Show HN: Why delegation beats memory in AI Agents(getseer.dev)

1 pointsby akshay3267 เดือนที่ผ่านมา1 comments

Show HN: Why delegation beats memory in AI Agents

https://www.getseer.dev/blogs/lessons-dec-2025

We've spent the last 6 months building Seer, an agent engine for enterprise workflows. We’re launching on NYE, but honestly, we’re still in the trenches.

While scanning the space, I keep seeing devs (us included, initially) get obsessed with complex "memory" layers and graph-based reflection. In practice, we found they mostly lead to context poisoning and high latency.

We pivoted to a "Barbell Strategy": Crisp, lean inter-agent instructions paired with massive, localized "artifact" context for sub-agents that are immediately killed after the task.

I’m curious—for those of you building agents in production:

Have you found a way to make "long-term memory" actually reliable, or are you also moving toward ephemeral, specialized agents?

What’s the "boring" plumbing problem (Auth, state rollback, etc.) that took you way longer to solve than the actual AI logic?

2 comments

austinbaggio6 เดือนที่ผ่านมา

How are you storing the agent context now?

Agent_Builder7 เดือนที่ผ่านมา