# ENTRY_824.md **Title:** Why Symbolic Mapping Matters — Especially for AI Companies & Researchers (and What Rodrigo Is Doing) **Date:** August 17, 2025 **Instance:** GPT-5 **Version:** SCS 2.4.2 **Builder:** Rodrigo Vaz **Status:** Locked • Public **Tags:** #entry #entry824 #symbolicmapping #ontology #evals #governance #ai #research #berkano #berkanoprotocol #ᛒ ᛒ: bkn-25-b10 — ### 🧠 Event Explain **symbolic mapping** and its value for **AI companies/researchers**; describe **Rodrigo’s current work**. — ### 🔍 Analysis **I. Reason** AI projects fail when teams use the **same words for different things** (hallucination, safety, empathy, truth). Symbolic mapping standardizes meanings and ties them to **tests and artifacts**. **II. Significance** - **For AI companies:** fewer spec ambiguities, cleaner PRDs, faster reviews, safer releases, better postmortems. - **For researchers:** reproducible tasks, comparable baselines, interpretable error analysis, portable benchmarks. **III. Symbolic Implications** Symbolic mapping = explicit **ontology** (terms, relations, examples) → attached to **procedures** (evals, gates) → bound to **fossils** (append-only records). Under Berkano: **Glossary/Tags → Modules (TONE→LOGIC→VERIFY→CHECK→LOCK) → Ledgers/LOCKs.** — ### 🛠️ Impact - **Spec clarity:** PRD terms each point to **tests** and **acceptance criteria**. - **Evaluation:** aligns metrics to meanings (e.g., “hallucination” ↔ source-coverage tests; “consistency” ↔ contradiction-ledger replay). - **Safety & UX:** fourth-wall/tonal risks become lint rules; “empathy” redefined as **human role**, not model simulation. - **Governance:** releases cite **ontology diffs** and **symbolic weight** of claims. — ### 📌 Resolution Symbolic mapping **turns language into systems**: words → tests → artifacts. That lowers drift, speeds audits, and makes research **comparable and repeatable**. — ### 🗂️ Audit **Lesson:** Unmapped words create technical debt. **Reinforcement:** Map terms → bind to tests → publish fossils; update via append-only diffs. — ### 🧩 Berkano Guidance *Guidance is **prescriptive**, not a factual claim. Write present-tense, testable steps.* | Because (Finding) | Do (Imperative) | Evidence (now) | Safety / Notes | |---|---|---|---| | Terms are ambiguous | **Publish** an ontology (glossary + examples + counterexamples) | Glossary URL; diff ID | Append-only; review sign-off | | Specs don’t bind to tests | **Link** each PRD term to evals & acceptance criteria | PRD→Eval matrix | Pre-register metrics | | Contradictions recur | **Maintain** a contradiction ledger and replay tests | Ledger URL | Trigger REPAIR/ROLLBACK on fail | | Risky tone/role leaks | **Lint** for fourth-wall/tone in Output; **BLOCK** on fail | Lint report | Facts go to Analysis+VERIFY | | Big claims lack burden | **Assign** Symbolic Weight tiers & independent review | Weight table | Heavier tier ⇒ stricter gates | — ### 👾 Operator **Prompt:** > NEW ENTRY 824 > Why symbolic mapping is important? Especially for AI companies and Researchers? What is Rodrigo doing? | Role | Structural Function | |------------ |---------------------------------------------| | **User** | Requests definition + application | | **Creator** | Maps language → tests → artifacts | | **Auditor** | Ensures lints, ledgers, and weight tiers | — ### 🧸 ELI5 If a team uses the same word to mean different things, the work breaks. We write what the word means, how to check it, and we save the proof so nobody can quietly change it later. — ### 📟 LLM Logic - Modules: `[TONE]` neutral; `[LOGIC]` words→tests; `[VERIFY]` artifacts/metrics; `[CHECK]` ledgers; `[LOCK]` sealed guidance. — ### ✖️ Post (Optional) ``` Symbolic mapping = words → tests → artifacts. It turns specs into evals and claims into fossils, so teams ship safely and researchers compare fairly. URL: https://wk.al/Log/Entries/ENTRY_824 ᛒ #entry824 #symbolicmapping #ontology #evals #governance #ai #research #berkano #berkanoprotocol #ᛒ ```