Creating A Tiny Model Incident Plan Before First Use
A practical owner guide for deciding what to do when a focused local model gives a risky answer, stalls, or needs human review during real operations.
Plan for the bad day before launch day
A tiny model is usually designed for one narrow job. It may sort customer messages, extract fields from intake notes, score a lead, rewrite a private draft, or return a small JSON decision for an internal tool. That focus is what makes it useful. The owner can understand the job, review the answer, and keep the cost under control.
Even a focused model still needs an incident plan before it touches real work. The plan does not need to be dramatic. It is simply the written answer to one practical question. What should the team do when the model gives an answer that could slow the business, confuse a customer, expose private information, or send work to the wrong place.
A small incident plan keeps a tiny model from becoming a mystery system. It tells staff when to pause automation, where to record the problem, who reviews the output, and how the workflow returns to normal. That kind of plan is useful even if the model never has a serious failure, because it makes daily review calmer and more consistent.
Name the incidents that matter for the task
Start with the specific job the model performs. A support routing model has different risks than a lead scoring model. A document extraction model has different risks than a private rewriting model. Do not copy a generic incident policy and hope it fits. Write the plan around the actual output.
For a routing model, the incidents may include sending urgent messages to the wrong queue, marking a complaint as low priority, or returning a blank category. For a lead model, the incidents may include rejecting a good lead, marking a weak lead as ready for a call, or missing a required field. For a JSON extraction model, the incidents may include invalid JSON, invented values, swapped dates, or a missing review flag.
Keep the first list short. Five to seven incident types are enough for most first launches. The goal is not to imagine every possible failure. The goal is to make the common and risky failures easy to recognize.
Set severity in owner language
Severity should be clear to the person who owns the workflow. Avoid labels that only engineers understand. A simple three level scale works well.
Level one means the output was wrong but harmless. The owner corrected it during normal review and the business did not slow down. Level two means the output affected a queue, customer reply, report, or decision, but a person caught it before major damage. Level three means the output reached a customer, exposed sensitive information, moved money, changed access, or caused a process to stop.
This scale helps the owner decide the next action without debate. Level one goes into the example log for future improvement. Level two triggers a short review of nearby examples and recent changes. Level three pauses the model path until a human reviews the cause and confirms the safe fallback.
Write the pause rule before anyone needs it
Every tiny model should have a clear pause rule. A pause rule says when automation stops and human review takes over. This protects the business from repeating the same mistake while everyone is still trying to understand it.
A practical pause rule might say that three level two incidents in one day pause automatic routing. Another rule might say that any level three incident immediately sends new items to manual review. For structured output, the rule might say that invalid JSON more than twice in an hour pauses downstream actions but still saves the original input for inspection.
The pause does not have to shut down the whole product. It can be narrow. The model can keep logging suggestions while the system stops acting on them. The owner can still see what the model would have done, but people make the final decision until the issue is resolved.
Keep a small incident record
An incident record should be easy to fill out. If it takes too long, staff will avoid it. The useful fields are the original input, the model output, the corrected output, the severity, the date, the reviewer, and the action taken. If private data is involved, store the record where the business already keeps sensitive review material, not in a public folder.
Add one field for suspected cause. The reviewer can choose from plain options such as unclear input, missing rule, stale example, bad format, privacy concern, or unknown. This field does not need to be perfect. It gives the builder a starting point when improving the prompt, schema, test set, or training examples.
Over time, these records become a useful improvement queue. They show whether the tiny model is failing because the task is changing, the examples are incomplete, the output schema is too large, or the fallback rule is too weak.
Decide how normal service resumes
A pause is only useful if there is a clear way to resume. The incident plan should say who can turn automation back on and what proof they need. That proof might be a corrected rule, a new test case, a passed acceptance check, or a short owner note saying the workflow is safe to continue.
For a small local model, resuming service should be deliberate but not heavy. The owner might review ten recent examples and confirm that the corrected behavior is acceptable. The builder might add the incident to the evaluation set so the same issue is tested before future changes. If the model feeds another system, the team should also verify that no bad output remains in a queue waiting to be processed.
This final step prevents a quiet restart that repeats the same problem. It also gives the owner confidence that the incident created a better operating habit, not just a stressful interruption.
Make the plan part of delivery
Tiny Model Generator should treat the incident plan as part of a useful delivery package. The model file matters. The prompt or runtime settings matter. The dataset and eval report matter. The incident plan connects those pieces to real business use.
A good first plan can fit on one page. It names the model job, lists the main incidents, defines severity, states the pause rule, shows the incident record fields, and explains how service resumes. That is enough to help an owner launch with more confidence.
The best tiny models are not trusted because someone says they are smart. They are trusted because the workflow has review points, fallback rules, clear records, and simple ways to improve. An incident plan gives the business that safety layer before the first real mistake has a chance to become a pattern.