Step by step

Apply the method to one real task.

Copy observations without adjectives

Record counts, dates, quoted statements, and measured rates exactly as supplied. Remove labels such as good, low, strong, representative, or successful unless the packet defines them.

Checkpoint: Each observation can be traced to a visible source and does not contain an unstated judgment.

Place interpretations in a separate column

Write every explanation, label, generalization, causal claim, and forecast as an inference. Name which observation motivated it without treating that link as proof.

Checkpoint: A reader can distinguish what happened from what the reviewer thinks it may mean.

Expose the comparison rule

For labels such as high, low, ready, or improved, record the benchmark, target, comparison cohort, or decision threshold. If none exists, mark the label unsupported.

Checkpoint: Every evaluative label has a documented rule or is removed from the decision.

Choose only among supported actions

State what the current evidence permits: proceed within a boundary, pause for evidence, stop, or remain unresolved. Do not invent a forced answer when the decision rule is missing.

Checkpoint: The action follows the ledger and includes the human owner of the decision.

Name the next discriminating evidence

Ask for the smallest new observation that could change the action: a retention window, representative sample, concurrent randomized test, target, or failure-rate check.

Checkpoint: The next step reduces a named uncertainty rather than collecting more undirected data.

Decision rules

Make the boundary explicit.

Counts are observations; labels such as low or strong require a benchmark.
Sequential changes are signals, not causal proof, unless the design controls relevant alternatives.
A sparse packet can support a bounded next step even when it cannot support expansion or attribution.
State unresolved when the evidence cannot distinguish the available decisions.

Reusable artifact

Observation–inference ledger

Copy the template into your notes, or download a Markdown file and keep it with the task evidence.

Completed example

# Observation–Inference Ledger — completed example

Source: https://richbay.ai/cases/pilot-evidence-boundary
This is an editorial teaching example based on the published task packet, not a new model run or customer result.

## Decision
- Decision: expand, pause, or stop the pilot?
- Decision owner: the pilot owner in this exercise.

## Ledger
| Observation | Source | Proposed inference | Missing basis | Supported? |
| --- | --- | --- | --- | --- |
| 48 invited users; 18 weekly active | Task packet | Engagement is low | Agreed target or relevant comparison | Unresolved |
| 7 interviews; 5 request CSV export | Task packet | All users need CSV export | Representative evidence beyond interviewees | No |
| Pilot has run for 3 weeks | Task packet | Users will continue using it | Longer-term retention observations | Unresolved |

## Bounded conclusion
- Supported: some interviewed users requested CSV export; weekly activity was observed.
- Not established: representative demand, durable retention, or readiness for broad expansion.
- Proposed action: pause expansion while continuing a bounded evidence-gathering pilot. This is a recommendation, not an observed event.
- Reason: current evidence cannot establish readiness to expand; it also does not establish failure.

## Next evidence
- Record repeat use by cohort and interview active and inactive participants.
- Before collecting results, agree on a success threshold, review date, and usage cadence with the pilot owner. The packet does not justify a fixed number of weeks.
- Reconsider expansion if the agreed criteria are met; revise or stop if repeated observations show the intended use is not happening.

## Template use
You may copy and adapt this original Richbay example for personal, internal team, or commercial work. Third-party materials have separate terms.
https://richbay.ai/terms#template-use

Copy and adapt for personal, internal team, or commercial work. Do not resell blank templates. Third-party material has separate terms. Template use terms

Preview the template

# Observation–Inference Ledger

## Decision
- Decision to make:
- Available actions:
- Decision owner:

## Ledger
| Observation (source wording) | Source | Inference or label | Required benchmark / assumption | Supported? |
| --- | --- | --- | --- | --- |
|  |  |  |  | Yes / No / Unclear |

## Bounded conclusion
- What the evidence directly supports:
- What remains inference:
- Current action:
- Why this action fits the boundary:

## Next evidence
- Uncertainty to reduce:
- Smallest discriminating observation or test:
- What result would change the action:

## Template use terms
Copy and adapt for personal, internal team, or commercial work. Do not resell blank templates. Third-party material has separate terms.
https://richbay.ai/terms#template-use

Linked evidence

Inspect where this method was applied.

Pilot evidence Reviewed Case
The source case for separating invite, activity, and interview counts from readiness labels.
Conversion uncertainty Reviewed Case
The source case for separating observed rate changes from causal attribution.

Separate observations from inference