Mike — Thinking Out Loud...
Welcome to Mikeland, a small corner of Prescher.com where experience meets unfiltered perspective. After years of advising leaders on complex strategic and operational challenges, Mike uses this space to unpack what’s really happening behind the buzzwords — what works, what doesn’t, and what actually moves the needle. Whether you’re a founder, owner, operator, or curious observer, here you’ll find practical insights, sharp opinions you can put to work in the real world, or not.
Does Ai Belong in Critical Infrastucture?
Had a chance to read the latest draft of NERC's AI/ML paper and it's about what I expected — a careful patient approach to introducing Ai/ML in to the North American grid systems. This is as it should be. The take-a-ways from this good work, in my own words (not theirs) are: Key Takeaways: — Establishes an AI/ML maturity model for electric utilities spanning experimentation, operational decision support, and bounded autonomy. — Reinforces that organizational accountability never transfers to AI. Utilities remain responsible for all outcomes. — Strongly prioritizes reliability, cybersecurity, data quality, governance, and workforce readiness above automation ambitions. — Promotes decision support and human-in-the-loop architectures as the near-term practical path for grid operations. — Identifies autonomous and agentic grid operations as possible future states, but only with extensive validation, regulatory acceptance, and cyber controls. For potential EPC Impact (Design, Build, Secure, Optimize): — Design: Increased demand for AI-ready OT architectures, data pipelines, observability, time synchronization, deterministic communications, and edge computing platforms. — Build: More projects will require integration of AI capabilities into EMS, ADMS, DERMS, cybersecurity, asset-management, and operational analytics environments — Secure: AI systems become new critical assets requiring segmentation, monitoring, validation, supply-chain scrutiny, and protection against model manipulation and data corruption. — Optimize: Creates opportunities for predictive maintenance, anomaly detection, operational decision support, outage response, and workforce productivity improvements. — Consulting/Governance: Likely drives demand for AI maturity assessments, cybersecurity assessments, OT . architecture reviews, AI governance frameworks, and compliance advisory services
The only way modern critical infrastructure can be sustained is if their teams (the Human Factor) keep pace with the rapidly changing technology which drives it. This is even more true if you've read another opinion on this page regarding NERC CIP's vision on Ai/ML's rapidly evolving impact. Humans are essential to the resilience and reliability equation. A “Front Seat, Side‑by‑Side, then Back Seat” approach lets an OT network consultant guide a customer through new communications technology in a way that builds both confidence and capability. In the front seat, the consultant leads design, deployment, testing, and turn‑up, so the solution is architected correctly and aligned with safety, reliability, and compliance needs from day one. Moving side‑by‑side, they co‑execute changes with the customer’s team, explaining decisions, documenting processes, and transferring practical skills while real work gets done. In the final steps, in the back seat, the consultant steps into a support and review role, allowing the customer to operate and evolve the network independently, but with expert backup when needed. This progression reduces risk, accelerates adoption, and leaves the customer with a resilient OT communications environment they truly understand and can sustain.
Knowledge Sharing — Learning to Drive
Why Boltzmann's Formula for Gas Entropy in a Vacuum Matters in OT Networks
I never really knew, (or understood) Boltzmann’s gas entropy in a vacuum formula, until I had been in the large-scale data communication network business for about a decade. Then a light bulb above my headed started to flicker on when I truly appreciate that complex systems...they break. It's not a question of if, just when. That's not good for critical infrastructure. The idea of Entropy offers a powerful mental model for why some complex OT critical infrastructure networks may be destined to fail. In Boltzmann’s view, a gas in a vacuum naturally spreads out into all available space, moving from an ordered state to a highly disordered one because there are simply more ways for the system to be disordered than ordered. The same thing happens in large OT data communications networks - as we add more devices, protocols, data paths, routes, and privatizations and filtering, combine with normal OA&M moves, adds, changes...the “state space” of the network explodes. There are far more ways for configurations, interactions, and failures to combine into chaos than there are for everything to line up in a clean, predictable way. Over time, without strong constraints, operation standards and QA, the network drifts toward higher “entropy”: more complexity, more hidden dependencies, and more fragile behavior. For critical infrastructure, that unstoppable drift toward disorder is not just inconvenient — it’s dangerous. High‑entropy OT networks are harder to understand, harder to secure, and harder to recover when something breaks. That’s why we have to actively fight this natural tendency by simplifying and hardening our designs and doing better knowledge sharing with operations staff. That means reducing unnecessary variation, standardizing architectures, limiting the number of allowed paths and behaviors, and designing with clear boundaries and deterministic behavior wherever possible. And when something does break, fix it, correctly...don't patch it. By intentionally lowering the entropy factors of our OT communications—through simpler topology logic, well‑defined roles, and robust, testable patterns — we trade a little flexibility for a lot more reliability, safety, and resilience in the systems that keep the lights on and the industrial world running.
Follow The Spec. And Your Data Communications Networks — Won't be a Wreck!
The advent of Ai tools for an against data flow models and data security are changing the network design landscape. Even so, most of the architectural and functional design for a given communications project has in fact already been done for us through a myriad of applicable standards, (e.g. IETF, IEEE, ISA/IEC, CISA, NIST, INL CIE/CCE, HIPAA, PCI, CMMI/C, C2/M2, NERC, ISACA, ISC2, SANS, COBIT, ITIL, PMI PMBOK, and ISO). With this over-abundance of guidance advising us, secure critical infrastructure data network design/build projects and their successful operation have the potential to self-define, if we let them. To elevate the prospect of creating a sustainable data communications system from a desired outcome to a certainty, remember… "Follow the spec. so your data communications systems won't be a wreck."
Schweitzer Engineering Labratories OT SDN — Fewer Knobs. Fewer Data Disruptions. Fewer Network Engineers!
I have recently had the opportunity to work with SEL's relatively new data network solution on a real-world grid project. Here are my own 5 classic data communications network challenges this solution has helped address:\n\nDeterministic performance:\n\n-- It's funny, coming from years of Cisco Systems switch/route design engagements and way of thinking, as opposed to \"More data paths equals more reliability\". I quickly learned this is NOT the mantra nor philosophy for OT data network design. Rather, more paths equal more configuration knobs equals more complexity and feature code exposure (bugs) equals more fragility in the overall network. SEL OT SDN takes a more homogeneous (to OT owners/operations) approach. It enforces simple core data network principles including predictable latency and bandwidth, which is critical for protection, control, and real‑time monitoring in power and industrial systems.\n\nStronger security model:\n-- Centralized control lets you strictly define which devices can talk, on which paths, and for what purposes, reducing attack surface and lateral movement.\n\nSimplified, centralized management:\n-- Instead of configuring dozens of switches one by one, policies and paths are managed from a single controller, making complex OT networks easier to operate. In my project, with a focus on knowledge transfer, we were able to hand-off OA&M for the solution to a group of EE grid engineers, NOT to a group of highly skilled data network engineers. This was perhaps the most impressive result (and lesson we learned) on this project. First time that's ever happened on one of my critical infrastructure projects.\n\nBuilt for critical‑infrastructure reliability:\n-- SEL designs for harsh environments, fail-over, and redundancy. They are the solution of choice for more than 50% of U.S. grid customers for protective relays. So the SDN fabric can maintain communications even during faults or cyber events.\n\nReady for future grid and OT demands:\n-- As more IEDs, sensors, and analytics tools come online, SDN’s flexible, software‑defined paths make it easier to scale and adapt without constant hardware re‑engineering.