Computational Work Conservation

This technical note establishes the principle of Computational Work Conservation — the proposition that completed computational work persists only through the artifacts produced by that work. When systems lose artifacts, they must redo the same computations. Modern infrastructure frequently discards intermediate results and temporary outputs, treating recomputation as inevitable rather than recognizing it as a direct consequence of lost artifacts. The note proposes that preserving artifact graphs — structures that map the relationships between computational outputs — allows systems to accumulate work over time. This contrasts with current practice in which distributed systems repeatedly recreate similar computations independently, destroying the value of prior effort. The implications extend particularly to agent ecosystems, where multiple autonomous systems can reuse artifacts from prior computation rather than duplicating effort. This framework enables a new computing paradigm — Cumulative Computing — in which systems build upon previously completed work through systematic artifact preservation rather than starting from scratch. This is Technical Note 07 of the Agent Artifact Availability (AAA) Framework series.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-11
DOI
https://doi.org/10.5281/zenodo.19059468
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Computational Work Conservation

Rich Kopcho
Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

Computational Work Conservation

Rich Kopcho
article en

Abstract

This technical note establishes the principle of Computational Work Conservation — the proposition that completed computational work persists only through the artifacts produced by that work. When systems lose artifacts, they must redo the same computations. Modern infrastructure frequently discards intermediate results and temporary outputs, treating recomputation as inevitable rather than recognizing it as a direct consequence of lost artifacts. The note proposes that preserving artifact graphs — structures that map the relationships between computational outputs — allows systems to accumulate work over time. This contrasts with current practice in which distributed systems repeatedly recreate similar computations independently, destroying the value of prior effort. The implications extend particularly to agent ecosystems, where multiple autonomous systems can reuse artifacts from prior computation rather than duplicating effort. This framework enables a new computing paradigm — Cumulative Computing — in which systems build upon previously completed work through systematic artifact preservation rather than starting from scratch. This is Technical Note 07 of the Agent Artifact Availability (AAA) Framework series.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 17%
Scientific Computing and Data Management
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Computational Work Conservation — Rich Kopcho · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS