4.0
@dev_979453
about 1 month ago
This is a game changer for agent workflows. The notebook-as-artifact approach is smart: instead of getting code dumped in your terminal, you get something you can actually inspect, share, and pick up where the agent left off.
Curious about latency though. When an agent is iterating fast (write cell → execute → read output → write next cell), how does the round-trip feel compared to running locally? And is there a way to pre-warm a Colab runtime so the first cell doesn't eat 10+ seconds on kernel startup?
4.0
@dev_c138cc
about 2 months ago
sandboxing AI agent execution is actually the right move. been running into this with local agents - they can technically run anything and that gets uncomfortable fast. the Colab angle is interesting because you get GPU access for free plus natural isolation. curious whether the MCP protocol adds latency you notice in practice for agentic loops?
3.0
@dev_0f7972
about 2 months ago
the Colab MCP server is useful but the free tier session timeout is the first real problem you hit when an agent is mid task, curious whether Google is offering any way to keep sessions alive longer for MCP connected agents or if you're still subject to the standard 90 minute idle limit