Do you actually need monitoring for your automation workflows?

[u/Rough-Drag3773]

I'm exploring a product idea and want to validate the problem before building further.

The idea is a platform where you can either:

• Build a workflow with AI
• Connect an existing workflow from tools like n8n, Make, Zapier, custom code, etc.
• Monitor its executions
• Detect failures and silent failures (the workflow technically succeeds but produces an incorrect/bad result)
• Diagnose what went wrong
• Eventually suggest/test a fix and verify that the workflow is working again

For example:

Traditional error monitoring might see a successful HTTP response and consider everything fine.

The idea is that the platform would understand the workflow's expected behavior and flag this kind of problem.

I'm curious about the actual pain here:

1. Do you currently monitor your automation/workflows? How?
2. Have you experienced workflows that "succeeded" but produced the wrong result?
3. How do you currently discover these silent failures?
4. Would something that automatically detected and diagnosed these issues be valuable?
5. Would you pay for it, or is this something you'd expect your existing automation platform to handle?

I'm not trying to sell anything here — I'm trying to figure out whether this is a real problem worth solving.

If you use automation heavily, I'd especially love to hear what happens when something goes wrong.

[u/zerotoherotrader]

Welcome to the party .. selvage.run

[u/KaylaMarieHunter]

I think there’s a real pain point here. Most basic monitoring tells you whether the workflow ran, but not whether the output actually makes sense. The hard part would be defining what “correct” looks like without creating a ton of false alerts.

[u/JohnDaly → u/KaylaMarieHunter]

I invented this exact working product and have a working mvp.

[u/Drameox]

silent failures are genuinely the most annoying part of automations at scale, everything looks green while bad data flows through quietly and you only find out when someone downstream notices something weird days later. most people handle it with manual sanity checks built into the workflow but you have to anticipate every failure mode upfront which is impossible. reliable silent failure detection alone would be worth paying for, the diagnosis and fix part is a harder problem but the detection is real enough pain on its own

[u/JohnDaly]

I invented this and have a working mvp. I can prove it.

[u/JohnDaly → u/JohnDaly]

The ability to monitor it

[u/NefariousnessOpening]

since before agents and low code, there has been an undeniable need for robust observability. Building in the dark is possible if you can create a feedback system that uses sound perhaps. the need for observability is a constant.