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Building Effective AI Agents

(www.anthropic.com)
543 points Anon84 | 1 comments | 17 Jun 25 17:50 UTC | HN request time: 0.217s | source
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AvAn12 ◴[17 Jun 25 19:54 UTC] No.44303213[source]▶
How do agents deal with task queueing, race conditions, and other issues arising from concurrency? I see lots of cool articles about building workflows of multiple agents - plus what feels like hand-waving around declaring an orchestrator agent to oversee the whole thing. And my mind goes to whether there needs to be some serious design considerations and clever glue code. Or does it all work automagically?
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1. gk1 ◴[17 Jun 25 20:31 UTC] No.44303611[source]▶
In at least the case for coding agents the emerging pattern is to have the agents use containers for isolating work and git for reviewing and merging that work neatly.

See for example the container use MCP which combines both: https://github.com/dagger/container-use

That’s for parallelizing coding work… I’m not sure about other kinds of work. I still see people using workflow builder tools like n8n, Zapier, and maybe CrewAI.