I build before I publish.
Until I've implemented a pattern, I treat it as a hypothesis. Building it is also the quickest way to find out that an elegant idea doesn't work.
I'm Pedro Miguel Lourenço, an operations and AI strategy advisor based in Porto. I spent most of my career inside transformation programmes in industrial companies. Now I work on how those companies bring AI into their operations, and I research the knowledge systems it depends on.
Most enterprise AI problems are knowledge problems.
A company runs on rules, constraints and judgement that mostly live in documents, old systems and people's heads. Ask a model to decide something in that setting and you get a fluent answer with nothing behind it. A bigger model doesn't fix that. Writing the knowledge down in a form a system can query, check and cite does.
My research is about that work: knowledge graphs that hold up when the organisation changes, retrieval based on how things are connected, and agents that show the evidence for each conclusion. OpenFoundry is where I build and test those ideas.
I judge the work by one test: would it hold up in a live operation?
Until I've implemented a pattern, I treat it as a hypothesis. Building it is also the quickest way to find out that an elegant idea doesn't work.
When enterprise AI fails, it's usually because the rules and constraints an answer depends on were never written down anywhere a system could read. In my experience, once that structure exists, smaller models do much better.
In operations, an answer without a source is worse than no answer, because people act on it as if the system were accountable. I design the evidence trail in from the start.
The question I spend most time on is where a decision should pass from the system to a person, what triggers the handoff, and what that person needs to see in order to act. That boundary belongs in the design.

I spent 10+ years on transformation programmes across Europe and North America: first as a consultant, then as a manager, then running a digital transformation consulting practice. The work covered manufacturing execution, prefabricated construction and process industries, places where a design decision shows up as a bottleneck on the line and the documentation is usually three revisions behind the equipment.
That background is why my research is shaped the way it is. Ontology governance matters because organisations reorganise. Provenance matters because someone eventually asks why. File-based knowledge graphs exist because a graph database is one more system a plant team has to be convinced to run.
I publish what I learn, and I'm glad to hear from anyone working the same problems.
I run commercial and product strategy for an Industry 5.0 software company, including its research and technology partnerships in EU-funded innovation programmes.
My own research on knowledge graphs and AI agents for operations, published on this site. OpenFoundry is part of it.
I teach the Industry 5.0 module of the Digital Transformation Executive Master, on how AI and other technologies change operating models.
I owned the methods behind the firm's digital consulting work and led R&D programmes with universities and technology providers that tested new technology in working operations.
I joined as a consultant and became a manager, leading a team of eight on programmes in several countries across manufacturing, retail, healthcare and technology. Most of what I know about plant floors I learned here.
I'm open to advisory, lecturing and research partnerships. I also enjoy a good argument about AI.