Foundational Concepts
This method helps a computer track why it believes each fact. Each fact keeps links to the facts and sources under it. A fact can rest on a file, a record, or another fact. The system checks those links as work goes on. A source changes or a key fact fails. The system then removes the beliefs that no longer have support. Other beliefs stay in place when support still holds.
Think of a simple case in a work file. A note says a server runs one program version. A second note uses that fact to plan a fix. The source file then changes to a new version. The system marks the first note as out of date. The system clears the plan that rests on that note.
The rest of this brief gives the history, the method, the 2026 gap, and a first project plan.
The six cases below work the method in full. Each case names the belief, the premises, the change, and the cascade in order. Each case ends with the limit of the layer in that setting.
A care team treats a patient for bacterial pneumonia. The diagnosis is a belief in the chart system. Four premises support the diagnosis.
The imaging team retracts the image read after a second review. The second review finds atelectasis and no consolidation. The first premise fails, and the diagnosis loses its strongest support. The label engine marks the diagnosis OUT. The antibiotic order rests on the diagnosis alone. The engine marks the antibiotic order OUT and flags the order for clinician review. The treatment plan cites the diagnosis in three sections. Each section loses support and retracts in the same cascade. The follow-up image order rests on the treatment plan. The engine marks that order OUT. The fever care order rests on the temperature record alone. That premise still holds, and the order stays IN. The justification chain answers the audit question for the antibiotic order. A reviewer follows the links to the premise values in force on the order date. The layer tracks support and makes no diagnosis. Clinicians choose the replacement diagnosis and the new treatment.
An intelligence profile assesses the health and the support base of a foreign leader. The profile holds each judgment as a belief with named sources. Three source reports support the judgment that a named faction backs the leader. Each report carries a reliability note from the handling team.
The agency discredits Source B after a fabrication check. The funding report retracts, and its premise fails. The funding judgment rests on the Source B report alone. The engine marks the funding judgment OUT. The succession assessment cites the funding judgment as one premise. The assessment loses that premise and flags for re-derivation. The health judgment rests on reports from Source A and Source C. Those premises still hold, and the health judgment stays IN. An analyst requests the dependency list for Source B. The layer returns every judgment with a link to that source in one list. The layer marks reach and support only. Analysts re-derive each flagged judgment by hand.
A brigade staff holds one course of action as the active plan. The plan is a conclusion in an assumption-based network. Four assumptions support the plan.
A new reconnaissance report corrects the enemy unit position. The unit sits on the planned route, and the second assumption fails. The plan label loses the environment with the failed assumption. The engine marks the plan unsupported in the current picture. Three orders cite the plan as their premise. Each order flags for review before execution. A second plan rests on a different assumption set. That set still holds, and the second plan stays active. Command receives the list of affected orders in one pass. The layer lists exposure and gives no tactical advice. Commanders choose the replacement course of action.
An operations agent stores facts from a project plan file. Each fact carries a link to the file section as its premise. The file states a deployment window on Friday at 18:00. The agent derives a freeze start on Thursday from the window. The agent derives a notice deadline on Wednesday from the freeze start. A calendar hold and a team notice rest on the deadline. The plan owner edits the file and moves the window to Saturday. The stored window fact loses support and drops. The freeze start and the notice deadline drop in the same cascade. The calendar hold and the team notice flag for rewrite. Facts from the staffing roster file keep support and stay IN. The audit log records each removal with the file edit as the cause. The layer clears derived facts and writes no replacements. The agent rebuilds its schedule from the new file version.
A compliance file holds eligibility claims for one care provider. Each claim rests on an enrollment record and an exclusion check. The enrollment record covers a stated period. The claims support service authorizations and payment requests. The payer reports a lapse in the enrollment record. The lapse covers the last two months of the period. The engine marks each claim inside the lapse window OUT. Authorizations that cite those claims flag for review. Payment requests in the same window flag for hold. Claims before the lapse keep full support and stay IN. The audit log lists each flagged item with the lapse as the cause. The layer flags exposure and decides no eligibility question. Compliance staff resolve each flagged claim with the payer.
An enclosure design holds a thermal claim for a handheld device. The claim states a surface limit under full load. Three premises support the thermal claim.
The vendor revises the data sheet and raises the peak draw to seven watts. The first premise fails, and the thermal claim drops OUT. The fan selection claim cites the thermal claim. The battery life estimate cites the peak draw and the thermal claim. Both claims lose support and flag for rework in order. The certification claim cites the thermal claim as evidence. The certification claim flags for hold before submission. Claims for other components keep their premises and stay IN. The layer propagates the change and makes no design choice. Engineers set the new heat path and the new fan.
The six cases share one pattern. A premise falls, the layer traces the links, and dependent claims retract in order. Claims with support from other premises stay in place in each case.
Goal. The desired end state is one justification layer under agent memory in daily use. Every stored belief carries its premises and its sources. Every source change triggers a check of all beliefs that rest on that source.
Proof target. The project proves one claim with an exact retraction test. After a source change, the layer finds and removes or recomputes 100 percent of the beliefs that rest on the changed source. Agent answers show fewer stale fact errors than answers from plain memory storage.
Product at the end. The product is the Justification Layer, version 1. The layer contains a graph belief store, a justification writer, a label engine, a change monitor, and an audit log. Agent memory systems place the layer under the memory store.