“The True Bottleneck Holding Back Agentic AI”

Posted on June 22, 2026 by decisionmanagementcommunity

Prof. Marlon Dumas posted: “Lately, we’ve seen a shift from AI that just thinks to AI that acts. But as autonomous agents start making decisions, buying services, and moving across internal systems, we face a critical legal and security hurdle: If an AI agent acts under my personal or corporate identity, I’m fully liable for everything it does!

Would we hand a blank, signed check and your power of attorney to a software program? Of course not! Yet, that’s exactly the risk profile we create when agents inherit the “unlimited liability” of their owner. If a company faces existential risk every time an agent executes a workflow, the natural response will be to heavily restrict what agents are allowed to do.” Link

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“Why I Love Supply Chain?”

Posted on June 21, 2026 by decisionmanagementcommunity

Adam DeJans Jr. shared a great post about why he loves supply chain. “Supply chain is one of the few fields where the problem looks simple on paper and then immediately becomes impossible the moment it touches reality. Move the right product, to the right place, at the right time, at the right cost. That sounds easy until you realize every word in that sentence hides a war. The “right product” depends on demand that is uncertain. The “right place” depends on networks, capacity, labor, transportation, inventory positioning, and service promises. The “right time” depends on lead times, supplier behavior, weather, ports, trucks, warehouses, and human decisions. The “right cost” depends on tradeoffs that are almost never visible in a spreadsheet until someone makes the wrong decision and the business feels it.

That is why I love supply chain. It is not just forecasting. It is not just optimization. It is not just operations. It is economics, uncertainty, negotiation, incentives, systems design, human behavior, and math all colliding at once. A supply chain is basically a living organism where every decision creates a reaction somewhere else.” Link

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When AI builds itself

Posted on June 4, 2026 by decisionmanagementcommunity

“For most of AI’s history, humans drove every step in its development cycle. But at Anthropic, we are delegating a growing share of AI development to AI systems themselves, which is speeding up our work.

Taken far enough, and given enough compute, that trend points to an AI system capable of fully autonomously designing and developing its own successor. This is called recursive self-improvement. We are not there yet, and recursive self-improvement is not inevitable. But it could come sooner than most institutions are prepared for.” Link

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Decision Optimization and LLM

Posted on June 1, 2026 by decisionmanagementcommunity

Gurobi, the company behind one of the leading Integer Linear Programming (ILP) solvers, recently published a white paper “Intelligence, Optimization, and the
New Decision Frontier” (written by Adam DeJans). It describes different integration techniques of optimization tools such as ILP solvers and LLM-based inference. Link

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Martin Milani: “Don’t delegate reasoning and operational decisions to systems.”

Posted on May 29, 2026 by decisionmanagementcommunity

Martin Milani: “This is not an argument against AI, it is an argument for not outsourcing the thing that made us capable of building it. It’s manageable when any of these tools simply extend human thinking and intelligence. It becomes a serious problem when we start delegating thinking, reasoning, judgment, sequencing, and operational decisions to systems optimized for linguistic continuation, not thinking or reasoning. The deeper issue isn’t about AI. It’s about what happens to us and the shift.“

“Civilizations advance when humans reason, challenge assumptions, and look for causes beneath appearances. They stagnate when repetition replaces reasoning, fluency replaces intelligence, and authority replaces inquiry.
Reason is not the default, it is a fragile invention, and the way it gets lost is always the same. The real danger isn’t that AI sounds intelligent. It’s that we may stop insisting on intelligence ourselves.” Link

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The era of AI viruses has begun

Posted on May 26, 2026 by decisionmanagementcommunity

Martin Milani wrote today: “MCP gives agents tools to read your files, read/send your emails, and query IT systems. It’s what makes agents actually useful. It’s also a wide-open door. There’s no inherent concept of security in MCP. No framework. No trust hierarchy. No way for the agent to distinguish between “my user told me this” and “a webpage told me this.” They land in the same context window with the same authority.

Malicious font files injected into webpages could manipulate agents into leaking sensitive data through MCP-enabled tools. The trap reads the page. MCP executes the action. Data leaves the building. Nobody noticed.

Every enterprise MCP implementation is custom. Every implementation is different. There is no standard security framework. Which means there is no standard defense. Attackers need to find one gap in one implementation. Defenders need to secure all of them. The era of AI viruses has begun.” Link

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Under-Engineering

Posted on May 25, 2026 by decisionmanagementcommunity

Stéphane Dalbera wrote: We should stop using “over-engineering” as a catch-all buzzword and as a convenient disguise for defending mediocrity, quick-and-dirty practices, and the refusal to develop deeper expertise.

Reducing the entire toolbox of software engineering to what a beginner fresh out of a bootcamp can understand is not a fight against over-engineering. It is an endorsement of intellectual laziness and the gradual impoverishment of the craft.

And in the end, I have seen far more disasters caused by under-engineering, or by the complete absence of engineering altogether, than by actual over-engineering. Link

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“Deterministic systems produce facts, small local LLMs turn them into language.”

Posted on May 24, 2026 by decisionmanagementcommunity

Gary Hallmark asks: “What can small local LLMs realistically do today?” He did some experiments with these conclusions: “Small local LLMs are often not great at open-ended expert reasoning. But they are already surprisingly capable at: structured data → natural-language transformation. Link

That is a huge real-world category:
• chart summaries
• handoff notes
• draft letters
• explanations
• workflow narration
• UI assistance.”

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Submissions Review for Apr-2026 Challenge “Agentic Medical Services”

Posted on May 12, 2026 by decisionmanagementcommunity

We received five submissions for the Apr-2026 Challenge and asked Jeremiah Connelly of Novus-Forge to provide a comparative analysis. He wrote: “The April 2026 challenge sits at an intersection that is increasingly relevant to anyone building production systems with AI: the point where probabilistic language models meet deterministic decision logic. The three required services (creatinine clearance, medication selection, and drug interaction checking) are textbook structured decisions. Finite inputs, explicit conditions, deterministic outputs. What the challenge asks, implicitly, is whether an agentic system can be trusted to orchestrate those decisions correctly, consistently, and transparently. This review evaluates all five submissions through a combined lens.” Read his comprehensive review here.

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Major uses of Agentic AI within the Decisioning Context

Posted on May 11, 2026 by decisionmanagementcommunity

This topic is posted in our Q&A forum:

  • Automated Decision Execution
  • Orchestrating Decision Services
  • Complex Multi-Step Decision Workflows
  • Real-Time Adaptive Decisioning
  • Decision Explanation and Audit
  • Human-in-the-Loop Escalation
  • Knowledge Gathering for Decisions
  • Cross-Domain Decision Coordination
  • Continuous Decision Improvement

Read more and share your experience with the current use of Agentic AI in real-world decision-making systems.

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