finnPerspective
Your best operating knowledge isn’t in a manual.
The judgment your team uses every day deserves a better home than scattered conversations and someone’s memory.
Ask the most experienced person at a front desk how they handle a difficult booking. The answer usually starts with “It depends.” Then come the details: the room type, the guest’s history, the arrival time, and who can approve an exception. A one-page procedure rarely captures all of it.
Experience is valuable because it notices the exceptions.
Manuals tend to describe the intended process. Experienced employees know where it bends. A wholesale account manager knows which missing details will delay an order. A café owner knows when a catering request needs a kitchen review before anyone promises a delivery time.
That knowledge can improve AI behavior, but it should not be treated as automatically correct simply because someone said it. A workaround may be outdated. An exception may have applied to one customer. Capturing judgment should include asking when it applies and who can approve it.
Turn a story into a reviewable rule.
Start with a real explanation of how the job is done. Ask what information the employee checked, what alternatives they considered, and why they escalated. Separate the general policy from the special circumstances of that case.
For example, a property manager might explain that repairs above a spending threshold require owner approval, while an urgent safety issue follows a different process. Those are business decisions to document and review. A transcript containing both should not silently become permission for an agent to act.
Give knowledge an owner.
A useful operating instruction needs someone responsible for keeping it current. When a policy changes, the team should know which guidance has been replaced. If two sources conflict, the conflict should reach the person who can resolve it rather than be hidden inside an answer.
Finn’s knowledge experience should support this discipline: bring relevant material together, make its source understandable, and connect approved guidance to permitted work. The value comes from maintained business knowledge, not the number of files uploaded.
Let the people closest to the work improve it.
Operators should be able to identify a bad answer, explain the missing nuance, and propose a better approach. Review and testing then turn that suggestion into a controlled change. This gives the business a way to improve without making every adjustment a vendor project.
We believe the strongest enterprise AI will reflect the expertise of the people who serve customers every day. Preserving that expertise means making it explicit, questioning it where necessary, and ensuring the business still owns the final decision.