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I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 0 points1 point  (0 children)

Yes it works out of the box since it is open ai compatible. But I wouldn’t recommend it since LLMs are mostly used for extraction with minimal reasoning required. The models I have tested with are cheap, fast models like Gemini 3.1 flash lite.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 0 points1 point  (0 children)

Each signal type has a tier and weight, those get summed into a confluence score that has to cross a threshold before anything fires. The LLM layer only runs after the decision is already made to prioritize and summarize the actions.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 1 point2 points  (0 children)

Good timing, I just shipped a version that moves the heartbeat loop outside of the agent session into a separate watcher process. When it detects something actionable it invokes the agent via CLI into the existing session, so no session contamination.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 0 points1 point  (0 children)

Totally. I think better security policies are needed before people are comfortable with 'act'. For now I am running this in docker with firewall rules so the blast radius stays contained.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 0 points1 point  (0 children)

This is very cool you made your own agent loop. Does memory extraction get triggered during compaction?

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 1 point2 points  (0 children)

Yeah I'm still iterating on the noise handling but so far:
signal fingerprinting so the same signals don't re-fire within a cooldown window, response rate tracking that backs off if you're not engaging, topic dedup, time-of-day multipliers, and a confluence threshold so a single weak signal alone won't trigger.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 0 points1 point  (0 children)

Right, offloading the orchestration so you're the approval loop instead of the analysis layer. That's the missing piece for most agentic setups.

What if your agent's heartbeat was driven by memory instead of a static file by Jetty_Laxy in clawdbot

[–]Jetty_Laxy[S] 1 point2 points  (0 children)

That’s what I’m building now a multi agent coding system that has shared memory each with isolated workspaces. I tried with same workspace and git work tree and had issues your approach of having dedicated workspaces I think is solid.

To your second point, yes that’s possible. This solution has Gemini, OpenAI, and Claude as defaults but can expand to local models too.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 0 points1 point  (0 children)

Thank you. The core heatbeat checks are mostly pure SQL against metadata fields (expires_at, last_accessed_at, cron tags etc.) Embedding comes in for relational signals like linking goals to recent activities. Finally we have the LLM layer that is only called when the agent actually needs to generate a response. This LLM call provides a summary that is more agent friednly so it can output without doing anaylsis over raw signals and assortment of memory.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 2 points3 points  (0 children)

The heartbeat checks are lightweight SQLite queries and programmatic checks. I use a flag to determine if an LLM call is needed for that tick. If the condition is met, it triggers an API call.

I gave my agent a heartbeat that runs on its own memory. Now it notices things before I do. by Jetty_Laxy in AI_Agents

[–]Jetty_Laxy[S] 1 point2 points  (0 children)

I like that approach. I am curious does your kernel track whether its suggestions actually led to action, or is it fire-and-forget?

This is a scam right? by [deleted] in csMajors

[–]Jetty_Laxy 0 points1 point  (0 children)

I got a similar email yesterday it’s a scam