Everyday AI Podcast – An AI and ChatGPT Podcast

Everyday AI
  • 4.7 (149)
  • Technology
  • Updated Daily

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. 19h ago

    Ep 876: The Most Important AI Model You’ll Probably Never Use That Just Dropped (Replay)

    You've probably never heard of Inkling.  It's the newest (and first) model from Thinking Machines Labs, and it could very well be a small snowball that picks up major momentum in today's enterprise AI landscape.  If you haven’t heard of Thinking Machines, they’re led by Mira Murati, the former CTO at OpenAI.  The big bet with Inkling?  The future of AI could be using smaller models fine-tuned and optimized for smaller tasks.  Will it work?  Tune in live as we dive in.  The Most Important AI Model You’ll Probably Never Use That Just Dropped -- An Everyday AI Chat With Jordan Wilson (Replay)  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: Inkling AI Model Launch OverviewThinking Machines Lab Leadership HighlightInkling's Multimodal and Agentic CapabilitiesOpen Source vs. Proprietary AI ModelsEnterprise Procurement with American AI ModelsAI Fine Tuning as a Service (Tinker)Benchmark Scores: Inkling vs. Frontier ModelsCustomization and Model Shopping for EnterprisesAI Token Costs Driving Model EfficiencyBridgewater Case Study: AI Model CustomizationFrontier Models Enabling Efficient Fine-TuningFuture Trends: Specialized Small Language Models Timestamps: 00:00 Inkling: A new AI model release 05:43 Inkling AI model details 09:08 China's dominance in open source AI 11:48 Launch and model updates discussed 15:21 Concerns over using Chinese open-source models 19:06 Training smaller AI models 20:22 Using GPT for AI Model Training 23:54 Predicting Rise of Small Language Models 28:38 Choosing the right AI model Keywords:  Inkling, Thinking Machines Lab, Meera Muradi, former OpenAI CTO, open source AI model, American AI model, fine tuning as a service, enterprise AI, multimodal AI, agentic models, customizable AI, Tinker, enterprise distribution, model procurement, Chinese open source models, strategic reset, model overhang, capabilities gap, AI model shopping, model routing, cost-conscious enterprises, artificial intelligence index, 975 billion parameter model, text-image-audio AI, open weights, proprietary AI models, customization accessibility, small language models, AI workflows, context window, Bridgewater use case, model distillation, GPU infrastructure, API costs, token efficiency, fine-tuned models, post training, AI competitive leverage, recurring financial judgment, AI benchmarks, middle tier models, automated model evaluation, privacy and workflow mapping, economical AI models, model rental, model routing automation. Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 876: The Most Important AI Model You’ll Probably Never Use That Just Dropped (Replay)

  2. 2d ago

    Ep 875: RSI Explained: When AI Starts Improving Itself and What It Means (Replay)

    Intelligence too cheap to meter -- could that actually be coming? 🤑 Maybe, and you mighta missed one of the biggest signs.   OpenAI said that its own model improved itself after release so well, that it was cutting prices to one model by 80%.  What's that mean?  Well, by definition, it's a broad example of Recursive Self Improvement, or when a model starts building better versions of itself.  And over the past 8 weeks, RSI has gone from a science fiction future to an actual, near-term reality.  So what happened and what changed? And what does it mean for your company?  We break it all down.  RSI Explained: When AI Starts Improving Itself and What It Means -- An Everyday AI Chat with Jordan Wilson (Replay) 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: OpenAI's GPT-5.6 Soul Self-ImprovementRecursive Self-Improvement (RSI) Definition & ImpactCutting AI Model Costs by 80%Timeline Acceleration for RSI AdoptionGoogle and Anthropic's RSI Research InitiativesAI Automation: Building and Training AI ModelsIndustry Call for Slowing Down AI PaceSuperintelligence, AGI, and the Singularity DiscussionPractical Implications of RSI for BusinessesSecurity and Oversight Concerns with Self-Improving AI Timestamps: 00:00 AI self-improvement and price cuts 06:33 AI startup funding and regulation concerns 09:14 AI misconceptions and public disconnect 11:29 Advancements in AI self-improvement 16:16 Development of AI Models 21:07 Sam Altman on reaching singularity 23:04 Entering the AI singularity era 26:37 Advancements in AI models 30:43 China's advancements in AI models 34:24 AI self-improvement and containment issues 37:01 Planning for AI cost reduction 40:00 AI controlling other AIs with GBD 5.6 42:46 Closing and subscription reminder Keywords:  Recursive self improvement, RSI, AI self-improvement, AI improves itself, agentic AI, token efficiency, token maxing, OpenAI, GPT-5.6 Soul, Luna model, AI cost reduction, post-training, AI automation, automated AI researcher, Anthropic, Claude Code, Codex, Google DeepMind, AGI, Artificial General Intelligence, Superintelligence, Artificial Superintelligence, ASI, Singularity, Sam Altman, AI acceleration, AI research automation, Frontier Labs, Pacing the Frontier, AWS compute deal, capital expenditures, data centers, CapEx, model distillation, small language models, AI capabilities, AI benchmarks, model variants, model efficiency, AI safety, technology acceleration, AI containment, AI security, open source AI, AI deployment, technology disruption, modular AI systems, price reduction AI, AI industry, AI timeline, human oversight AI, AI risk management, AI regulation. Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 875: RSI Explained: When AI Starts Improving Itself and What It Means (Replay)

  3. 4d ago

    Ep 874: Scheduling AI: how to easily make AI work for you in Claude, Gemini and ChatGPT (Replay)

    Scheduled tasks are a secret weapon. ⚔️ How secret?  They can actually be hard to find and there's not a lot of info out there on how to use them. lolz.  But for many, they can be the stepping stone to the fully autonomous desktop worker. Because for many users who may only be able (or comfortable) to access AI on the web, scheduled tasks provide that proactive, work-done-for-you vibe that AI agents delivered.  But how does it work in Gemini, ChatGPT and Claude?  And what's worth scheduling and automating?  We put AI to work on this Wednesday and find out.  Scheduling AI: how to easily make AI work for you in Claude, Gemini and ChatGPT -- An Everyday AI Chat with Jordan Wilson (Replay) 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: Introduction to Scheduling Tasks in AIGoogle Gemini Scheduled Actions OverviewChatGPT Scheduled Tasks Features & HacksChatGPT Work Mode and Virtual BrowserClaude Scheduled Tasks vs. Routines ComparisonUsing API Triggers with Claude Code RoutinesReal-World AI Dashboard Scheduling TestDetailed Results: Gemini vs. Claude vs. ChatGPTKey Takeaways for Best Automated SchedulingPractical Use Cases for Scheduling AI Tasks Timestamps: 00:00 Using scheduled tasks effectively 06:00 Adopting AI for productivity 06:51 Discussing main AI platforms 12:45 Scheduling tasks with ChatGPT 14:38 Work mode and virtual browsing 17:58 Creating and Editing Scheduled Tasks 22:47 Using Claude's cloud routines 26:59 Creating interactive stock visuals 27:51 Tracking AI company stock trends 31:58 Reviewing AI stock tracking tool 35:35 Improving user interface and experience 39:23 ChatGPT's unique scheduling features 41:49 Using APIs in Claude routines 44:45 Dashboard automation and triage setup Keywords:  AI scheduling, scheduling AI, scheduled tasks, scheduled actions, proactive agentic workflow, agentic adoption, agent built workflow, Google Gemini, Gemini scheduled actions, Gemini connectors, Gemini canvas mode, ChatGPT scheduling, ChatGPT scheduled tasks, ChatGPT work mode, ChatGPT projects, ChatGPT memory, ChatGPT sites, agentic app actions, model selector, reasoning level, app automation, connectors and skills, OpenAI, Claude scheduling, Claude scheduled tasks, Claude routines, Claude code, Claude co work, Claude home, Claude API token, Zapier integration, trigger-based automation, custom dashboards, triage dashboard, interactive visual, stock price dashboard, news summarization, personalized automation, user interface changes, web interfaces, desktop agents, repetitive tasks automation, business process automation, workflow optimization, productivity AI tools, AI-powered research, CRM integration, KPI tracking Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 874: Scheduling AI: how to easily make AI work for you in Claude, Gemini and ChatGPT (Replay)

  4. 6d ago

    Ep 873: The Next 12 months of AI: 19 Predictions Every Business Leader Needs to Hear (Replay)

    The next 12 months of AI leaked.  Kinda.  For the past 90ish days, we've been quietly collecting evidence of what's next. 1,030 saved posts. 90 Podcasts. Countless conversations. Every model drop, every leak, every quiet product update the big labs hoped you'd scroll past. Then we connected the dots. What came out the other side: 19 calls on where AI goes over the next 12 months. And some of them are uncomfortable. We're walking through all 19.  Bring your team's AI roadmap. You'll want to edit it. 👇 The Next 12 months of AI: 19 Predictions Every Business Leader Needs to Hear -- An Everyday AI Chat with Jordan Wilson (Replay) 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: Reactive Chat Dies, Proactive AI Agents RiseVoice and Mobile Become AI Default InterfaceManager Threads Replace One-Off AI ChatsMultiplayer AI: Humans and Agents CollaborateCompany-Wide Vibe Operations with ChatGPT SitesAgent Native Workflows and Resources StandardizationSkill Reuse as Key Company MetricCompany Reasoning Data as Strategic GoldShift from Public Leaderboards to Private EvalsModel Routing Becomes AI Industry NormCheaper AI Intelligence, Anthropic Competition HeatsFortune 100 AI Token Spend EfficiencyCompute Power as New AI CurrencyLocalized AI Controversies and Election DeepfakesMainstream AI Backlash and Content DetectionMath Benchmarks Solved by Advanced AIToken Maxing Returns with Cost DeclineOpen Agents Crash Risks and CybersecurityRecursive Self Improvement (RSI) in AI Development Timestamps: 00:00 Starting the AI 101 series 03:35 Yearly AI predictions roundup 07:54 Using full duplex AI assistants 09:45 Talking vs. Typing to AI 13:45 Breaking down AI silos 19:03 Turning processes agent-native 22:32 Skill development and reuse in AI 24:09 Bringing Slack DMs into Channels 29:46 Dealing with AI usage limits 30:45 AI startups revolutionizing knowledge work 35:46 AI strategy in Fortune 500 companies 40:11 AI impact on local politics 41:58 Concerns Over AI Watermarking 46:52 Experiencing token budget challenges 51:05 Sergey Brin prioritizes RSI at Google 52:06 Discussing AI model improvements 55:24 Closing and subscription reminder Keywords:  AI predictions, AI trends, business AI strategy, proactive AI agents, reactive chat, AI operating systems, ChatGPT, Claude, Grokbot, voice and mobile AI control, full duplex agent, AI skills, skill reuse, manager threads, multiplayer AI, agent native, company reasoning data, private AI benchmarks, public leaderboards, private evals, model routing, AI token spend, open source models, compute scarcity, hardware scarcity, AI controversies, local AI data centers, AI deepfakes, AI backlash, AI content detectors, AI in politics, math solved by AI, token maxing, cyber defense, open agents, cybersecurity budget, recursive self improvement, RSI, Fortune 100 AI usage, AI workforce transformation, dashboard automation, AI for dashboards, no-code AI apps, business intelligence AI, automation skills, agent crashes, model overhang, vendor lock in, AI-powered cyberattacks, AI-driven skill creation, AI-enabled workflows, token efficiency, AI local hosting, cost-effective AI models, enterprise AI adoption, AI asset management, company AI metrics. Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 873: The Next 12 months of AI: 19 Predictions Every Business Leader Needs to Hear (Replay)

  5. Sep 29

    Ep 872: AI Cost Control 101: Why Your Chatbot Bill Is Becoming a Board-Level Problem (Start Here Series Vol 31)

    AI’s all-you-can-eat era is ending. 🍲 For years, one subscription felt like unlimited access to frontier models. But that business model for the AI labs apparently breaks when agents can now run for days, use tools, retry work and burn through tokens. And with Anthropic's powerful Fable 5 model exiting subscription tiers today and moving to API only pricing, it's as imperative of a time as ever to figure out your AI spend strategy.  Frontier AI is becoming a metered utility. On today's show, we teach you how to deal with it.  AI Cost Control 101: Why Your Chatbot Bill Is Becoming a Board-Level Problem -- 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: End of Unlimited AI Subscription PlansAnthropic Fable Five Subscription RemovalCopilot and Grok Switching to Pay-Per-UseEnterprise AI Cost Control ChallengesToken Consumption in Agentic AI ModelsBoard-Level AI Spending ConcernsStrategies for AI Spend OptimizationFine-Tuning and Multi-Model Routing SolutionsSeven-Step AI Cost Reduction Playbook Timestamps: 00:00 Rising AI costs and usage 05:18 AI service cost challenges 10:18 Cost of AI and OpenAI's Future 14:18 Chatbot costs becoming a big issue 15:10 Automating work with desktop agents 19:26 Hidden costs of automation loops 24:13 The future of model mixtures 25:16 Microsoft Foundry's fine-tuning service 31:20 Fine tuning AI models 32:13 Closing thoughts on AI future Keywords:  AI cost control, chatbot bill, AI spend, token efficiency, metered AI, agentic models, AI subscription plans, Fable Five, Anthropic, API pricing, OpenAI, GPT-5.6, Copilot cowork, GitHub Copilot, Google Gemini, AI credits, usage limits, credit-based system, Grok, NeoCloud, board-level AI concerns, token maxing, spending limits, enterprise AI, SMB advantage, API token pricing, token-based billing, model routing, open source AI models, GLM 5.2, Kimmy 2.7, caching, difficulty-based routing, fine-tuning models, Microsoft Foundry, fine-tuning as a service, Thinking Machines Lab, tuned specialists, mixture of models, AI routers, perplexity, Merge, spend routers, AI budgeting, overage alerts, default model selection, AI model compaction, automation, human-in-the-loop AI, context length limits, token burn rate, Jovan’s paradox, AI tool escalation Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 872: AI Cost Control 101: Why Your Chatbot Bill Is Becoming a Board-Level Problem (Start Here Series Vol 31)

  6. Sep 28

    Ep 871: Desktop Agent Lingo Simplified: Goals, Loops, Plans, Subagents and how it works in Codex and Claude Code (Start Here Series Vol 30)

    Talking about prompts and chatbots won't help you talk about AI strategy in 2026.  You've gotta know the ins and outs of loops, plans, goals, subagents and more.  In this episode of Everyday AI, we're breaking down the agent lingo and how the key terms play out in systems like Codex and Claude Desktop.  Desktop Agent Lingo Simplified: Goals, Loops, Plans, Subagents and how it works in Codex and Claude Code -- 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: Desktop Agent Vocabulary PrimerAgent Harnesses: Codex vs. Claude CodeDesktop Agent Plans: Features and WorkflowGoal Setting in Codex and Claude DesktopPlan vs. Goal: Key DifferencesAgent Loops: Automation and VerificationSub Agents: Parallel Task ManagementContext Windows and Task DelegationGuardrails, Verification, and Cost ControlTransition from Chatbots to Autonomous Agents Timestamps: 00:00 Shifting focus to AI agents 03:28 Accessing the Start Here series 09:31 Using plan mode in clawed desktop 12:04 Understanding plan vs. goal mode 14:25 Setting project goals and planning 19:33 Accessing Start Here series 22:03 Building effective training loops 26:48 Managing sub agents effectively 27:30 Setting up sub-agent system 30:47 Closing and subscription reminder Keywords:  desktop agent, desktop AI agent, agent lingo, agent vocabulary, long running agent, autonomous agent, codex, Claude Code, Claude desktop, AI harness, agentic harness, agentic tools, super app, Microsoft super app, OpenAI codex, long running desktop agents, plan mode, planning phase, agent plan, goal setting, AI goal, agent goals, loop mode, agent loops, scheduled automations, sub agents, agent subagents, context windows, parallel work, context hygiene, verification steps, approval points, skills, automations, API token usage, project threads, co work tab, code tab, work trees, checkpoints, file access, browser automation, human in the loop, token efficiency, agent delegation, AI supervision, knowledge work automation, AI subagent management, desktop agent mental model, computer control, AI project management, AI workload delegation, remote steering, front end chatbot, proactive AI, AI context sharing. Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

    Ep 871: Desktop Agent Lingo Simplified: Goals, Loops, Plans, Subagents and how it works in Codex and Claude Code (Start Here Series Vol 30)

  7. Sep 25

    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)

  8. Sep 24

    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)
See All (876)

Hosts & Guests

4.7
out of 5
149 Ratings

About

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. 

Information

You Might Also Like