How To Understand & Optimize Agentic AI Workforces with Promise Theory with Tony Davis & Dr. Mark Burgess - Modern CTO Recap

Podcast: Modern CTO

Published: 2026-02-23

Duration: 41 min

Summary

This episode dives into Promise Theory, a concept where AI agents make their own promises rather than being forced to obey commands. It explores how this framework can enhance the functioning of autonomous AI agents within Agentic Workforces.

What Happened

In today's episode, Joel Beasley sits down with Dr. Mark Burgess, the creator of Promise Theory, and Tony Davis from ANI Solutions to unpack the fascinating concept of autonomous AI agents making their own promises. Instead of relying on rigid commands, these agents operate based on a system of mutual agreements, allowing them to adapt and respond to their environment more effectively. This approach aims to transform the future of work by creating a more flexible and dynamic workforce powered by AI.

Dr. Burgess shares his journey into developing Promise Theory, starting from his early work on CFEngine in the 1990s. He emphasizes that rather than forcing machines to follow orders, he envisioned a system where agents declare their intended actions, thereby fostering a more natural interaction with technology. This shift away from obligation-based management to a promise-based framework allows for better handling of individual autonomy, which is crucial in managing complex systems that frequently drift from their desired state.

The conversation also touches on the broader implications of this theory in various fields, such as networking and open-source projects. Dr. Burgess reflects on the evolution of his ideas and how they have been embraced in the tech community, highlighting the organic spread of concepts that sometimes gain traction without extensive promotion. The episode ultimately paints a picture of a future where AI agents work alongside humans in a more collaborative and understanding manner, driven by the promises they make to one another.

Key Insights

• Promise Theory allows AI agents to operate autonomously by making mutual agreements instead of following rigid commands.
• The concept originated from Dr. Burgess's experiences in managing complex systems and wanting to create self-healing computer systems.
• The shift from obligation-based management to promise-based frameworks enhances individual autonomy and adaptability in AI systems.
• Promise Theory has been successfully integrated into various applications, demonstrating the organic growth of innovative ideas in technology.

Key Questions Answered

What is Promise Theory?

Promise Theory is a framework developed by Dr. Mark Burgess, where AI agents autonomously make promises about their actions instead of following rigid commands. This approach allows agents to communicate their intentions, creating a more flexible and adaptive system of operation. The essence of the theory is to facilitate better interactions among autonomous agents, helping them decide whether to accept the promises made by others.

How did Dr. Mark Burgess develop Promise Theory?

Dr. Burgess's journey began with the creation of CFEngine in 1993, where he initially sought to understand computer behavior through a lens of physics. He realized that traditional logic-based approaches to managing computers were inadequate for addressing autonomy. After years of developing his ideas intuitively, he formalized Promise Theory to express the need for systems that could maintain their intended states through promises rather than obligations.

What role does autonomy play in AI according to the podcast?

Autonomy is central to the discussion of AI in this episode, particularly how it relates to the management of agentic workforces. Dr. Burgess argues that traditional logic imposes too many restrictions on autonomous agents, whereas Promise Theory allows for a more organic interaction based on intentions. This autonomy enables agents to adapt and make decisions independently, leading to more resilient and self-sustaining systems.

What are the practical applications of Promise Theory?

Promise Theory has found its way into various applications, particularly in networking and system management. Dr. Burgess mentions that it has been integrated into Cisco’s networking solutions, showcasing its relevance in real-world scenarios. The adaptability and self-healing capabilities of systems based on this theory suggest significant potential for improving operational efficiencies in complex environments.

How does Promise Theory compare to traditional obligation-based management?

Traditional obligation-based management relies heavily on strict commands and logic, which can limit the autonomy of systems. In contrast, Promise Theory emphasizes intentions and the idea of best-effort commitments. This perspective acknowledges that agents may not always be able to fulfill promises due to various factors, thus allowing for a more nuanced and realistic approach to managing AI and technology.