Ask HN: Where does operational truth live before it reaches "systems of record"?
I’m trying to pressure-test a pattern I keep seeing in industrial and asset-heavy operations, and I’d value perspectives from people who’ve lived this.
In many environments (manufacturing, equipment rental, oilfield services, aerospace, medical devices), quality and ops work often starts outside formal systems: - inspection notes written by hand - photos on phones - voice notes from the field - emails and spreadsheets coordinating fixes
ERP/QMS systems exist, but under time pressure the work happens elsewhere first. When an audit, customer escalation, or safety question hits, teams scramble to reconstruct what actually happened from scattered artifacts.
A few questions I’m genuinely curious about: - Have you seen environments where this doesn’t happen? What made them different? - Where does reconstruction pain show up the most — audits, customer disputes, asset recertification, something else? - What information tends to get lost when work is summarized or normalized too early? - Who usually carries the burden of “proving” things are fine when something escalates?
I’m not selling anything or looking to promote a tool. I am just trying to understand where reality breaks abstraction in practice.
Would appreciate any firsthand experiences or counterexamples.
Epigram 102:
102. One can't proceed from the informal to the formal by formal means.
— Alan J. Perlis, Yale
That’s a great way to put it.
What I keep running into is that teams know the work is informal at the edge, but systems are designed as if formality can be enforced at capture time. In practice, that just pushes the work elsewhere.
In your experience, where does that mismatch hurt the most: audits, safety reviews, customer disputes, or something else?
Everywhere.
Computing and formal mathematics rely on exhaustive case analysis and binary logic. And even with The Excluded Middle, there are unprovable statements.
There are at least two incompatible ternary truth tables (hello there SQL NULL) in formal logic. Then there is fuzzy logic, but that is also a formalization.
(NP-complete problems and uncomputable problems in binary logic are another sore point.)
And for informal systems the best people have found so far is hypothesis testing, which is to say that only the rejection of hypothesis based on measurements works, but not confirming a hypothesis.
Turtles and blech all the way down.
Agree with your pov, especially the idea that you can only reject hypotheses, not confirm them.
What I keep seeing operationally is that teams are forced to act before hypotheses can be tested or falsified. For example, inspections completed, assets redeployed, and customers responded to. Only later are they asked to prove correctness.
When that gap shows up for you, what was the concrete trigger? An audit, a customer dispute, a safety review, or something else?
I find there is a lot of value in quick and dirty capture and storage of records in good old fashioned files and directories (that re synced, backed up, etc):
things/thing/2026-02-02-shipping-tracking-number.pdf
things/thing/2026-01-12-before-photo.jpg
things/thing/2026-01-10-scan-of-diagram-sketch.jpg
... etc, just capture all the artifacts this way, be they photos, scans of handwritten notes, print-to-pdf of website orders / confirmation numbers, invoices / receipts, instruction manuals, whatever.
99% of the time, its not needed in the future, 1% of the time, it's a big deal, and in those case you can then analyze what was captured into some more useful summarized notes, spreadsheets, as needed.
Understanding this asymmetry is important, you want a system where it is mostly effortless to capture and store raw artifacts as-is, and it doesn't matter if it takes a few hours to analyze things from one place later as needed. If you have the original artifacts that's a few hours of busywork, if the artifacts don't exist... it's impossible.
This asymmetry framing is really helpful.
I’m curious in the cases where that 1% mattered, what made the reconstruction painful even when the raw artifacts existed? Was it ordering events, understanding intent/decisions, or just finding the right things under pressure?
And were those moments tied to audits, disputes, safety issues, or something else?
the phone photos thing is so real. spent way too many hours trying to piece together what actually happened from someone's camera roll
@scott-iii That’s exactly the kind of situation I’m trying to understand better.
Out of curiosity, when you were piecing it together from the camera roll, what was hardest: ordering events, understanding why decisions were made, or just finding the right photos at all?
And was this tied to an audit, a customer issue, or something else?