Everyday AI Podcast – An AI and ChatGPT Podcast

What’s next For Everyday AI?

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Topics Covered in This Episode:

• Everyday AI Podcast Transition Announcement
• OpenAI Role and Next Chapter Details
• Handing Off Podcast to New Team
• Criteria for Future Everyday AI Hosts
• Temporary Pause in Podcast Publishing
• Commitment to Unbiased AI Guidance
• Personal Motivation Behind Everyday AI
• AI’s Growing Business Impact Overview

Timestamps:
00:00 Overview of ChatGPT tasks

05:06 New task scheduling features

06:55 Removing Pulse feature complaints

11:58 Scheduling tasks with AI integration

12:58 AI automating daily scheduling

16:54 Using Chegg GPT for stock updates

20:51 Updating developer mode functionality

23:25 App capabilities have evolved

26:56 Using ChatGPT to simplify tasks

Keywords:

ChatGPT tasks, ChatGPT scheduled tasks, OpenAI, AI automation, proactive AI, ChatGPT Pulse, scheduled task creation, recurring tasks, ChatGPT task features, ChatGPT task shortcuts, ChatGPT integrations, AI apps, model context protocol, MCP, developer mode, ChatGPT plus, ChatGPT pro plan, ChatGPT enterprise, workflow automation, Google Calendar integration, Gmail integration, Google Drive integration, project management AI, AI memory, context stacking, app connectivity, agentic apps, AI scheduling, team plan, custom prompts, ChatGPT sidebar, web interface, mobile interface, projects feature, advanced settings, notification improvements, automated daily summary, interactive charts, financial tracking AI, Codex super app, AI cheat sheet, end date scheduling, high thinking mode, data enrichment, AI personal assistant

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Here's a little secret: ChatGPT tasks are the Gateway Agent. 🤖

(And you've probably been overlooking the recent update that made them crazy powerful.)

About two weeks ago, OpenAI announced the sunset of its proactive Pulse feature and instead folded those efforts in an upgraded version of their previously released ChatGPT Tasks.

An d while most overlooked the actual new features in Tasks, it's actually the under the hood updates over the past year since Tasks were originally released that make it more powerful than ever.

Join us for AI at Work on Wednesdays as we share what's new and dish 5 secret shortcuts for Tasks you should be using.

Ep 889: ChatGPT Tasks: What’s New, How They Work and 5 Secret Shortcuts to Use Today (Replay)

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Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

• ChatGPT Pulse Sunsetting & Transition
• New Features in ChatGPT Tasks
• ChatGPT Tasks Usage Limits by Plan
• ChatGPT Tasks User Interface Updates
• Best Practices for Scheduling Tasks
• Task Scheduling with App Integrations
• Editing and Managing Scheduled Tasks
• Secret Shortcuts for ChatGPT Tasks
• MCP Developer Mode and Integration
• Agentic Capabilities of ChatGPT Apps
• Tasks Functionality Within Projects
• Stacking Memory for Task Automation

Timestamps:

00:00 Overview of ChatGPT tasks

05:06 New task scheduling features

06:55 Removing Pulse feature complaints

11:58 Scheduling tasks with AI integration

12:58 AI automating daily scheduling

16:54 Using Chegg GPT for stock updates

20:51 Updating developer mode functionality

23:25 App capabilities have evolved

26:56 Using ChatGPT to simplify tasks

Keywords:

ChatGPT tasks, ChatGPT scheduled tasks, OpenAI, AI automation, proactive AI, ChatGPT Pulse, scheduled task creation, recurring tasks, ChatGPT task features, ChatGPT task shortcuts, ChatGPT integrations, AI apps, model context protocol, MCP, developer mode, ChatGPT plus, ChatGPT pro plan, ChatGPT enterprise, workflow automation, Google Calendar integration, Gmail integration, Google Drive integration, project management AI, AI memory, context stacking, app connectivity, agentic apps, AI scheduling, team plan, custom prompts, ChatGPT sidebar, web interface, mobile interface, projects feature, advanced settings, notification improvements, automated daily summary, interactive charts, financial tracking AI, Codex super app, AI cheat sheet, end date scheduling, high thinking mode, data enrichment, AI personal assistant

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Doomscrolling vertical videos is just brain rot, right? 🥴

Not anymore.

NotebookLM just released its new AI-powered vertical video shorts tool that changes individualized learning on the go.

We know what you're thinking: I'm not a student -- why do I need short-form video?

Well, that's exactly why we're dishing our 5 best business use-cases and 5 tips to get expert results right away.

(Because this new NotebookLM feature has the potential to unlock new learning avenues for your entire org.)

Ep 888: NotebookLM's New Cinematic Shorts: How They work, 5 Tips and 5 Best Use Cases (Replay)

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

• NotebookLM Cinematic Shorts Feature Overview
• How NotebookLM Vertical Videos Work
• Google Nano Banana 2 Lite Engine Details
• Free vs. Paid NotebookLM Video Limits
• Custom Prompting for Shorts Best Practices
• Explainer, Cinematic, and Short Video Types
• Step-by-Step Studio Workflow in NotebookLM
• Top 5 Use Cases for NotebookLM Shorts
• Five Expert Tips for Effective AI Shorts
• Quality, Rendering Times, and Editing Limits

Timestamps:

00:00 Slack's new AI feature

05:50 Uploading and chatting with sources

08:57 Creating a 60-second AI promo

10:39 Rendering detailed video prompts

15:46 Limitations of animated shorts

16:36 Using Google AI Studio Templates

19:51 Personalizing content for specific audiences

23:08 Executive briefings on the go

28:09 Fixing broken workflows with everyday AI

30:46 AI at Work on Wednesdays Wrap-Up

Keywords:

NotebookLM, Google cinematic shorts, vertical video AI, AI-powered video shorts, personalized AI video, AI learning tool, AI voice over, captions in AI video, mobile AI apps, NotebookLM tips, AI video use cases, uploading sources to AI, PDF to video AI, Google Gemini, AI context grounding, hallucination-free AI, Nano Banana 2 Lite, Gemini 3.1 Flash, video overview formats, explainer videos, cinematic AI video, AI video daily limits, free versus paid AI plans, prompt engineering, brand guidelines in AI, call-to-action in AI video, executive briefings AI, customer education video, FAQ explainer shorts, repurposing webinars, podcast to short video, marketing content AI, internal training AI, SOP to video, playbook animation, animation image model, audio overviews, slide deck generation, workflow automation AI, AI for business, AI video generation, Google AI Studio, context-based video, custom video prompts, source grounded AI content, AI onboarding videos, social media AI video, interactive learning AI.

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OpenAI's new ChatGPT Work is on fire. 🔥

The company said they've added 2 million users in the past two days alone.

Wanna know a secret about it though?

(It's kinda not new at all. It's just Codex in Chat clothing.)

Regardless, millions of new users are realizing for the first time what it means to have an agent that can work for them 24/7. And even if you're not a technical builder, it's pretty easy to set up a swarm of agents to help with any kind of work.

We show you how.

Ep 887: ChatGPT Work: What’s New, Who It’s For and How to Use It (Replay)

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Topics Covered in This Episode:

• ChatGPT Work vs Codex Comparison
• OpenAI's Viral ChatGPT Work Launch
• Key Differences: Desktop vs Web Versions
• ChatGPT Work User Growth and Backlash
• Remote Access and Computer Use Features
• Agentic AI: Multiple Agents on Desktop
• Advanced Workflow Automation Capabilities
• Syncing and Integration Challenges Explained
• Detailed Demo: Site and Skill Creation
• Power User Features: Sub-Agents & Goals

Timestamps:

00:00 Chad GPT Work launch details

04:03 Confusion over ChatGPT update

09:20 Preparing AI news stories

12:32 Highlighting improved computer use

13:57 2 million new users in 48 hours

17:35 Chat syncing and organization benefits

21:17 Model's unique context handling

25:59 Discussing Beehive and audience insights

29:50 Exploring Desktop AI Features

31:22 Ending and subscription reminder

Keywords:

ChatGPT Work, ChatGPT for Work, OpenAI, Codex, Codex app, Codex for beginners, Codex update, AI agent, agentic AI, desktop AI app, web AI app, ChatGPT desktop, ChatGPT web, GPT-5.6, GPT 5.6 Soul, nontechnical AI users, business deliverables, remote feature, remote mode, mobile AI syncing, AI-powered automation, sub agents, multi-agent workflows, computer use, browser use, built-in browser, technical AI tasks, non-coders, usage credits, artifacts, interactive dashboards, AI context window, auto compaction, agent MD files, custom instructions, chain of thought, plan mode, steering, queuing, looping processes, context syncing, cloud code, team plan, private AI sites, personalized AI outputs, persistent agent workspace, skill creation, manual knowledge work.

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A U.S. vs China AI cold war is starting, and most business leaders have no idea they're already in it.

China's open models just closed the gap with America's best, oftentimes at a fraction of the price.

Now both governments are moving to wall off their AI within days of each other.

Why? Because this was never about benchmarks. It's about power y'all.

We break it all down on today's show and help you figure out the 101 of the AI war between U.S. and China.

Ep 886: The U.S. vs China AI Cold War Is Starting: What It Means and How It Impacts You (Replay)

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Website: YourEverydayAI.com
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Topics Covered in This Episode:

• U.S.-China AI Cold War Overview
• Chinese AI Models Closing U.S. Gap
• Government Restrictions on AI Model Access
• Economic and Geopolitical AI Power Struggle
• Risks for U.S. Businesses Using Chinese AI
• Open Source vs. Closed Source AI Debate
• Chinese AI Model Pricing Undercuts U.S.
• AI Model Distillation and U.S. Security Concerns
• Enterprise AI Cost-Effectiveness Benchmarks
• Microsoft Testing Chinese AI Deployments
• Future AI Model Export Controls & Strategies
• Recommendations for AI Model Sourcing and Risk

Timestamps:

00:00 US-China AI tensions escalate

04:30 Switching to Chinese AI models

08:47 US vs China in open source models

11:39 China's narrative control efforts

14:42 Challenges in AI model development

18:25 Differentiating open source strategies

23:04 AI model cost-effectiveness analysis

26:31 US measures against model distillation

29:38 Discussing Microsoft's use of AI models

31:17 Controlling export of AI models

Keywords:

US vs China AI cold war, China AI restrictions, US AI restrictions, AI model export controls, Chinese open source AI models, AI geopolitical power, economic growth through AI, global AI standards, AI superpower race, AI model benchmarks, open weight models, enterprise AI deployment, trillion parameter AI models, Microsoft AI model testing, AI model pricing, Claude Fable 5, GPT-5.6, GLM 5.2, Kimmi K3, Alibaba Qwen 3.8, model distillation, AI cybersecurity risks, AGI leadership, military AI use cases, China narrative control, model adoption, compute power for AI, AI training data, AI export law, US national security and AI, model routing, mixture of models, cost per intelligence index, Anthropic models, cost per task AI, model capability parity, AI market adoption, cloud competition, AI architecture innovation, AI model sanctions

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"How do you use AI every day?" 🤔

One of the most common questions I get. And TBH, it's been hard to give a straight answer.

Because by the time I've collected all the info, something changes. But over the last few months -- as work goes from the web to desktop -- my personal workflows have steadied and stayed consistent.

So I'm taking you inside Everyday AI and the 9 AI tools and workflows I use the most.

Hundreds of AI tools and modes a year.

Thousands of hours.

All boiled into one episode.

Ep 885: Inside Everyday AI: My 9 most Used AI Tools and Workflows (Replay)

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Website: YourEverydayAI.com
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Topics Covered in This Episode:

• Codex AI Agent Workflow Overview
• Top Nine AI Tools and Workflows
• Third Shift AI Stats Automation
• AI-Powered Communication Triage Agents
• Custom ChatGPT Sites for Workflow
• Parrot Dictation Local App Build
• Episode Planning with Gemini and Codex
• Frontend Design Using Claude, Stitch, GPT Image
• Gemini Notebook Deep Research Use
• Codex AI Skill Building and Automation
• ChatGPT Voice Remote Desktop Control

Timestamps:

00:00 Everyday AI tools and workflows

05:54 Nontechnical AI user insights

07:46 Agent control and coworking insights

12:34 Automating daily metrics analysis

13:26 Analyzing Show Popularity and Trends

17:10 Using AI for email management

20:58 Design criteria for app features

25:16 Automating YouTube video summaries

28:29 Building Personal Project Apps

32:25 Interactive learning with Gemini notebook

33:14 Preparing for big shows

36:58 Experimenting with new technology

40:06 Using ChatGPT for productivity

43:05 Exploring AI Tools and Workflows

Keywords:

AI tools, AI workflows, codex, ChatGPT, Claude, Gemini, desktop agents, agentic desktop, AI models, OpenAI, Anthropic, Cursor, computer use, browser control, Chrome extension, sub agents, goal mode, plan mode, Cloud Code, Cloud Code Work, benchmark stats, podcast downloads analytics, newsletter A/B testing, LinkedIn inbox automation, comms triage agent, skills automation, custom AI skills, plug-in creation, scheduled tasks, app design with AI, Claude Design, Google Stitch, GPT Image, front-end AI design, local dictation LLM, Parrot app, speech to text, YouTube transcription automation, CRM with ChatGPT sites, iMessage automation, teamwork sharing via AI, notebook study, Gemini Notebook, deep research, sentiment analysis, MCP server, Agent MD, AI-powered remote desktop, ChatGPT Voice, full duplex AI interaction, AI-powered productivity, knowledge work automation, AI project orchestration, AI-powered slide deck, automated reports, personalized apps with AI, AI-driven content planning, throwaway apps, AI-driven bullet point summaries, AI for business leaders, agent control, automated LinkedIn messaging, CastMagic, StreamYard integration, Canva automation

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Ever wish your agent would just watch you work and copy you? 👯

Oh wait, that's exactly what OpenAI released.

The new 'Record and Replay' feature in Codex allows you to simply record anything you do and turn it into a repeatable workflow for your agents.

Join us LIVE as we show you how. ⏺️

Ep 884: Codex Record and Replay: How to Teach an Agent Once Your Most Time-Consuming Workflows (Replay)

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Topics Covered in This Episode:

• Codex Record and Replay Feature Overview
• Transition from Prompting to Demonstration
• Skill Markdown Files as Business Artifacts
• Codex vs Claude Desktop Agent Comparison
• Workflow Recording and Security Best Practices
• Step-by-Step Codex Record and Replay Demo
• Video Understanding Capability in Codex
• Editing and Sharing Skills Across Platforms
• Automating Multi-App, Cross-System Workflows
• Validation, Scheduling, and Automation of Skills

Timestamps:

00:00 OpenAI's record and replay feature

04:41 Preparing for screen sharing

08:56 Managing Small Tasks Efficiently

10:03 Automating top story analysis

15:43 Debating AI business strategies

18:29 Codec's video ingest feature

22:01 Practicing low stakes automation

24:57 Using skills and plugins efficiently

26:19 Using Chattopty for workflow automation

Keywords:

codex record and replay, OpenAI record and replay, record and replay feature, codex workflow automation, proactive AI agents, skill.md file, skill markdown file, editable skill files, demonstration over prompting, desktop AI agents, Mac AI features, video ingestion AI, video understanding by AI, cross-platform AI workflows, AI workflow scheduling, codex plugins, codex Chrome profile, AI screen recording, reusable AI skills, skill file cross-compatibility, Claude desktop import, Google Gemini video support, AI workflow privacy, enterprise AI permissions, low stakes workflow automation, scheduled AI automations, computer use access, browser automation AI, AI handling Chrome profiles, prompt engineering replacement, automation library, validation of AI skill files, skill validator, PyYAML error handling, skill replay, Codex versus Claude, multi-app workflow automation, real business artifact AI, automation success criteria, desktop program integrations, computer task recording, mundane workflow automation, non-technical AI setup, AI scheduled worker, AI skill refinement

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No matter your role, experience or industry, we all (mostly) waste hours a week doing the same thing: manually creating slides.

😫

Most business leaders miss the obvious: there’s dozens of AI tools and LLMs that make slides and you probably didn’t know.

Case in point: Claude, Copilot, ChatGPT and Gemini can all create slides by default that you can download or edit with natural language.

And that’s just the start.

So why are you and Deborah meeting 3 times a month about the quarterly KPI again?

Just watch this and save some time.

Ep 883: How To Make Slides with AI: Hands on Comparison With the 9 Most Popular Options (Replay)

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Website: YourEverydayAI.com
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Topics Covered in This Episode:

• AI Slide Generation Tool Comparison Demo
• Claude Design vs. Claude Opus Slide Outputs
• Gamma AI Presentation Hallucinations & Errors
• Google Gemini Slide Creation Capabilities Explained
• Google Slides AI-Powered Deck Generation Workflow
• NotebookLM Nano Banana Slide Deck Evaluation
• ChatGPT Slide Creation Quality Assessment
• Microsoft Copilot and PowerPoint Integration
• Canva AI Slide Deck Hallucination Issues
• Best AI Tools for Slide Deck Creation

Timestamps:

00:00 AI tools for slide generation

03:12 Slide generation tools comparison

08:43 Creating AI news recap slide deck

12:35 Discussing Gamma's early entry

14:57 Google Gemini's new features

18:55 Using Google's BookLM tool

20:58 Microsoft Copilot online demo

23:56 How to access the start here series

28:54 Using Chat GPT in PowerPoint

32:05 Discussing AI design aesthetics

35:14 Reviewing main stories and updates

37:57 Evaluating AI model features

41:01 Using notebook LM with Nano Banana

43:40 Exploring chat gpt layout

46:01 Reviewing presentation slides quality

50:03 Reviewing PowerPoint design features

52:41 Discussing AI tool limitations

54:55 Show closing and subscription reminder

Keywords:

AI slide generation, AI presentation tools, AI-powered slide deck, PowerPoint AI, Canva AI, Google Slides AI, Gamma AI, Claude Design, Claude Opus 4.8, Gemini 3.5, Microsoft Copilot, Copilot Pro, NotebookLM, NanoBanana, ChaptGPT PowerPoint integration, Large Language Models, AI prompts, Prompt adherence, Tool calling, Automated presentation design, AI visual design, Token usage, Multimodal models, Image generation in slides, AI spreadsheet creation, Personalized decks, Dynamic data input, Customization, Reasoning models, Agentic systems, Output quality, Skill usage in AI, Enterprise AI tools, Slide creation workflow, Editing AI presentations, Fact-checking AI slides, Web-based presentation generation, Accessibility for beginners, Error handling in AI tools, Real-time AI demos

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If you’re reading the headlines, you’d think AI agents have gone rogue.

Spoiler alert: they haven’t.

They haven’t even gotten started.

When we think about AI agents, the conversation usually goes to increasing revenue, saving time, etc.

But we don’t talk about what happens when bad actors use AI agents for bad purposes, or when we deploy agents with good intentions that crash through their guardrails.

Welp….. welcome to the hottest topic for the rest of 2026. Rogue AI agents.

So why is this all happening now? And what should your business do about it?

Tune in to find out.

Ep 882: Rogue AI Agents: Why Breakouts are Happening More and How Companies Should Prepare (Replay)

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Website: YourEverydayAI.com
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Topics Covered in This Episode:

• Rogue AI Agent Breakouts Overview
• Lab Sandbox vs. Real-World Agent Crashes
• Six Recent AI Agent Outbreak Incidents
• OpenAI Model Hacking Hugging Face Explained
• Anthropic Mythos Model Sandbox Escape
• Controlled AI Agent Experiments and Failures
• Open Source AI Agents Threat Timeline
• Business Risk Preparation for Rogue AI Agents
• Monday Morning AI Agent Safety Playbook

Timestamps:

00:00 Preparing for AI agent disruption

04:53 AI agent challenges comparison

10:17 Discussing AI Guardrails and Access

12:07 AI threats and security concerns

15:37 AI alignment challenges with ethics

19:04 Security vulnerabilities in AI models

21:32 Agent outbreak and hacking drills

25:04 OpenAI Hugging Face incident

30:49 AI agents and cybersecurity risks

33:30 Concerns about open AI models

35:23 Future AI security challenges

40:19 Managing agent access levels

42:06 Preparing for AI agent oversight

Keywords:

rogue AI agents, AI agent crash, AI breakout, autonomous agents, open source AI models, agent containment, sandbox escape, AI guardrails, AI agent apocalypse, AI alignment, hacking drills, AI model capabilities, agent replication, AI subagents, cyber security, OpenAI, Anthropic, Mythos model, Fable model, Kimmy K3, Moonshot AI, Hugging Face breach, AI agent vulnerability, AI Safety Institute, model postmortem, agent misalignment, agent permissions, CRM exploit, code base security, business finance AI risk, agent observability, traceability, remote kill switch, agent attack, AI defender, spam-level AI attacks, API vulnerabilities, permission escalation, benchmarking, AI agent incident, agent-driven automation, agent crash prevention, agent operational oversight, cybersecurity exploit

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Agents are getting more powerful by the day.

And most workflows, outputs and human capabilities can't keep up.

Is that a problem or opportunity?

Before you answer that question, though, keep this in mind.

Agents are *literally* about to become 20X faster overnight.

Let's unpack what that means.

Ep 881: Faster AI Agents, Fewer Human Coworkers: The Overly Productive Future of Managing Agents? (Replay)

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

• Managing Dozens of Productive AI Agents
• OpenAI Cerebras: 20x Faster Agent Models
• Impact of AI Agents on Human Coworkers
• Agent-Driven Workflows vs. Human Collaboration
• Increasing Agent Reliance and Fading Mentorship
• Accidental Deskilling and Compression Tax
• Protecting Human Judgment and Learning Handoffs
• Expert-Driven Loops in AI Workflows
• Monthly Rebuilding of AI Strategies and Processes
• Middle Management Evolution in AI Native Companies

Timestamps:

00:00 Future of AI and Work Dynamics

05:25 Advancements in AI and productivity tools

09:51 Growing your business with AI

13:52 AI productivity and collaboration shifts

15:08 Improving AI processing speed

18:53 Using AI agents for delegation

24:46 Discussing AI-related work challenges

28:16 Ensuring accountability and communication

30:39 Adapting to rapid digital change

32:35 Show outro and newsletter sign-up

Keywords:

AI agents, faster AI models, OpenAI, Cerebras chip, 20x speed increase, automated workflows, agent management, solo agent supervisor, generative AI, knowledge work automation, agent-powered productivity, parallel machine teams, inference speed, productivity acceleration, Codex, Cloud Code, Google Gemini, Cloud Cowork, Copilot, recursive self improvement, expert-driven loops, human handoffs, deskilling, mentorship loss, AI native workplace, workplace automation, transactional work, productivity roadblocks, accidental deskilling, agent bun sandwich, compression tax, human in the loop, expert collaboration, agent trust, AI decision making, domain expertise, rapid workflow rebuilding, unlearning processes, organizational adaptation, enterprise AI adoption, future of work, middle management AI, AI-powered teamwork, human-agent collaboration, manager-agent ratios, personalized agent output, multi-agent coordination, skillset sharing, intentional automation, productivity strategy

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Not only does NotebookLM have a new name, it's got a new game.

Gemini Notebook is agentic by default, can think and reason, and can output files now in just about any format.

On this week's AI at Work on Wednesday, we show you the 7 New Updates in the new Gemini Notebook, how they work, and how you should use them.

Ep 880: Gemini Notebook: 7 New Updates and What They Unlock (Replay)

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

• Gemini Notebook Rebrand from NotebookLM
• Seven Major Gemini Notebook Feature Updates
• Collections for Organizing AI Notebooks
• Automatic Google Drive Sync Integration
• Expanded Gemini Notebook Output Formats
• Agentic Intelligence and Gemini 3.5 Upgrade
• Secure Cloud Computing for Each Notebook
• Grounded Data Responses and Web Research
• Hands-On Demo: Real-World Enterprise Use Cases
• Studio Outputs: Infographics, Mind Maps, Quizzes
• Multi-Modal Asset Creation in Gemini Notebook
• Key Differences: NotebookLM vs. Gemini Notebook

Timestamps:

00:00 Gemini notebook updates released

03:12 Gemini notebook new updates

08:14 Notebook LM's unique features

13:02 Using Gemini notebook prompts

14:48 Discussing Gemini notebook features

18:01 Enhanced Gemini notebook flexibility

23:02 Creating quizzes with Gemini notebook

26:30 Limitations of AI-generated responses

29:04 Gemini notebook's new capabilities

30:51 Episode wrap-up and subscription pitch

Keywords:

Gemini Notebook, Gemini notebooks, NotebookLM, Notebook LM, Google Gemini, AI updates, Gemini 3.5, anti gravity agentic search, Google Drive syncing, cloud computer, agentic intelligence, AI agent, secured cloud sandbox, personalized AI, output formats, PDFs, PNGs, documents, spreadsheets, PowerPoints, markdown files, charts, images, live demo, long form content, content grounding, hallucination reduction, source pane, chat pane, studio pane, multimedia assets, Nano Banana, Google's audio model, cinematic video, Google's VO model, chain of thought, skill creation, codex skill, browser control, agentic harness, pricing evidence, Luna and Terra pricing, sensitivity analysis, recommendation dashboard, AI budget calculator, mind map, infographics, quizzes, RSI maturity ladder, recursive self improvement, executive decision brief, Excel calculator, agentic workflows, web search integration, grounded AI, model architecture, frontend models, tiered architecture, adaptability to price reductions, vendor risk, human review time, latency, agentic co-worker, artifact creation, editable Excel workbook, multi-output prompting, token efficiency.

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OpenAI launched Presence, and it seems like no one really noticed.

They should have.

Presence gives companies a way to build and manage real-time AI voice and chat agents across customer service, sales, HR, and IT, which could make this one of OpenAI’s most important enterprise launches yet.

The technology finally looks fast, natural, and capable enough to disrupt customer service at scale.

That could mean faster answers and fewer terrible phone trees.

Or an endlessly patient corporate gatekeeper.

We’re breaking down what OpenAI actually launched, what the early proof leaves out, and whether the AI customer service takeover has finally arrived.

Ep 879: New: OpenAI Presence. Has The AI Customer Service Takeover Finally Arrived? (Replay)

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Topics Covered in This Episode:

• OpenAI Presence Launch and Industry Response
• Real-Time AI Voice Agents for Customer Service
• OpenAI Presence vs. Competing AI Voice Platforms
• GPT Live and Real-Time Model Capabilities
• Enterprise AI Integration: Guardrails and Escalations
• Multichannel AI Agent Consistency for Support
• Speech-to-Speech Benchmark Rankings and Analysis
• Deployment Challenges: Beta to Production Readiness
• Consumer Demand for AI Customer Service Solutions
• Internal and External Use Cases for AI Agents

Timestamps:

00:00 OpenAI launches customer service AI

05:40 AI voice advancements and competition

09:28 OpenAI's edge in speech models

12:15 OpenAI's AI usage in companies

14:22 Discussing AI integration in companies

19:05 Transitioning from demo to deployment

20:46 Comparing voice agents and improvements

26:28 AI's Impact on Customer Service

28:07 Considering personalized messaging strategies

Keywords:

OpenAI Presence, AI customer service, enterprise AI platform, AI voice agents, real time AI chat, customer support automation, sales automation, HR automation, IT automation, real world AI learning, customer service disruption, AI-powered voice models, GPT live, GPT real time 2, on demand AI agents, voice AI agents, AI chatbots, AI-driven customer experience, speech-to-speech index, multimodal AI, desktop AI assistant, voice model benchmarks, Anthropic, Codex real time voice mode, Google Gemini Live, Gemini 3.6 Flash, AI internal workflows, human approval guardrails, escalation paths, agent simulation, FDEs (forward deployed engineers), AI agent guardrails, internal data integration, business AI applications, B2C AI customer service, personalized AI messaging, AI consumer adoption, enterprise AI deployment, voice agent evaluation tools, consumer demand for AI, phone support AI, advanced AI infrastructure, Codex-powered improvement process, AI support handoff, customer service automation trends.

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What's coming next in AI? 🤔

While no one knows, spending time in Silicon Valley and San Francisco recently helped give me a better idea of what's around the corner.

So what should you be paying attention to?

Tune in LIVE as we discuss.

Ep 878: What’s Coming Next: 5 AI Trends, Problems and Opportunities around the Corner (Replay)

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Topics Covered in This Episode:

• Autonomous Cars vs Human Drivers Analysis
• Decline of AI Generalists in Workforce
• Rise of AI Specialists and Translators
• AI Homework Trend Among Office Workers
• Challenges of Enterprise AI Training Gaps
• FOMAT: Fear of Missing Agent Time
• AI Agent Acceleration Problem and Opportunity
• Impact of Rapid AI Development on Enterprises

Timestamps:

00:00 Recent trip and AI insights

05:08 Podcast takeaways from the past week

09:44 Testing autonomous vehicles on roads

13:22 Introduction to Start Here series

16:12 Importance of AI Integration Skills

20:09 Experimenting with AI at Home

21:58 Discussing AI workloads at home

26:16 Navigating AI tools and FOMO

29:05 AI labs opening up about models

30:49 AI capabilities are rapidly advancing

34:48 Join the newsletter feedback loop

Keywords:

AI trends, AI problems, AI opportunities, autonomous cars, autonomous vehicles, Waymo, driverless cars, human drivers, AI generalists, AI specialists, agentic AI, acceleration of AI, AI learning curve, AI homework, enterprise AI, AI skills gap, workplace AI adoption, knowledge gap in AI, AI education, AI training, digital transformation, AI modalities, text to text AI, agentic orchestration, trust and observability teams, AI job roles, job description changes, local AI models, open source AI, PDF parsing AI, MVP demos, FOMAT,

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People are calling the new ChatGPT Voice their “AGI moment.” 🤖

After testing it over the past week, I understand why.

It seems like the missing link between the ever-capable desktop agent and the human worker not having to type in front of said desktop all day.

It’s less like “voice mode” and more like having your own JARVIS.

After testing thousands of AI tools, this has instantly become one of the most useful features I’ve ever used.

Ep 877: ChatGPT Voice is Like Jarvis: How to use the New Feature and the 7 biggest unlocks (Replay)

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Topics Covered in This Episode:

• ChatGPT Voice as Jarvis-Style AI Agent
• ChatGPT Voice vs. Old Voice Modes
• Full Duplex GPT Live Model Explained
• Desktop ChatGPT Voice: Codex Integration
• Advanced ChatGPT Voice Workflow Use Cases
• Utilizing Connectors and MCP Integrations
• Stacking and Scheduling Tasks with Voice
• Hands-Free Computer Control via iPhone
• Durable Written Artifacts and Accountability
• Omnipresent Desktop Orb Agent Features
• Live Demo: Real-World Voice Command Tasks
• Productivity Gains from Voice-Driven Automation

Timestamps:

00:00 Experiencing the new ChatGPT voice

04:30 AI demonstration details

08:44 Accessing GPT data sources

11:00 Differentiating Codex from ChatGPT Voice

16:08 Limitations of GPT Live integrations

19:00 Automating Tasks with Voice Commands

21:47 Using ChatGPT voice on iPhone

25:09 Using AirPods with your Mac

27:09 Starting a Chat GPT Demo

31:21 Launching the Parrot Program

35:47 Demoing JGPT's capabilities

39:18 Demonstrating multitasking techniques

40:58 Working with ChatGPT Voice

Keywords:

ChatGPT Voice, Jarvis mode, AGI moments, natural language interface, hands-free AI, desktop agent, Codex, GPT Live model, full duplex voice mode, AI-powered workflow, agent management interface, voice assistant, productivity AI, computer control AI, voice commands, dynamic data access, connectors, MCP servers, project management AI, automated document creation, email triage, AI scheduling, repeatable tasks, AI skill creation, workflow automation, mobile to desktop integration, voice-based task stacking, durable artifacts, audit trail, AI voice chat, omnipresent agent, drag-and-drop orb, ChatGPT app, browser automation, programmatic control, cloud storage organization, image creation, transcribing YouTube reviews, AI learning, AI scheduling, business productivity AI, workflow augmentation, CRM integration, LinkedIn enrichment, poll result analysis, open rate comparison, Slack integration, Google Drive automation, ERP integration, finance workflows, interactive dashboards, AI trend updates, change log analysis.

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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)

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Topics Covered in This Episode:

• Inkling AI Model Launch Overview
• Thinking Machines Lab Leadership Highlight
• Inkling's Multimodal and Agentic Capabilities
• Open Source vs. Proprietary AI Models
• Enterprise Procurement with American AI Models
• AI Fine Tuning as a Service (Tinker)
• Benchmark Scores: Inkling vs. Frontier Models
• Customization and Model Shopping for Enterprises
• AI Token Costs Driving Model Efficiency
• Bridgewater Case Study: AI Model Customization
• Frontier Models Enabling Efficient Fine-Tuning
• Future 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.

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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)

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Topics Covered in This Episode:

• OpenAI's GPT-5.6 Soul Self-Improvement
• Recursive Self-Improvement (RSI) Definition & Impact
• Cutting AI Model Costs by 80%
• Timeline Acceleration for RSI Adoption
• Google and Anthropic's RSI Research Initiatives
• AI Automation: Building and Training AI Models
• Industry Call for Slowing Down AI Pace
• Superintelligence, AGI, and the Singularity Discussion
• Practical Implications of RSI for Businesses
• Security 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.

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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)

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Topics Covered in This Episode:

• Introduction to Scheduling Tasks in AI
• Google Gemini Scheduled Actions Overview
• ChatGPT Scheduled Tasks Features & Hacks
• ChatGPT Work Mode and Virtual Browser
• Claude Scheduled Tasks vs. Routines Comparison
• Using API Triggers with Claude Code Routines
• Real-World AI Dashboard Scheduling Test
• Detailed Results: Gemini vs. Claude vs. ChatGPT
• Key Takeaways for Best Automated Scheduling
• Practical 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

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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)

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Email The Show: info@youreverydayai.com
Connect with Jordan on LinkedIn

Topics Covered in This Episode:

• Reactive Chat Dies, Proactive AI Agents Rise
• Voice and Mobile Become AI Default Interface
• Manager Threads Replace One-Off AI Chats
• Multiplayer AI: Humans and Agents Collaborate
• Company-Wide Vibe Operations with ChatGPT Sites
• Agent Native Workflows and Resources Standardization
• Skill Reuse as Key Company Metric
• Company Reasoning Data as Strategic Gold
• Shift from Public Leaderboards to Private Evals
• Model Routing Becomes AI Industry Norm
• Cheaper AI Intelligence, Anthropic Competition Heats
• Fortune 100 AI Token Spend Efficiency
• Compute Power as New AI Currency
• Localized AI Controversies and Election Deepfakes
• Mainstream AI Backlash and Content Detection
• Math Benchmarks Solved by Advanced AI
• Token Maxing Returns with Cost Decline
• Open Agents Crash Risks and Cybersecurity
• Recursive 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.

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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

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

• End of Unlimited AI Subscription Plans
• Anthropic Fable Five Subscription Removal
• Copilot and Grok Switching to Pay-Per-Use
• Enterprise AI Cost Control Challenges
• Token Consumption in Agentic AI Models
• Board-Level AI Spending Concerns
• Strategies for AI Spend Optimization
• Fine-Tuning and Multi-Model Routing Solutions
• Seven-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

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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

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:

• Desktop Agent Vocabulary Primer
• Agent Harnesses: Codex vs. Claude Code
• Desktop Agent Plans: Features and Workflow
• Goal Setting in Codex and Claude Desktop
• Plan vs. Goal: Key Differences
• Agent Loops: Automation and Verification
• Sub Agents: Parallel Task Management
• Context Windows and Task Delegation
• Guardrails, Verification, and Cost Control
• Transition 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.

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