Everyday AI Podcast – An AI and ChatGPT Podcast

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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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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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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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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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
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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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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:
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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