🔧 The Core Problem (Mechanism) • AI chatbots operate within a finite context window; a hard token limit on what the model can see at any given moment. • Once a thread exceeds this, the system uses a sliding window that silently discards older messages. • This causes the AI to lose earlier logic and begin confabulating. • Users experience this as the AI “getting dumber,” but it is actually losing visibility into prior reasoning. 🧠 Why Current Workarounds Fail • Requesting summaries • Copy-pasting into new threads • Using external tools These are all: • Manual • Friction-heavy • Lossy • Destructive to tone, persona calibration, and accumulated conversational context (the “vibe”) ⸻ 🚀 Proposed Feature: Context Preservation Gateway Trigger Condition • When thread token usage reaches ~80% of the model’s context window • Display a proactive warning (not a hard stop) ⸻ 🧭 Modal Flow (UX) ⚠️ Context Capacity Warning This conversation is approaching memory limits. Performance may degrade soon. Available actions: 📥 Export Full Thread • Formats: Markdown, JSON, PDF 🗜️ Compact and Continue • AI generates a summary • Raw history is purged • User may specify what to preserve ➡️ Start Fresh Thread with Context Seed • New thread • Summary auto-injected Optional setting: ☐ Don’t show again for this thread ⸻ ✨ Key Differentiators vs Existing Compaction OpenAI approach: • Silent compaction • No export • Binary choice • AI-only summarization This proposal: • Proactive warning with agency • Export before data loss • Tiered options: export, compact, branch • User-guided selective preservation ⸻ 🧩 Addendum: User-Directed Preservation Instructions 🚨 Problem with AI-Only Summarization • AI prioritizes statistical salience (recent + frequent info) • Critical constraints often appear only once • These get dropped despite being essential Examples: • “Never use semicolons in code.” • “My boss’s name is Mark, not Michael.” • “All outputs must follow ISO date format.” ⸻ 🛠️ Proposed Enhancement Add an optional text input during compaction: 🗜️ Compact and Continue The AI will summarize this thread and continue from the summary. Key details to preserve (optional): [ Project deadline is March 15 ] [ API uses OAuth2 ] [ Tone should remain casual ] These instructions will be injected into the summarization prompt. Buttons: Cancel Compact Now ⸻ ⚙️ Technical Implementation Preservation instructions are prepended to the summarization prompt: System: Summarize this conversation for continuity. Mandatory preservation: user input Include all items above verbatim in the summary. Result: • User controls what survives • Deterministic preservation • Reduced hallucination risk • Trust-centered architecture ⸻ 📈 Strategic Leverage (Why Build This) 1. 🏆 Competitive Moat • Claude + ChatGPT users complain about losing long threads • Graceful degradation + export becomes a visible differentiator 2. 🔒 User Lock-In via Data Gravity • Export formats (especially JSON + metadata) • Enables re-import → platform stickiness 3. 🧯 Reduced Support Load • Prevents the “Why did my AI get dumb?” churn trigger 4. 💸 Infrastructure Cost Reduction (Win-Win) Mechanism: • Long contexts require large KV caches • KV cache scales linearly with token count • GPU memory usage balloons with long threads Compaction impact: • Old KV cache invalidated • Smaller fresh cache built • GPU memory freed Strategic framing: • Users get better performance • Platform reduces inference costs • Incentives are structurally aligned ⸻ 📊 Summary of Improvements • Proactive warning → User: no surprise degradation → Platform: fewer support tickets • Export before purge → User: data ownership + continuity → Platform: format-based lock-in • Preservation field → User: critical constraints survive → Platform: higher satisfaction • Compaction itself → User: restored performance → Platform: lower GPU load
