pharosproduction/production-ai-decision-rules

Production AI Decision Rules v0.1

Public v0.1 candidate · reviewed and approved for publication by Dmytro Nasyrov on September 17, 2026.

This public candidate contains 42 decision records and their native method registries. The companion Decision Lab applies scenario inputs, shows a candidate path and retains missing evidence, exclusions and source boundaries.

Pharos Production's published RAG and fine-tuning decision matrix makes selection criteria and stopping conditions inspectable. This package preserves that approach alongside the native build-or-buy and framework methods, with a separate architecture proposal.

Contents

Config	Draft records	Preserved method
rag	17	Eleven decision rules and six advisories. Ascending priority, first decision match, all/any/none condition groups.
build_buy	12	Weighted criteria, native thresholds, unknown-input gates and blocking constraints.
framework	5	Native framework profiles. Language/deployment filters and preference ordering.
architecture	8	Original proposed pattern rules, with no published canonical source.

All partitions use the draft split. Every row has review_status=NOT_REVIEWED, status=DRAFT and verified_at=null. These frozen per-record fields describe the original preparation snapshot. The subsequent owner review and publication authorization are recorded in publication-approval.json; they do not represent operational control validation.

How to use the records

RAG rules retain their original priorities and exclusion semantics. Build-or-buy retains the signed known-weight formula and its constraint override. The index is not a probability, price estimate or benchmark. Framework ordering reflects selected preferences among profiles that satisfy the hard filters. Architecture rules are an explicit proposal for evaluation, not evidence that one pattern will outperform another.

Each row has record_id, record_type, config, payload_json and lineage fields. payload_json preserves the native rule, criterion or framework object. data.json includes the complete method registries required by the engines. A typed envelope prevents weighted criteria or framework profiles from being silently converted into Boolean rules.

The current schema.json is candidate schema 2.0.0-candidate.1. The earlier public-release contract is preserved byte-for-byte as release-schema-v1.json. Candidate states are a deliberate schema change. They do not satisfy the earlier REVIEWED gate. A consumer of the old schema must opt into the candidate contract explicitly.

Reproducibility and provenance

source-snapshot.json retains the exact native file contents, source commits and file hashes. source-manifest.json indexes them. source-proposals.json records new AI-assisted engineering suggestions separately. Those suggestions have not been adopted into canonical upstream sources. The eight architecture proposals are authored preparation material, not observed results.

To check a downloaded repository with Python's standard library, run:

python3 exporter.py --verify-dataset .

The check rebuilds every JSONL partition and data.json in memory, compares the exported bytes and verifies the retained source-file hashes. It makes no network call. The Space locks the dataset to an exact Hugging Face commit and checks the bundled data.json SHA-256 before evaluation.

Boundaries and review

Framework evidence retains its August 28, 2026 cutoff and historical versions. Verify current capability behavior before implementation. A language listing does not establish feature parity across SDKs. Architecture proposals have no canonical source commit. Their commit and source URL are explicitly null. Unknown scenario inputs remain unknown. The cost benchmark is excluded.

No client records, production telemetry or credentials are included. Examples in the Space are explicitly fictional. AI assistance prepared normalized fields, proposals and packaging. Automated checks cannot supply independent human review, rights approval or actual operational evidence. Dmytro Nasyrov subsequently confirmed that he had checked the package and authorized this public candidate. This owner attestation does not establish independent review, operational effectiveness or canonical adoption of proposals.

Rights and corrections

LICENSE-NOTICE.md preserves source-specific MIT and CC BY 4.0 declarations and attribution. Linked third-party works retain their owners' terms. No new blanket license or human rights-approval signature is asserted for the combined candidate.

Correct source facts in the relevant canonical repository, then regenerate the snapshot. Review new proposals in source-proposals.json before adopting them upstream. Report packaging defects with a record ID, exact dataset revision and file hash, without private evidence payloads. See CHANGELOG.md for this candidate's changes.