Months ago I listed what a system needs before an agent can run unattended and treated the list as finished. It wasn’t. A stop button handles the runaway. It does nothing for the run that dies on step nine of fourteen.
Every governance program is built to add definitions and none of them can retire one. In a regulated shop that gets worse, because the instinct to keep every record gets misread as a ban on ever deprecating a definition. They’re different objects.
The moment you harvest a platform out of an app, the app stops being something you can change quietly. That standing cost lands hardest on the team that built it, and most extraction plans never budget for it.
The whole agent-reliability project is trying to engineer the one thing a tool can’t have: accountability. Data governance already named this. The agent is a custodian, and we keep trying to promote it to owner.
I built audit logs and self-voiding approval gates to make an autonomous agent safe to run unattended, then realized I’d rebuilt a regulation the FDA shipped in 1997. The regulated world solved agent trust before agents existed.
I argued the way to find a platform’s real boundary was to watch the second team that wanted in. The catch I keep running into: two consumers tell you what they have in common, and that’s not the same thing as what the platform is.
The samples post ended on seating a data steward. This is what you build around that seat in a regulated life sciences org: the roles you actually need, the order to do it in, and why the regulation is the only budget argument that ever works.
Someone asked how many samples we have and three systems gave three different numbers. The dependency order behind vocabulary, ontology, semantic layers, catalogs, and contracts, and why the piece everything stands on is a role most orgs never seat: the data steward.
Birgitta Böckeler’s harness-engineering framework treats iteration as human work. Someone watches, notices, edits the rules. That assumption breaks the moment agents run overnight. The next move is sensors with memory.
Enterprise data strategy has moved its destination from ‘break the silos’ to ‘vectorize everything.’ The step in between is the layer that makes vectors actually work, and it’s the one most roadmaps quietly skip.