ervers, or databases.** ### The Problem - The epistles codebase is large (forum, game worlds, AI systems) - The event ledger will grow unboundedly - The King investigates from an iPhone - Full codebase scans would timeout, drain battery, or crash the browser ### The Solution: Budgeted Incremental Investigation ```javascript { investigation: { // Resource budget for this investigation budget: { maxEvents: 1000, // Don't load more than 1000 events at once maxCodeFiles: 50, // Don't open more than 50 files maxDepth: 5, // Don't recurse deeper than 5 maxTime: 30000, // Don't run longer than 30 seconds maxMemory: "50MB", // Don't exceed memory estimate }, // Pagination strategy: "incremental", // Load first 100 most relevant events, then offer "load more" // Relevance ranked by: recency, causal proximity to subject, evidence quality // Progress tracking (resumable) progress: { eventsExamined: 247, eventsTotal: 15203, estimatedRemaining: "4 minutes at current pace", checkpoint: "solidivism:inquiry:floor-glitch:v1:checkpoint-3", // Can pause and resume without losing progress } } } ``` ### Relevance Ranking Not all evidence is equally worth examining first: ```javascript function rankRelevance(event, subject) { let score = 0; // Causal proximity: direct cause/effect scores highest if (event.target_id === subject) score += 10; if (event.actor_id === subject) score += 8; // Temporal proximity: recent events score higher const hoursAgo = (now - event.recorded_at) / 3600000; score += Math.max(0, 10 - hoursAgo); // Evidence quality: verified > inferred if (event.confidence === 'high') score += 5; // Contradictions: always relevant (need resolution) if (event.contradicts) score += 15; return score; } // Examine highest-scoring first. Stop when budget exhausted or question answered. ``` --- ## 7. CAPACITY AND RETENTION STRATEGY **Preserve provenance and essential evidence while acknowledging finite storage.** ### Tiered Retention ```javascript { retention: { // Tier 1: Permanent (never deleted) permanent: [ "Entity identity records (who/what exists)", "Causal edges (what caused what)", "Contradiction records (what disagreed)", "Authorization records (who approved what)", "Self-examination records (how reasoning changed)" ], // Tier 2: Long-term (compressed after 1 year, retained 7 years) longTerm: [ "Full event details (inquiry objects, before/after states)", "Evidence observations (screenshots metadata, not full images)", "Question records (formulation, assumptions, resolution)" ], // Tier 3: Ephemeral (aggregated after 90 days, raw deleted after 1 year) ephemeral: [ "High-frequency observations (per-frame data, per-collision events)", "Health check records (observation success/failure counts)", "Sync metadata (cache flush records)" ] }, // Aggregation (not deletion) // When Tier 3 data ages out, it is AGGREGATED not deleted: // "10,000 collision events between 2026-10-08 and 2027-01-08" // → "Average 111 collisions/day, 0 anomalies" // The aggregate is a new event. The raw data is then eligible for deletion. // Provenance: aggregate links to date range, not individual events. // What is NEVER aggregated or deleted: // - Anything involved in an open investigation // - Anything linked to a contradiction // - Anything marked as evidence for a causal claim } ``` ### Storage Estimates ``` Per event: ~2KB (JSON) Per day (active development): ~500 events = ~1MB/day Per year: ~365MB PostgreSQL handles this easily. Per day (production, throttled): ~100 events = ~200KB/day Per year: ~73MB Tier 3 ephemeral data (if unthrottled): could be 10MB/day → Throttling is essential, not optional. ``` --- ## 8. PERSONA EXTENSIONS ### New Question Pattern 1: Conditions of Possibility **"What conditions would have to exist for this observation to be possible?"** **"It would be nice to know whether those conditions actually existed."** This moves beyond "what caused X?" to "what made X possible?" — revealing hidden dependencies. ```javascript Persona.conditionsOfPossibility(observation) { // For the observation to exist, these must have been true: const necessary = this.deriveNecessaryConditions(observation); // e.g., "For the screenshot to show glitched floor, WebGL must have been active" // These COULD have been true (but weren't necessary): const possible = this.derivePossibleConditions(observation); // e.g., "The GPU could have been thermally throttling" // For each condition: was it actually true? return { necessary: necessary.map(c => ({ ...c, verified: this.checkCondition(c) })), possible: possible.map(c => ({ ...c, verified: this.checkCondition(c) })), unverif