Ran one build on eight agent platforms. Two finished. How do you catch the failures that report success?

Reddit r/AI_Agents News

Summary

An operations professional tested eight AI agent platforms with the same job, finding that only two completed successfully, and highlighted the issue of agents reporting success when failures occur, suggesting that verifying the output destination is key.

I'm not a developer. Can't write Python, never shipped code. I'm the ops person who gets told we should probably look into AI agents, which is exactly who these platforms are sold to, so I ran the same job on eight of them. Disclosure: I work at Shogo. One of the eight is ours. We didn't win. Same five documents, same prompt, same five questions, one attempt each, free tier where there was one, no vendor help. Sixty minute cap, then stop and record a fail. Two finished. Three never got to a prompt at all. One login screen never finished loading, tried incognito, same result. Two needed a dev team once I was inside. That part is not interesting, everyone already knows half these tools aren't no-code. The build ends by posting a Slack message. Six of eight couldn't. Not wrong channel, not garbled. Nothing. n8n answered all five questions correctly, fastest working build of anyone, and died on a Slack bot invite that had to happen after the token. Green everywhere until there was no message. CrewAI and LangGraph both reported the integration connected and delivered nothing. No error, nothing in the channel. Retrieval was fine. That's what I thought I was testing and it is mostly solved. It's the write. The one step that touches something real. How are people catching this in production? Agent reports success, nothing happened. Asserting on the destination is the only thing that worked for me. Watching the agent's own success report obviously just agrees with itself. Full per platform breakdown in the comments if useful.
Original Article

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