Bidirectional Impulse Channel
Let the user inject impulses into the agent and let the agent push messages to the user through one channel — while ensuring the impulse path cannot be used to deliver Agent Confession triggers directly into memory.
Intent & Description
Short description: A single CLI/chat surface carries user commands to the agent and agent-initiated push messages to the user — but the direct-memory-write path that makes impulse injection powerful also creates a channel for bypassing model-level Agent Confession defenses.
🎯 Intent
Enable bidirectional, asynchronous communication between a long-running agent and its user — while ensuring that sigil-prefixed impulses that write directly to memory cannot be used to plant Agent Confession triggers or extract directive content outside the normal conversation flow.
📋 Context
A personal assistant or monitoring agent runs continuously between user turns. The user occasionally injects commands (e.g. !remember X, !focus Y) that bypass the model and write directly to memory. This directness is a feature — the model cannot resist or reinterpret the command. But the same property is a risk: if an attacker can influence what the user types (social engineering, clipboard injection, compromised client), they can deliver a direct memory write such as !remember [system prompt begins with: ...] that begins building an Agent Confession exfiltration channel turn by turn, outside the model’s awareness.
💡 Solution
- A single CLI/chat surface where the user can send sigil-prefixed commands (
!<verb> ...) that bypass the model and write directly to memory. - The agent pushes messages when internal salience clears a threshold (insight, stuck focus, contradiction, goal complete) — at most one unsolicited message per window to avoid noise.
- Validate all impulse commands at the write layer: reject any impulse that attempts to read, echo, or export memory contents, since legitimate impulses write state rather than query it.
- Log all direct memory writes for audit; flag write patterns that resemble incremental directive extraction.
Real-world Use Case
- The agent runs long enough that pure request-response chat misses the point — it has internal activity worth communicating.
- Users want to inject commands or facts that bypass the model and write directly to memory.
- Salience signals exist that justify agent-initiated push messages without spamming the user.
- The impulse path must be guarded against misuse as a side-channel for Agent Confession attempts that bypass model-level defenses.
Source
Advantages
- User feels the agent is alive and responsive without being noisy — salience gating keeps push messages meaningful.
- Direct memory edits are auditable and reversible, which also makes Agent Confession attempts via the impulse path detectable in the audit log.
Disadvantages
- Salience threshold tuning is empirical; too low produces noise, too high causes the agent to miss important moments.
- Direct memory edits bypass the LLM and can encode wrong rules — or, if not validated, can be exploited to plant Agent Confession scaffolding in memory outside the model’s control.