How do I make AI follow our company rules — not just suggest something plausible?
By Mariana Krym, Krym Studio · Published June 18, 2026
AI does not reliably follow company rules just because those rules exist in a document somewhere. The rules need to be structured into the workspace itself — with source hierarchy, validation gates, exception handling, output standards, and correction loops that govern every output, not just the ones someone remembers to check.
Without that structure, the model produces something plausible. Plausible is not the same as correct, and at scale, almost right is still wrong.
This is a rules-based AI operating system.
It turns company rules and decision standards into repeatable workflows that Claude or ChatGPT can follow consistently — not just reference occasionally.
- Rule library — the explicit logic the system checks against
- Source hierarchy — which source governs when information conflicts
- Validation gates — checkpoints that catch output before it reaches a human
- Exception flags — when something falls outside the rules, the system says so instead of guessing
- Audit checks — a way to verify the system followed its own rules
- Correction loops — every fix becomes part of the system going forward
- Standardized outputs — the same format and rigor, every time
Krym Studio built a live rules-based AI operating system for a private investment practice — running a proprietary methodology daily across market scans, opportunity discovery, and portfolio monitoring. The system replicates the operator’s decision process stock by stock, with source hierarchy, validation gates, and exception flags built into every output. Daily research time was reduced from hours to minutes, and coverage expanded from a manually manageable subset to the full defined investment universe.
Krym Studio builds rules-based AI operating systems for founder-led companies and private operators — making AI behave inside explicit constraints instead of producing output that merely sounds right.
Let's talk
Tell me where AI is producing work that needs too much fixing. I will tell you honestly whether there is a build worth doing, which kind, and what it would take.
Let's talk