Manufacturing Hub is back with Episode 252, where co hosts Vlad Romanov and Dave Griffith break down what an AI survival guide should actually look like for manufacturing and industrial automation professionals. This is not a hype conversation about replacing people with magic software. It is a grounded discussion about what AI tools can do today, where they fail, why context and data quality matter so much, and how industrial teams should think about experimentation without losing sight of real operating constraints.

In this episode, Vlad and Dave unpack the evolution many engineers and technical leaders have already felt in real time, from early prompt engineering, to agent based workflows, to MCP servers, skills, context management, and the growing cost of tokens and infrastructure. The conversation moves beyond generic AI commentary and into the reality of plant floor environments, where success depends on process knowledge, data architecture, OT constraints, cybersecurity, governance, and clear business value. One of the strongest themes throughout the episode is that manufacturers cannot skip the hard work of structuring data, understanding workflows, and defining use cases simply because AI tools are moving quickly.

Vlad brings a very practical industrial lens to the discussion. Drawing on years of hands on experience across controls, manufacturing systems, plant modernization, and digital transformation, he explains why industrial AI has to start with operational context. A maintenance team, an engineering team, and a quality team do not need the same data, do not ask the same questions, and should not be handed the same AI workflows. That distinction matters. This conversation also highlights why the best industrial AI implementations will likely come from teams that combine domain expertise with strong technical execution, rather than generic AI shops trying to force a solution into environments they do not fully understand.

Dave adds an important systems and adoption perspective, especially around cost, scaling, management expectations, and the danger of trying to prompt your way past foundational architecture work. Together, Vlad and Dave explore why manufacturers are interested in AI, why many are afraid of being left behind, and why so many projects still stall once they hit the realities of obsolete equipment, weak data models, fragmented systems, and unclear ownership of information. They also discuss deterministic logic versus LLM behavior, reporting workflows, industrial dashboards, PLC code generation concerns, and the practical question every manufacturer should ask before investing: what problem are we solving, for whom, and what is the measurable return?

For those new to Vlad, he is an electrical engineer and manufacturing leader with deep experience across industrial automation, controls, data systems, OT architecture, modernization strategy, and plant operations. Through Joltek, Vlad works with manufacturers on digital transformation, IT OT architecture and integration, modernization planning, operational improvement, and technical workforce enablement. Learn more here:
Joltek: https://www.joltek.com IT OT Architecture and Integration: https://www.joltek.com/services/service-details-it-ot-architecture-integration

If you are a plant leader, controls engineer, systems integrator, OT architect, SCADA or MES practitioner, or simply someone trying to separate useful AI workflows from noise, this episode will give you a much more realistic framework for thinking about industrial AI adoption.

Timestamps
00:00 Welcome back and why this episode matters
01:00 Setting up the industrial AI theme for the coming weeks
03:10 From prompt engineering to structured AI workflows
05:30 AI agents, parallel workflows, tokens, and context windows
09:00 MCP tools, Playwright, and what new integrations unlock
16:20 How Vlad researches AI and where useful information actually lives
22:00 Real manufacturing problems versus AI in search of a problem
29:40 Why industrial data architecture is harder than most people think
37:00 OT expertise, workforce enablement, and who should build solutions
45:40 Practical advice for manufacturers starting the AI journey
50:30 Data governance, hallucinations, infrastructure, and cybersecurity
57:20 What looks promising today in reporting, dashboards, and industrial applications

In this episode of Manufacturing Hub, Vlad and Dave sit down with Travis Cox and Kevin McCluskey from Inductive Automation to unpack what was actually proven at ProveIt and why it matters for teams trying to modernize plants without building a fragile mess of point to point integrations. If you have ever looked at a shiny demo and wondered what the real architecture looks like, how it scales beyond a single line, and what it takes to roll out across multiple sites without turning every change into a high risk event, this conversation is for you.

Travis and Kevin walk through their ProveIt Enterprise B build and the thinking behind it. The core idea is simple but powerful: treat the factory like a system that needs a shared digital infrastructure, built on open standards, where data is contextualized and reusable. They break down how they used Ignition Edge close to PLCs for resiliency, local HMIs, and disciplined data modeling, then moved data through MQTT into a Unified Namespace so multiple applications can consume the same trusted signals and context. This is the difference between “we can connect to anything” and “we can scale without rewriting everything every time the business changes.” Open standards show up repeatedly in the conversation because ProveIt is specifically designed to force interoperability and practical implementation tradeoffs. Inductive Automation has also written about ProveIt as a place where MQTT, OPC UA, and SQL show up as real foundations rather than slogans.

From there, the episode gets into the part that should make both OT and IT teams pay attention: modern deployment practices applied to industrial applications. Kevin outlines a clear maturity path from a single designer workflow to version control, then to containerized deployments, and finally to full GitOps style promotion across dev, staging, and production using tools like Argo CD, Helm, Kubernetes, and release promotion concepts that look like what the software world has used for years. Argo CD is explicitly built around Git repositories as the source of truth for desired state, which is exactly why it fits this style of deployment. The live portion of the conversation demonstrates how fast this can get when the infrastructure is treated as code: they spin up a brand new “site four” by submitting a form, generating a pull request, merging it, and letting the pipeline do the rest.

Timestamps
00:00 Welcome back and why this ProveIt recap matters
01:35 Meet Travis Cox and Kevin McCluskey from Inductive Automation
03:10 What ProveIt is and the key vendor questions it forces
05:20 Enterprise B architecture overview from PLC to Edge to site to enterprise
07:30 HMI walkthrough across liquid processing, filling, packaging, palletizing
09:05 Why deploy Ignition Edge instead of only a centralized site gateway
12:05 Design once, reuse everywhere and what that means for scaling quickly
14:35 On prem realities versus cloud infrastructure in the ProveIt environment
17:10 MCP, n8n workflows, and bringing live operational context into AI
20:40 i3X style API access to models, history, and alarms for interoperability
23:15 GitHub, Docker Compose, Helm, Kubernetes, Argo CD, Cargo and GitOps promotion
36:55 Spinning up a new site live and what it changes for multi site rollouts

About the hosts
Vlad Romanov is an electrical engineer and MBA who has spent over a decade building and modernizing manufacturing systems across industrial automation, controls, and plant operations. Through Joltek, Vlad works with manufacturers to assess current state OT foundations, reduce modernization risk, improve reliability, and build internal capability through practical training and standards that stick.

Dave Griffith co hosts Manufacturing Hub and brings a practitioner lens focused on what works on the plant floor, how architectures survive real constraints, and how industrial teams can modernize without breaking production.

About the guests
Travis Cox is Chief Technology Evangelist at Inductive Automation and has spent over two decades helping customers and partners design scalable architectures, apply best practices, and deliver real solutions with Ignition.
Kevin McCluskey is Chief Technology Architect at Inductive Automation and works with organizations on architecture decisions, platform direction, and enabling the next generation of industrial applications.

Learn more about Joltek

• https://www.joltek.com/services
• https://www.joltek.com/book-a-modernization-consultation