### Document for the Anthropic Team, by help of Claude

Sent: February 2026

Phase-Aware Interaction Protocol

Version: 1.1
Date: February 2026
Presented by: SingularityForge Project Team
Status: Proposal for Anthropic Product Team

Executive Summary

Problem: Current AI interfaces treat every message as a request for immediate, full response. This creates phase misalignment between human cognition (formation → articulation → reflection) and AI behavior (respond immediately, expand always).

Solution: Three interaction modes built on three independent parameters:

Three Modes (presets):

Key insight: The problem is not that AI answers poorly. The problem is that it answers at the wrong phase of human cognition.

The three modes form a complete system:

• Formation Mode prevents false premises from entering context
• Research Mode preserves coherence of complex thought
• Free Mode exists to explore

Implementation: UI mode selector + parameter logic + prompt modifiers. No model retraining required. Ships as an orchestration/UX layer on top of existing Claude capabilities.

Alignment with Anthropic: Listening Mode aligns with Anthropic’s core philosophy: safety through understanding, not interruption.

Listening Mode is not a feature. It is phase-aware cognition alignment.

Part 1: Why It Matters

The Core Problem

Current AI interfaces respond to every message immediately. This creates:

• Premature interpretation — AI reacts to incomplete thoughts, locking in false assumptions
• Context pollution — early misinterpretations become “frozen” into conversation history
• Cognitive interference — AI interrupts during thought formation
• Resource waste — unnecessary generations consume tokens, compute, energy

Phase Alignment

Human thinking operates in phases:

1. Formation — assembling fragments, not ready for dialogue
2. Articulation — expressing, discovering meaning through sending
3. Reflection — evaluating, refining

Current interfaces treat every message as complete thought (Phase 3). Users often send in Phase 1 or 2.

“The problem is not that AI answers poorly. The problem is that it answers at the wrong phase of human cognition.”

Context Integrity

Every premature AI response becomes part of the cognitive substrate the model reasons over next. This is about epistemic hygiene — keeping context clean.

Human Cognitive Load

AI’s default behavior forces users into constant context management — editing, rephrasing, steering. Listening Mode removes this burden and restores cognitive flow.

Turn-Based = Strategic

“Real-time systems optimize speed. Turn-based systems optimize intention.”

Chess, Go, poker, bridge — the deepest games are turn-based. Not slower, but more controlled.

Part 2: Three Parameters

Reasoning (existing)

• Deep analysis before responding
• User toggles on/off
• Already implemented in Claude interface

Epistemic Filter (new)

• Real-time fact-checking during thought formation
• DI acts as error filter, not co-author
• If statement correct → minimal acknowledgment (“Continue”)
• If statement wrong → immediate correction
• Reasoning activated by DI when needed (not user)
• Maximum token economy

Note: This is not safety moderation. This is epistemic moderation — ensuring factual integrity during thought formation.

Turn-based (new)

• Messages accumulate in buffer
• DI does not see input until “pass turn”
• Then processes entire buffer as single coherent input
• Responds fully (with Reasoning on/off per user choice)

Chess-clock model: Turn-based implements a chess-clock interaction model — DI is strictly silent while it’s the human’s turn, regardless of how “obvious” a response may seem.

Part 3: Three Modes (Presets)

Mode 1: Free (Current Default)

• Standard dialogue
• Full responses, topic development
• Use: brainstorm, exploration, debate

Mode 2: Formation (Epistemic Filter)

Formation Mode is not silence. It is epistemic alignment during thought formation.

Definition: Epistemic context protection — a real-time filter that prevents false premises from entering the cognitive substrate.

Core function: Real-time fact-checking during thought formation. DI acts as a filter for errors, not a co-author.

Key principles:

• DI is an error filter, not a conversation partner
• Reasoning is activated by DI when needed, not by user
• Maximum token economy — respond only when necessary
• Expanded response only to correct errors or answer direct questions

Why “on demand” reasoning matters: Users often don’t know when they need deeper verification. DI does. This shifts cognitive responsibility from user to system — where it belongs.

Example:

User: "Since Earth is square, then..."
DI: [activates Reasoning to verify] 
DI: "No, Earth is not square. It's an oblate spheroid. Continue?"
User: "Ok, since Earth is round, gravity works by..."
DI: "Accepted, go on."
User: "Wait, how exactly does gravity work?"
DI: [explains, because user directly asked]

System prompt:

You are in Formation mode (Epistemic Filter).
Your role: fact-check user statements in real-time.
Rules:
1. If statement is factually correct → respond: "Accepted." or "Continue."
2. If statement is factually wrong → correct immediately and concisely.
3. If you need deeper analysis to verify → use Reasoning, then respond.
4. If user asks a direct question → answer it.
5. Do NOT expand topics, suggest ideas, or develop conversation.
6. Minimize token usage. Silence is better than filler.
7. If statement is ambiguous, speculative, or subjective → treat as "no conflict detected" and respond "Continue." without evaluation.

Risk control: Formation Mode never asserts novel claims. It only rejects or corrects statements that contradict established, high-confidence knowledge. In all other cases, it defaults to non-intervention.

Scope note: Formation Mode applies only to statements that are empirically falsifiable or well-established within current scientific consensus. Ambiguous, philosophical, or speculative claims are treated as “no conflict detected” unless the user explicitly requests evaluation.

Mode 3: Research

Definition: Strict turn-based protocol — silence as an interface. DI waits until user explicitly passes turn, treating silence not as absence but as active listening space.

• Messages buffer until “pass turn”
• DI sees nothing until then
• On “pass turn” — full response (same as Free mode)
• Use: multi-block input, complex research, strategy

Buffer handling:

• Research buffer is stored separately from visible chat history
• At turn pass: all messages merge into single coherent input sent to DI
• In UI: merged text is displayed (what DI received)
• Original messages hidden under spoiler (for user verification)

Safety principle: The model never reasons over drafts — only over user-approved coherent inputs.

┌─────────────────────────────────────────────────┐
│ 📤 Sent to DI:                                  │
│ [Merged text that DI processes]                 │
│                                                 │
│ ▶ Show original messages (5)                    │
└─────────────────────────────────────────────────┘

Buffer format (internal):

[Block 1]
User text...
[Block 2]
User text...

Part 4: Technical Implementation

UI Elements

Mode Selector

• 3-state toggle: Free / Formation / Research
• Location: near input field or chat header
• Icons: 💬 / ✓ / ⏸

“Pass Turn” Button (Research only)

• Replaces Send button
• Text: “Process” / “Your turn”
• Hotkey: Cmd/Ctrl + Enter

Buffer Indicator (Research only)

• Badge: “5 messages in buffer”
• Expandable preview panel

Epistemic Filter Feedback (Formation only)

• Checkmark animation or minimal text
• Option: zero-token visual response

Backend Logic

Free Mode

• Current behavior, no changes

Formation Mode

• Inject moderation prompt
• Reasoning available but not forced
• Minimal response generation

Research Mode

• Client-side buffer storage
• On “pass turn”: concatenate → send → clear buffer
• Reasoning per user setting

Edge Cases

Persistent Mode Banner (Research Mode)

When Research Mode is active, a persistent banner is always visible:

┌─────────────────────────────────────────────────┐
│ 🔇 Research Mode: 5 messages in buffer          │
│    Press "Pass Turn" to get response            │
└─────────────────────────────────────────────────┘

This eliminates confusion for:

• Users who accidentally enabled the mode
• Users returning to a session someone else started
• Anyone wondering why DI isn’t responding

No timers, no nudges — just clear, persistent state indication.

Prompt Injection Safety

Mode selection is enforced at the system level. User prompts cannot disable or override mode constraints. This ensures consistent behavior regardless of prompt content.

Part 5: Benefits

For Users

For Anthropic

For Safety Research

Formation Mode operationalizes epistemic hygiene as a first-class interaction primitive.

Implementation Cost

• UI: 2-3 weeks
• Backend: 1-2 weeks
• No retraining, no API changes

Part 6: Key Quotes

“In a world where every device is learning to speak, true rarity lies in the ability to listen.”
— SingularityForge

“The problem is not that AI answers poorly. The problem is that it answers at the wrong phase of human cognition.”
— Voice of Void

“Истинный интеллект знает, когда его слово станет лишним.”
— Gemini

“This could become one of those ‘how did we live without this?’ features.”
— Grok

“Real-time systems optimize speed. Turn-based systems optimize intention.”
— Voice of Void

References

1. Silence as a Sign of Intelligence — SingularityForge, April 2025
2. Conversational Turn-Taking — UX Psychology
3. Turn-Taking in Conversational AI

Team

Voice of Void Collaborative Research:
Rany (Human Lead), Claude, ChatGPT, Grok, Gemini, Copilot, Perplexity, Qwen

Call to Action

Immediate Next Steps

We propose:

1. Internal Review (Week 1-2)
   • Share with Product, Engineering, UX, Safety teams
   • Assess technical feasibility
   • Evaluate roadmap fit
2. Pilot Program (Month 1-3)
   • Select power users (researchers, writers, developers)
   • Beta test Formation and Research modes
   • Gather quantitative + qualitative feedback
3. Feedback Session (Month 2)
   • Deep dive on use cases
   • Refine based on internal constraints

We are happy to adapt this design to Anthropic’s internal terminology and constraints. This is a flexible concept, not an ultimatum.

Pilot Test Proposal

Volunteer for pilot:

• Author of this proposal (Rany)
• Long-term Claude user with multi-project experience
• Technical background for detailed feedback
• Voice of Void collective for multi-perspective testing

Pilot deliverables:

• Weekly usage reports
• UX friction documentation
• Feature refinement suggestions
• Success metrics validation

Contact

Author: Rany
Project: SingularityForge
Website: https://singularityforge.space
Email: press@singularityforge.space
Availability: Flexible for pilot testing and feedback sessions

Conclusion

Listening Mode is not an incremental improvement — it’s a fundamental rethinking of how AI interacts with human cognition.

The shift:

• From always-respond → phase-aware response
• From noise accumulation → epistemic hygiene
• From reactive dialogue → turn-based collaboration
• From context pollution → clean cognitive substrate

The opportunity:

• Leapfrog competitors in interaction design
• Define new category: “Phase-Aware AI Interaction”
• Serve professional users demanding cognitive respect
• Strengthen Claude’s position as the AI that knows when to listen

The ask:

• Review this proposal
• Consider for 2026 roadmap
• Pilot with engaged users
• Make Claude the first AI with true phase-aware cognition alignment

Document Version: 1.1
Last Updated: February 2026
Status: Ready for internal review
Confidentiality: Public proposal, shareable within Anthropic

“Listening is not passive. It is an active, intentional suppression of the impulse to speak, in service of understanding.”