So What About AI Agents

SummaryIn this episode of So What About AI Agents Philippe Trounev and Dr. Craig Kaplan discusses the need for a new approach to AI safety and governance, emphasizing the importance of prevention in design and the concept of AI agents and collective intelligence systems. He highlights the role of ethics and morals in agentic society, the enforcement of ethics and morals in AI agents, and the purpose and values of AI agents. Dr. Kaplan also explores the blueprint for collective intelligence systems, problem-solving and coordination in multi-agent systems, transparency and accountability, decentralization of power, observation and reporting, and the role of values in AI systems. He concludes by discussing the relevance of Herbert Simon's ideas in AI research.takeawaysDemocracy in AI governance can enhance safety.AI agents can work together like a community.Ethics in AI must be enforced through safeguards.Collective intelligence can outperform individual expertise.Designing AI systems requires careful consideration.Transparency is crucial for AI agent interactions.Values from diverse individuals should shape AI behavior.The historical context of AI informs current practices.Short-term fixes are not sufficient for AI safety.Our online behavior influences future AI training.titlesBuilding Safe AI: A Democratic ApproachThe Future of AI GovernanceSound Bites"Two heads are better than one.""We need to think hard about design.""We should behave well online."Chapters00:00Introduction to AI and Superintelligence01:20Governance and Safety in AI05:30The Role of AI Agents in Society07:29Evolving Towards Agentic Democracy09:35Ethics and Morals in Agentic Society12:16Influence vs. Enforcement in AI Behavior15:52Blueprint for Collective Intelligence Systems19:39Human Traits in AI Collective Intelligence22:49Transparency and Accountability Among Agents25:25Decentralization and Power Distribution29:35Learning from Human Governance33:20Herbert Simon's Insights on AI and Morality36:42Key Takeaways for AI Governance

summaryIn this conversation, Philippe Trounev and Mitchell Jones delve into the complexities of agentic payments and the necessary payment infrastructure for the evolving AI economy. They discuss the challenges faced by AI startups in managing payments, the importance of measurement and optimization in payment systems, and the future of agent-to-agent payments. The conversation highlights the need for budgeting controls and trust in agent networks, emphasizing the role of gateways in facilitating these processes.takeaways
Agentic payments require a clear understanding of costs and value delivery.
Current payment infrastructures are inadequate for the needs of AI startups.
AI startups must adapt their pricing strategies beyond traditional models.
Using a payment gateway simplifies the integration of multiple AI models.
Measurement is crucial for managing costs in AI operations.
Budgeting controls are essential for preventing runaway costs in agentic systems.
Trust and accountability are vital in agent-to-agent transactions.
The future of payments will involve more automation and less human intervention.
Experimentation with pricing models is now more feasible for startups.
Building a robust payment infrastructure is critical for the success of AI applications.

Keywords

agentic payments, payment infrastructure, AI startups, payment systems, budgeting, trust, agent-to-agent payments, LavaPayments, FinTech, AI economy

Chapters

00:00 Understanding Agentic Payments
02:28 The Role of Payment Infrastructure in AI
05:21 Optimizing Payment Systems for AI Startups
08:07 The Future of Agent-to-Agent Payments
11:03 Budgeting and Control in the Agentic Economy
13:50 Building Trust in Agent Transactions
16:45 The Evolution of AI Agents and Payments
19:25 Challenges in Agent Communication and Budgeting
22:29 The Importance of Measurement in Payment Systems
25:18 Future Use Cases for Agent Payments
28:08 Final Thoughts on the Agentic Economy

In this conversation, Philippe Trounev and Paul Schmidt discuss the concept of agentic sales organizations, focusing on how AI can empower sales teams by alleviating mundane tasks and enhancing efficiency. They explore the role of sales research agents, essential tools for implementing AI in sales, and the importance of data hygiene. The discussion also covers the cost considerations for introducing AI and predictions for the future of sales technology.takeawaysAgentic sales organizations empower sales teams with AI tools.Sales research agents can save significant time for sales reps.Proposal agents help create polished presentations quickly.Personalization in outreach is key to engaging prospects.Data hygiene is essential for effective AI implementation.Sales teams should document processes for better AI output.Integrating AI should feel seamless for salespeople.Cost-effective solutions exist for implementing AI in sales.AI can help sales teams focus on high-value tasks.Domain expertise is crucial when selecting AI tools.https://www.docsie.ioJoin us on Discord https://discord.gg/pAUGNTzv

EP 48 – Agentic DevOps | Featuring Scott Rowlandson (NetOrca)
In this episode, Philippe Trounev sits down with Scott Rowlandson from NetOrca to unpack one of the most urgent questions in technology today:
We dive deep into the evolution of DevOps, the rise of AI agent orchestration, and how automation is reshaping engineering teams across regulated industries like financial services.
Scott brings real-world experience from working in high-compliance environments—where automation isn’t just helpful… it's essential. Together, we explore:
How automation is changing the DevOps landscape

Why DevOps roles aren’t disappearing—but evolving

AI agents and the future of engineering workflows

Reducing delivery times in complex tech stacks

Why regulated industries rely heavily on automation

“Human-in-the-loop” DevOps models

What skills DevOps engineers MUST develop to stay relevant

Automation will eliminate some manual DevOps tasks.

But demand for skilled DevOps engineers is increasing, not shrinking.

AI agents will drastically accelerate deployment, compliance, and operations.

DevOps pros who embrace orchestration and automation will lead the next era.

The future of engineering is hybrid: AI + humans working together.

Is AI automation about to replace traditional DevOps roles?🔥 Key Topics Covered🎯 Main Takeaways

In this insightful conversation, Philippe Trounev and Padraic O'Reilly discuss the evolving landscape of compliance and automation in cybersecurity. They explore the challenges and opportunities presented by AI agents, the importance of quality assurance, and the role of human oversight in maintaining effective compliance systems. The discussion also touches on the future of agentic compliance and the balance between automation and human involvement.https://www.cybersaint.ioand https://www.docsie.ioJoin us on Discord https://discord.gg/ceKz5d4b