI changes 03:55 Introduction to AI chatbots essentials 09:05 Rapid innovation in AI models 13:01 Understanding early AI models 14:37 Choosing an AI operating system 17:08 Discussing desktop app benefits 21:14 Understanding the context layer 23:55 Challenges without web search integration 28:55 Advancements in CRM connectors 32:35 Challenges with AI governance 35:13 Importance of observability in workflows 37:36 Developing universal AI skills Keywords:  large language model, LLM, AI chatbot, AI operating system, ChatGPT, Claude, Gemini, Copilot, Perplexity, Grok, open models, cheat code for LLM, AI best practices, prompt engineering, context engineering, context window, context layer, reasoning models, generative AI, deterministic vs generative, web search in AI, model selection, paid AI model, free AI model risks, AI surface, desktop AI app, agentic capabilities, AI connectors, app integrations, business data privacy, permissions and governance, shadow IT, enterprise AI, observability, transparency, reasoning artifacts, workflow automation, verification loop, iteration in AI outputs, skill creation, plugin, automated workflow, agentic orchestration, company data security, expert driven loop, AI scheduling, context carry, modular AI, AI-powered work automation, personalized context, role-based access control, SaaS application integration, economic value of AI, knowledge work automation, prime prompt polish, refine queue, five five five framework, human-in-the-loop AI, knowledge cutoff, model versioning. Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 867: 2026 LLM Cheat Code: 10 Essential Steps To Get the Most out of Any AI Chatbot (Start Here Series Vol 26)

  5. 4d ago

    Ep 866: Build, Buy, Partner, or Wait: The 4-Layer AI Stack Decision Framework for 2026 (Start Here Series, Vol 25)

    The most expensive AI mistake of 2026 won't show up on any invoice. 💸 It'll show up two years from now when you can't get your data out, your competitors are eating your lunch, or your team is stuck maintaining software no one actually wanted to build. Because in 2026, AI isn't one decision anymore. It's four. The model. The workflows. Your data. Your business software. Each layer has its own build, buy, partner, or wait choice. And most companies are making all four without realizing it. Today on Everyday AI, we're breaking down the framework that puts those choices back in your hands. Build, Buy, Partner, or Wait: The 4-Layer AI Stack Decision Framework for 2026 (Start Here Series, Vol 25) An Everyday AI Chat with Jordan Wilson Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: Build vs. Buy vs. Partner vs. Wait in AIFour-Layer AI Stack Decision FrameworkEvolution of AI Agentic Workflows in 2026Buy vs. Build Decision ObsolescenceWhen to Build Proprietary AI SolutionsPrepackaged AI Workflows for Small BusinessesData Ownership and Integration StrategiesVendor Lock-In and Technical Debt RisksPartnering in Regulated or Critical WorkflowsWaiting for Stable AI CategoriesThree-Week AI Adoption BlueprintCapability Gap and ROI in AI Investments Timestamps: 00:00 Buy vs. build AI question 04:19 Start here podcast series intro 09:52 AI companies offering consulting services 11:27 AI skills and vertical integration 14:19 Evaluating AI adoption strategies 18:53 Building proprietary processes 20:28 Streamlining organizational workflows 23:48 Importance of strategic partnerships 27:34 Deciding on software investments 32:26 Evaluating tech capabilities and gaps 35:59 Implementing AI Workflows Step-by-Step 38:09 Accessing the start here series Keywords:  build vs buy AI, build or buy AI, build, buy, partner or wait, AI stack decision framework, four layer AI stack, AI implementation strategy, AI decision making, technical debt, vendor lock-in, agentic AI, AI agents, AI workflows, enterprise AI adoption, prepackaged agentic workflows, Microsoft Copilot, Google Gemini, OpenAI, Anthropic, domain assistants, specialized agents, model context protocol, large language models, custom AI solutions, proprietary data, workflow automation, data integration, business software AI integration, regulated workflows, audit heavy workflows, AI-powered business software, SAP autonomous enterprise, Codex, model portability, AI category stability, AI talent, agentic engineering, proprietary processes, competitive advantage, ownership map, workflow differentiation, capability gap, learning curve, risk management, OpenClaw, open source AI, modular AI skills, training gap, internal context, audit and score, governance, operational risk, partnership with AI vendors, regulated industries AI, SMB AI adoption, AI-driven business transformation, ROI, rate of innovation Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 866: Build, Buy, Partner, or Wait: The 4-Layer AI Stack Decision Framework for 2026 (Start Here Series, Vol 25)

  6. Sep 18

    Ep 865: Open Source AI 101: Why Local Models, Cheap APIs, and AI Agents Change Everything (Start Here Series Vol 24)

    Until a few months ago, open source AI was kinda a hobby project.  Now, it's tearing corporate boardrooms apart.  Why?  Over the past 6ish months, the gap between frontier closed AI and open sourced AI has shrunk to pretty much nothing. And with the surge of always on agents driving open models, their development and release schedule is on pace with the frontier labs.  So if your team isn't paying attention to -- and running test cases through -- open AI models, there's a good chance you'll either be overpaying or playing catch up soon.  We walk you through the 101 and what you need to know when it comes to open source AI in this Start Here Series special.  Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: Open Source AI vs Closed Models ShiftChinese Model Distillation & Legal ImpactsEnterprise AI Cost Triage StrategiesGoogle Gemma 4 Local Model CapabilitiesFrontier Model Performance Gap Closing24/7 Agentic AI Systems OverviewAPI Pricing War: DeepSeek vs US VendorsLegal Protection Tradeoffs for Open Source AIAI Workflow Triage: Task-Specific ModelsFuture Trends: Local and Specialized LLMs Timestamps: 00:00 Introducing the Firefly AI assistant 03:33 Open source AI cost benefits 09:25 AI model performance differences 10:19 Open source model improvements 15:28 Advancements in local AI capabilities 17:04 Impact of Google's Gemma four 22:15 Introducing Adobe's Firefly AI Assistant 24:19 Adobe Firefly AI assistant beta launch 29:26 Choosing the right AI tools 32:00 Shifting workloads to open source 33:31 Using open-source and closed models 36:47 The future of open models Keywords:  open source AI, open source models, local AI models, local models, closed source AI, closed models, proprietary AI, proprietary models, AI agents, agentic AI, AI workflow triage, cheap API, AI API costs, model distillation, Chinese open source models, China AI models, US AI models, Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 865: Open Source AI 101: Why Local Models, Cheap APIs, and AI Agents Change Everything (Start Here Series Vol 24)

  7. Sep 17

    Ep 864: Headless Software: Why Companies Are Building Software for AI Agents, Not Humans and what it means (Start Here Series Vol 23)

    Salesforce's cofounder essential questioned: why should you login to Salesforce anymore? 🤔 He wasn't signaling the AI-driven SaaSpocalypse was picking up steam.  Instead: he's talking about going headless.  What's that? It's a future where Salesforce -- any potentially many other household software giants -- stop making software interfaces for humans and start designing for AI agents instead.  So will this be a short-lived trend? Or, will the future of work not really involve a ton of humans clicking around?  Join us as we dissect the latest.  Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: Headless Software Definition and EvolutionAI Agents Versus Traditional Software InterfacesSalesforce Headless 360 and MCP ProtocolsOpenAI Workspace Agents Features and ImpactGoogle Vertex AI Rebranding to Gemini AgentsModel Context Protocol (MCP) and A2A IntegrationPer Seat Software Pricing DisruptionEnterprise Procurement for Agent-Ready SoftwareAgentic Commerce and Automated Bot Traffic TrendsStrategies for Auditing and Migrating Vendors Timestamps: 00:00 Shift to AI-first software development 05:39 Benefits of headless software 07:29 Headless software development insights 11:28 Salesforce launches headless 360 platform 14:15 The rise of headless software 19:10 AI model connectivity in 2026 23:24 AI's impact on software pricing 26:22 Discussing token maxing in business 28:25 AI agents impacting human commerce 32:16 Evaluating software and vendor choices 35:46 Competitive advantage in software pricing Keywords:  headless software, interface-less software, headless software trend, software for AI agents, agent-first platforms, Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 864: Headless Software: Why Companies Are Building Software for AI Agents, Not Humans and what it means (Start Here Series Vol 23)

  8. Sep 16

    Ep 863: Agentic Context Carry: 3 Steps to Improve Cowork and scheduled AI Workflows (Start Here Series Vol 22)

    Info hunting and juggling sound familiar?  It’s the downfall of almost any business leader. Where is that email from Emily? Why can’t I find last quarter’s budget in Drive? Oh, and Keenen needs an answer back on that research project. Oh shoot, I swear Caleb confirmed the expenses in one of these Slack channels.  You’re off an information rabbit hole and by the time you find that Slack message, you already forgot what Emily’s email said.  Hit home? Well, as AI models expand to Coworking and Scheduled agents, we have a new best friend that doesn’t really have a name.  (Until we randomly named it. Lolz)  Scheduled Agentic Context Carry. You need to know what it is, why it’s important, and how to use it.  We’ll dive in.  Newsletter: Sign up for our free daily newsletter More on this Episode: Episode Page Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders. Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup Website: YourEverydayAI.com Email The Show: info@youreverydayai.com Connect with Jordan on LinkedIn Topics Covered in This Episode: Scheduled Agentic Context Carry (SACC) ExplainedAI Agents: Features vs. Benefits ParadigmCo-Working and Scheduled AI Workflow ShiftPersistent Context and Memory in AI AgentsLarge Language Models’ 1,000,000 Token Context WindowsWorkflow Automation: Eliminating Human-AI Duct TapeMulti-App Integration and Cross-Platform ContextThree Steps to Deploy Scheduled Agentic Context CarryChain of Thought Iteration with Scheduled AgentsAutonomous Agent Limitations and Future Bridge Timestamps: 00:00 Explaining SACC and AI benefits 03:43 Introducing the Start Here series 06:26 Rise of AI in enterprises 11:55 AI agents learning industry trends 15:08 Agent capabilities in AI systems 16:47 Explaining complex trends simply 20:13 Streamlining tasks with AI agents 24:18 Understanding AI and context windows 27:43 Understanding prompt engineering basics 30:51 Debugging and reviewing schedules 33:08 Building automated workflows this quarter Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 863: Agentic Context Carry: 3 Steps to Improve Cowork and scheduled AI Workflows (Start Here Series Vol 22)
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The Everyday AI podcast is a daily livestream, podcast and free newsletter where we help everyday people grow their careers with AI. The Everyday AI podcast is hosted by Jordan Wilson, a former journalist who's now the owner of a boutique digital strategy company with 20 years of martech experience.  Our main focus is to help you keep up with AI trends to make your job easier. Get your work done faster. Increase your output.  Start Here Series Inner Circle Connect- Make sure to sign up for our daily newsletter at: https://youreverydayai.com- Email us: info@youreverydayai.com- Connect with Jordan on LinkedIn: https://www.linkedin.com/in/jordanwilson04/In the Everyday AI podcast, we'll cover all things artificial intelligence, machine learning, and practical tips on how to use both in your daily life. We'll include a touch on a variety of topics, software and applications. We may be covering the latest AI news from Microsoft, Google, Facebook, Adobe and social channels like Snapchat, Tiktok, and Instagram. Or, we may be diving into software like ChatGPT, Midjourney, Bard, or Runway ML. 

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