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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

What is gibberlink?

What are multi-agent systems and how do they work?

The challenges of multi-agent systems

1. Scalability

2. Coordination

3. Security

4. Interoperability

5. Decision-making

Business-to-agent (B2A) solutions

Conclusion

The importance of protocols

What is MCP used for in AI?

What is MCP in AI agents?

What are the benefits of MCP?

The AI acceleration trend: what can MCP do?

Closing thoughts

The new UX challenges of agentic AI

The mother of all demos

Today’s UX challenges

Frameworks for human-AI interface design

Conclusion

What are AI agents?

Understanding agentic systems: Practical examples

Core components of AI agents

Deep Research agent

Research agent in action

GUI Agents

The future of AI agents

The future of work