mindsetai - kn

Cluely’s story

Is the use of AI cheating? Or common sense?

Authenticity

Human development

Societal impact

The debate about technological progress

History, innovation, impact

Closing thoughts

Multi-agent systems, MCP, A2A tied together

How does A2A work?

What’s the difference between MCP and A2A?

The key principles of the A2A protocol

Orchestrator agent

JSON

Agent cards

What does A2A mean for you—and what could go wrong?

1. It can go dark—fast

2. Google's A2A protocol is trying to do too much

3. It doesn’t scale—yet

Closing thoughts

Why the shift toward AI coaching?

Demystifying AI agents vs. AI coaches

Real AI coach use cases that work

Mintra

Training Industry

5app

How to launch an AI coach (without rebuilding everything)

Go-live in 30 days

What’s next in AI coaching?

1. Accuracy + Exploration

2. Learning + Coaching

So should you launch an AI coach?

Watch the webinar and book a demo

The infamous Shopify memo about AI

Takeaways from the Shopify memo

The excited camp

The critics

The skeptics

Job market and economic impact

Junior roles will be changing

AI use will become part of performance reviews

My take

Economists’ take

Predictions for the next five years in AI

Closing thoughts

OpenAI’s new ChatGPT image generator

What makes the new ChatGPT image generator so special?

Moving away from “denoising”

Conversational design

Image referencing

Accurate text rendering

ChatGPT image generator copyright, cultural, and ethical implications

The business implications of ChatGPT’s image generator

Closing thoughts

The proposition: The strategic value of AI agents in EdTech

Benefits for your platform’s users

Benefits for you

Can AI agents make money for your brand? Key pricing strategies

The foundation: Subscription-based

The flexible option: Pay-per-interaction

The bold move: Performance-based pricing

The revenue multiplier: Value-added services

Building the business case

Investment: Buy or build?

Return on investment

What else to consider

Apple Intelligence: false advertising, embarrassment, and a deepening crisis

Why people should be worried about Apple?

1. Hardware vs. software

2. Vertical integrations

3. Lack of urgency in innovation

What could Apple do to stay in the AI game

1. Acquire a large language model provider.

2. Build an AI agent-first operating system

3. Win big in voice and wearables

4. Invest in robotics (eventually)

Closing thoughts

Dario Amodei’s take on the future of developers

What is vibe coding?

The ever-changing role of a programmer—Tim O’Reilly’s take

Closing thoughts

Why vertical AI agents threaten traditional SaaS

Why Google’s business model is at risk from AI-driven search tools

A hybrid model for SaaS companies

Conclusion

AGI, Industrial Revolution, and the shifting landscape of knowledge work

The 10x human: Why AI won’t replace humans

Barriers to AI revolution: workflows, law-making, social trust

Workflows and assets

Lawmaking, liability, and social trust

Conclusion—and criticism