Comparison & Recommendation
Deltas between approaches plus a recommended adoption path.
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Side-by-side delta
Evidence-based
Summary: Approach 2 is the target deterministic architecture; Approach 1 is a transition architecture used to accelerate discovery, with strict promotion/expiry rules for LLM output.
| Dimension | Approach 1 — LLM‑First (Controlled) | Approach 2 — Deterministic‑First | Delta |
|---|---|---|---|
| Role of LLMs | Early semantic bootstrapping, provisional outputs with expiry & promotion gates. | Non-authoritative; optionally for naming/explanation; never defines truth. | A1 trades faster discovery for added governance controls. |
| Replayability | Required eventually; LLM outputs must be retired/promoted. | Mandatory at every layer (schema enforcement, deterministic ingestion, rules/ML). | A2 stronger audit posture. |
| Governance model | Promotion pipeline: LLM → human validation → rules/ML → authoritative DB. | Human-in-the-loop on semantics; no self-modifying behavior. | Both require governance; A1 adds explicit transition controls. |
| Time-to-value | Faster demos and taxonomy discovery in early phases. | Slower initial modeling, but stable baseline early. | A1 best for early discovery; A2 best for regulated scale. |
Illustrative scoring chart
A visual summary aligned with both documents (scores are illustrative, not measured).
Recommendation
Best for devs & org👩💻Best approach for developersPragmatic
Start with Approach 2 as the backbone (contracts, schemas, replayable pipeline), and optionally add the Approach 1 bootstrap layer as an offline accelerator where uncertainty is high.
- Keep ingestion + schema strictly deterministic.
- Use LLMs only for summarization/naming and only if outputs have expiry + promotion workflow.
- Promote learnings into rules DSL / ML models and retire the LLM outputs.
🏢Best approach for the organisationAudit-ready
Approach 2 is the organisational default (auditability, compliance, determinism, predictable cost). Use Approach 1 only as a controlled transition state with explicit gates.
- Semantic layer remains governed core IP.
- No LLM output can be production-authoritative without a deterministic successor.
- Agents remain read-only and recommendation-only.
🧾Decision rule (industry-standard)Simple gate
If an output must be reproducible / auditable / compliance-grade, it must be produced by deterministic rules/ML — not an LLM.