As-Of Information-Set Pinning

Problem

Re-running the decision later produces a different answer, and nothing in the record says whether the agent changed its mind or the world underneath it changed. Because each read resolved to whatever the source held at the moment of the re-run, the original inputs are unrecoverable, so a dispute cannot be settled and an audit cannot distinguish a defensible call from a mistake. The same gap corrupts measurement in the other direction: an agent evaluated on historical periods reads restated figures and reasons with weights trained on text published after the decision date, so it scores itself on facts it could not have had and the backtest overstates what the deployed system would have done.

Solution

Fix a single as-of timestamp when the decision starts and route every read through a resolver that turns a source plus that timestamp into an immutable version identifier: a dated model snapshot rather than a moving alias, a corpus or index version rather than a name, a vintage of reference and market data rather than a current quote, and a table version or AS OF timestamp on a store that keeps past states addressable. The resolved identifiers are written into the decision record as a pin manifest, so the decision carries the description of its own inputs rather than a pointer to whatever those inputs later became. Re-execution at dispute, examination or backtest time replays the manifest: the same snapshot, the same corpus, the same table versions, so a difference in outcome is attributable to the agent and not to the world. Retention on every pinned source is set to at least the window in which the decision can be questioned, and a read that cannot be served at the recorded version fails the run rather than falling back to the current value, which turns a silently mutating dependency into a visible error.

When to use

• A decision is dated and can be questioned later by an examiner, a customer dispute or a regulator.
• Upstream sources are restated, revised or re-crawled in place rather than versioned beside their earlier values.
• An agent is scored on historical periods, where reading current values or a model trained past the decision date inflates measured performance.
• Two runs of the same case must be comparable, so the input set has to be held constant across them.