data/build-005-engine-v1.jsonGoverned disposition rules, threshold heuristics, inherited decision-gap signal, and explicit non-claims.
Repetition alone is not an automation opportunity. Map the service step-by-step, preserve judgment where it is central, remove low-value repetition, and prototype only the stable rule-bound work.
The complete structured public archive is certified for this build.
This page exists so the durable record does not depend on conversation history. Research, decisions, generated artifacts, audits, limitations, media metadata, plans and canonical source paths are retained here as part of the build itself. A listed repository path proves that an implementation record was retained; it does not independently support a real-world factual claim.
6 of 6 listed retained paths have a public reader link on this archive page. Unlinked paths remain named for traceability but are not represented as publicly inspectable evidence.
data/build-005-engine-v1.jsonGoverned disposition rules, threshold heuristics, inherited decision-gap signal, and explicit non-claims.
The Decision Gap Engine is imported directly so 005 keeps the original problem signal visible while classifying service steps.
Automatic workflow mining, model classification, process-mining integrations, and agentic automation were deferred because they would obscure the form-selection logic this build is meant to expose.
Maps service work into AUTOMATE / KEEP HUMAN / REMOVE candidates with visible reasons and explicit boundaries.
Interactive scenario visual that changes the service path instead of merely restyling it.
Carries signals, dispositions, reasons, and inherited decision-gap context.
Making, method, evidence, and limits.
Low-value repeated work is not automatically preserved simply because it can be automated.
Software may still assist; the label protects central expert judgment and high-consequence ambiguity.
It is not a deployment, ROI, labor, legal, or safety approval.
data/build-005-acceptance-v1.jsonMachine-readable automated/manual release state.
data/build-005-privacy-support-v1.jsonPrivacy and support assumptions for local workflow data.
data/build-005-freshness-performance-v1.jsonResilience and dependency record.
docs/builds/005-release-record.mdFull release-engineering history and automated certification basis.
docs/builds/005-linkedin-production.mdMotion-film production specification, checksum, sampled-frame QA, and remaining phone/platform QA.
005 establishes the form-before-automation boundary that 006 expands into a wider question: does the opportunity deserve software at all?
CURRENT VERIFIED MEDIA / 30-second film · 329.8 KB
FINAL PROPOSITION / MAP THE WORK BEFORE YOU AUTOMATE IT.
SHA-256 b5305b662b6e09de04daf4b842421865d77fbfa1a42997e54770638a1e245fc0Reproducible from data/linkedin-film-specs-v1.json with scripts/render-linkedin-films.py. The website—not a chat attachment—is the canonical media source.apps/web/app/100-builds/005/a/ServiceSoftwareLab.tsxapps/web/app/100-builds/005/b/ServicePathSplit.tsxdata/build-005-engine-v1.jsondata/build-005-acceptance-v1.jsondata/build-005-privacy-support-v1.jsondata/build-005-freshness-performance-v1.jsondocs/builds/005-release-record.mddocs/builds/005-linkedin-production.mdtests/build005.spec.tsThese paths preserve the implementation record. Only items with an explicit public reader link are publicly inspectable here. A file path, working interface or internal engine is not independent support for a real-world claim; synthetic propositions and design reasoning remain labeled within the retained record.