🔧 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