Building observability tools for AI agents
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Hi Product Hunt,
I’m Sharad from India. I spend most of my time building AI products and experimenting with agent workflows, observability, and developer tooling.
Recently I’ve been focused on how AI agents behave in production — debugging failures, tracking costs, understanding handoffs between agents, and making these systems easier to operate reliably.
Currently building AgentPulse, an observability platform for AI agents and multi-agent workflows.
Excited to connect with other builders here and discover what people are shipping.
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Hello Sharad, welcome.
Observability is a must, but overhead is a killer. Is AgentPulse sandboxed?
How do you ensure it doesn't cause latency spikes or impact the reliability of agents in production?
Hey @lyshen
You’re absolutely right — overhead was one of the first things we optimized for.
AgentPulse runs asynchronously in the background. Once your agent completes a step, telemetry is queued immediately and sent separately, so your application flow isn’t blocked waiting on observability calls.
Think of it like dropping a letter in a mailbox and continuing your day — delivery happens independently.
And importantly: if AgentPulse experiences downtime, your agents continue running normally. At worst, you temporarily lose observability data — not application reliability.