The Society of Decision Professionals (SDP)

The Society of Decision Professionals (SDP) is dedicated to the practice of decision analysis and decision quality. SDP is currently the only certifying body for decision professionals. Here is what Warren Powell wrote about it: “This was such a contrast from my decades of attending the Informs meetings, which consist almost exclusively of academics (professors and Ph.D. students) presenting mathematical models and algorithms, all dreaming of real-world applications.
 
SDP consists entirely of business professionals who are directly involved in the process of making decisions within their companies. I spent a career making trips to observe real-world problems in the field. I was immediately struck that I was sitting in a room full of people who actually make decisions rather than just talk about it.
Link

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AI Agents are Going Beyond Chatbots

Bart Peetermans posted: “We are rapidly moving past the ‘Chatbot’ phase and into the ‘Autonomous Agent’ phase… LLMs are not Calculators! LLM-based agents are NOT a replacement for optimization. Linear and non-linear scenario analysis go beyond the abilities of an LLM and are much better catered for by true sourcing optimization tools. Use the LLM for the qualitative heavy lifting; let the optimization engines handle the math.” Link

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Enterprise AI is moving toward Decision Systems

Adam DeJans Jr describes how to think about decision systems through the lens of sequential decision problems. “Most operational environments are not one-time optimization problems. They are ongoing processes where decisions must be made repeatedly as the state of the world evolves.

Consider a transportation network. At any given moment, there is a current state of the system: trucks are located in different regions, orders are arriving, drivers have hours-of-service constraints, weather conditions are changing, and new information is constantly entering the system. Any decision we make (dispatching a truck, accepting a load, repositioning inventory) changes that state and affects the options available in the future. From a technical perspective, these systems usually revolve around a few core components.Link

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Bigger Models or Smarter Teams?


Philippe Kahn posted today at LinkedIn: The focus on creating larger AI models has been prevalent, but what if the key to achieving AGI lies in collaboration among AI systems? It’s clear that relying on a single “God Model” may not be the solution. The future of AI is not about a singular, massive brain, but rather an ecosystem of agents that engage in debate, verification, and correction. Link

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New Tools and Skills Shift

Read the LinkedIn article written by Jacob Feldman

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Meaning-Driven Architecture

Jack Jansonius published an article, “When Data Doesn’t Know What It Means.”

Many enterprise data systems suffer from a hidden problem: the data no longer “knows” what it means. Over decades, business meaning has been fragmented across processes, rules and technical structures, making systems increasingly opaque and difficult to control.

Meaning-driven architecture offers an alternative. By explicitly modelling goals, decisions and domain concepts, systems become transparent, testable and easier to govern. Instead of hiding logic in process flows or rule sets, decision tables make reasoning explicit—providing a stable semantic foundation for both traditional IT and AI. Link

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Rules as Code 2026 Conference started in The Hague

https://rules-as-code.yellenge.nl/

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From Process-Centric to Decision-Centric Architecture

Stefaan Lambrecht from TRIPOD shared a typical story for insurance operations. Embedding critical business logic within a script inside a process cost the insurer €50 million. This wasn’t caused by careless people or bad intentions. It happened because the decision was invisibly embedded in a process where no one thought to look. That situation is far more common than most insurers realize. The natural conclusion is in the title. Link

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From Buzzwords to Decisions

John Brandon Elam published an article, “Define Your Term or Stop Using Them” with the subtitle “Why the smartest-sounding people in the room are often contributing the least.”

The fundamental unit of business value isn’t data. It isn’t AI. It isn’t any specific technology. It’s the decision. Everything else is infrastructure in service of making better decisions more consistently. But here’s the thing: if you can’t define the terms you’re using, you can’t define the decisions you’re trying to improve. And if you can’t define the decisions, you’re not optimizing anything. You’re just adding complexity and calling it progress. Link

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Decision Modeling by Adam DeJans Jr.

Adam DeJans Jr. describes the technical approach he uses, regardless of whether the tool is for optimization, ML, simulation, or even a rules engine: Link

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