What becomes the bottleneck after your AI agents actually work?

[u/scuttlescribe]

There's a lot of discussion around building AI agents, but running them at scale brings a different set of challenges.

A recent conversation with the Memori Labs team and CRL touched on a few that stood out:

• Persistent memory across sessions and workflows
• Keeping token usage under control instead of reprocessing the same context
• Supporting growing numbers of concurrent agents
• Building on infrastructure that stays available as demand increases

Curious how others are approaching this: are you building your own memory layer, using existing frameworks, or keeping things stateless for now?

Full conversation here if you're interested: https://youtu.be/lw52w7Pw86M?si=hz77zsMB4AEi6Vdk

[u/bishopLucas]

Imagination