Everyday AI Podcast – An AI and ChatGPT Podcast

Until a few months ago, open source AI was kinda a hobby project. 

Now, it's tearing corporate boardrooms apart. 

Why? 

Over the past 6ish months, the gap between frontier closed AI and open sourced AI has shrunk to pretty much nothing. And with the surge of always on agents driving open models, their development and release schedule is on pace with the frontier labs. 

So if your team isn't paying attention to -- and running test cases through -- open AI models, there's a good chance you'll either be overpaying or playing catch up soon. 

We walk you through the 101 and what you need to know when it comes to open source AI in this Start Here Series special. 

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:
Open Source AI vs Closed Models Shift
Chinese Model Distillation & Legal Impacts
Enterprise AI Cost Triage Strategies
Google Gemma 4 Local Model Capabilities
Frontier Model Performance Gap Closing
24/7 Agentic AI Systems Overview
API Pricing War: DeepSeek vs US Vendors
Legal Protection Tradeoffs for Open Source AI
AI Workflow Triage: Task-Specific Models
Future Trends: Local and Specialized LLMs

Timestamps:

00:00 Introducing the Firefly AI assistant
03:33 Open source AI cost benefits
09:25 AI model performance differences
10:19 Open source model improvements
15:28 Advancements in local AI capabilities
17:04 Impact of Google's Gemma four
22:15 Introducing Adobe's Firefly AI Assistant
24:19 Adobe Firefly AI assistant beta launch
29:26 Choosing the right AI tools
32:00 Shifting workloads to open source
33:31 Using open-source and closed models
36:47 The future of open models

Keywords: 
open source AI, open source models, local AI models, local models, closed source AI, closed models, proprietary AI, proprietary models, AI agents, agentic AI, AI workflow triage, cheap API, AI API costs, model distillation, Chinese open source models, China AI models, US AI models,
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Salesforce's cofounder essential questioned: why should you login to Salesforce anymore? 🤔

He wasn't signaling the AI-driven SaaSpocalypse was picking up steam. 

Instead: he's talking about going headless. 

What's that? It's a future where Salesforce -- any potentially many other household software giants -- stop making software interfaces for humans and start designing for AI agents instead. 

So will this be a short-lived trend? Or, will the future of work not really involve a ton of humans clicking around? 

Join us as we dissect the latest. 

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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.

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Website: YourEverydayAI.com
Email The Show: info@youreverydayai.com
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Topics Covered in This Episode:
Headless Software Definition and Evolution
AI Agents Versus Traditional Software Interfaces
Salesforce Headless 360 and MCP Protocols
OpenAI Workspace Agents Features and Impact
Google Vertex AI Rebranding to Gemini Agents
Model Context Protocol (MCP) and A2A Integration
Per Seat Software Pricing Disruption
Enterprise Procurement for Agent-Ready Software
Agentic Commerce and Automated Bot Traffic Trends
Strategies for Auditing and Migrating Vendors

Timestamps:

00:00 Shift to AI-first software development
05:39 Benefits of headless software
07:29 Headless software development insights
11:28 Salesforce launches headless 360 platform
14:15 The rise of headless software
19:10 AI model connectivity in 2026
23:24 AI's impact on software pricing
26:22 Discussing token maxing in business
28:25 AI agents impacting human commerce
32:16 Evaluating software and vendor choices
35:46 Competitive advantage in software pricing

Keywords: 
headless software, interface-less software, headless software trend, software for AI agents, agent-first platforms,
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Info hunting and juggling sound familiar? 

It’s the downfall of almost any business leader. Where is that email from Emily? Why can’t I find last quarter’s budget in Drive? Oh, and Keenen needs an answer back on that research project. Oh shoot, I swear Caleb confirmed the expenses in one of these Slack channels. 

You’re off an information rabbit hole and by the time you find that Slack message, you already forgot what Emily’s email said. 

Hit home? Well, as AI models expand to Coworking and Scheduled agents, we have a new best friend that doesn’t really have a name. 

(Until we randomly named it. Lolz) 

Scheduled Agentic Context Carry. You need to know what it is, why it’s important, and how to use it. 

We’ll dive in. 

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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:
Scheduled Agentic Context Carry (SACC) Explained
AI Agents: Features vs. Benefits Paradigm
Co-Working and Scheduled AI Workflow Shift
Persistent Context and Memory in AI Agents
Large Language Models’ 1,000,000 Token Context Windows
Workflow Automation: Eliminating Human-AI Duct Tape
Multi-App Integration and Cross-Platform Context
Three Steps to Deploy Scheduled Agentic Context Carry
Chain of Thought Iteration with Scheduled Agents
Autonomous Agent Limitations and Future Bridge

Timestamps:

00:00 Explaining SACC and AI benefits
03:43 Introducing the Start Here series
06:26 Rise of AI in enterprises
11:55 AI agents learning industry trends
15:08 Agent capabilities in AI systems
16:47 Explaining complex trends simply
20:13 Streamlining tasks with AI agents
24:18 Understanding AI and context windows
27:43 Understanding prompt engineering basics
30:51 Debugging and reviewing schedules
33:08 Building automated workflows this quarter
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You think proper AI implementation is a technical problem for your company to solve? 🤔

Wrong. 

It’s actually about people. 

Maybe it’s because of the fast-pace nature of AI, and the fact there’s literally dozens of new AI tech drops each week that promise to change how we work, but the defecto response to showing ROI on AI always defaults to the technical side. 
Yet, studies show building an AI-native organization is WAY more about change management than anything else. 

We break it down, and show you the 5 moves the Top 5% are making to get it right. 

AI Change Management That Works: 5 Moves The Top 5% Make — An Everyday AI Chat with Jordan Wilson

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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:
AI Change Management vs. Technical Problem
AI Adoption’s People and Process Gap
Top 5% Change Management Playbook Steps
Budget Split: Funding People Over Tools
Dangers of AI Upskilling and Reskilling
Rebuilding AI-Native SOPs from Scratch
Weekly AI Enablement Rituals for Teams
Grading AI Behavioral Change, Not Tool Use
Enterprise ROI Gap in AI Adoption
Case Studies: Moderna, BBVA, JPMorgan AI Transformation

Timestamps:

00:00 AI adoption and change management challenges
04:39 AI change management challenges
08:57 AI's impact on workplace dynamics
12:51 Prioritizing Team Discussions and Processes
15:11 Investing in AI vs. People
18:25 Building AI-native processes
20:59 Embracing AI in daily tasks
24:05 Weekly AI strategy meetings
28:13 AI performance in big tech reviews
31:11 Adapting to AI in the workplace
34:21 Joining the Start Here series

Keywords: 
AI change management, AI adoption, change management strategies, AI transformation, enterprise AI ROI, 
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Even if you're 'doing AI right' you're probably lying, hurting others and getting dumb. 🤯

Sounds brash, but it's largely the truth. 

Even proper AI use rewards speed, agility and scale. It doesn't emphasize thoughtful conversations, deep learning or thoughtful human conversation. 

We call these the 7 Silent Sins of AI, and chances are you're committing many of them. 

Don't worry. We'll break them down and teach you the basics on how to avoid them.

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:
The Hidden Costs of Heavy AI Use
Sin One: Sycophancy in AI Chatbots
How to Fix Sycophancy with Custom Instructions
Sin Two: AI Psychosis and Delusional Echo Chambers
Sin Three: WAIF and Weaponized Training Data
Three Questions to Ask Before Trusting AI Stats
Sin Four: Accidental Deskilling of the Brain
Sin Five: The Agent Bun Sandwich Hollowing Expertise
Sin Six: The Compression Tax on Cognitive Bandwidth
Sin Seven: Automation Bias and Blind AI Trust
Grieving the Loss of Domain Expertise
Daily Habits to Protect Your Thinking

Timestamps:

00:16 The personal cost of heavy AI use
02:35 The seven invisible AI traps overview
04:29 Sin one: sycophancy explained
07:22 Fix sycophancy with blunt custom instructions
08:53 Sin two: AI psychosis and echo chambers
11:48 How to spot AI psychosis in yourself and others
12:39 Sin three: WAIF and tainted training data
17:44 Three questions to vet any AI stat
18:12 Sin four: accidental deskilling
22:57 Sin five: the agent bun sandwich
29:26 Sin six: the compression tax
34:34 Sin seven: automation bias
38:29 Grieving the end of domain expertise

Keywords: 
sycophancy, AI psychosis, WAIF, weaponized authority, accidental deskilling, agent bun sandwich,
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