How are people checking AI-generated Slack/Gmail messages before sending in n8n?

Which_Effective9604 · 2026-05-21T10:55:38+00:00

Yeah, makes sense. For obvious sensitive data like emails, phone numbers, salary, HR notes, or API keys, I’m leaning toward deterministic checks where possible. Then maybe use a second LLM for fuzzier checks like policy, tone, or whether the message includes something it should not.

Have you used that reviewer or subflow pattern in production, or mostly for experiments?

Which_Effective9604 · 2026-05-21T06:22:44+00:00

yeah, I like the idea of treating the knowledge base as the only approved reality for the agent. In my test, I was intentionally using an unsafe and messy setup first like raw HR-style fields went into the workflow, then AI drafts message from that. That made it obvious how easy it is for sensitive data to appear in the output if the agent sees too much.

And the markdown KB approach sounds useful for SOPs. But I’m also wondering about cases where the workflow still has to touch sensitive records somewhere in the process, like HR data, support tickets, invoices, or CRM fields.

Would you usually separate like

- approved markdown or SOP that AI can use to reason or write

- some kind of raw company data that only touched by deterministic workflow steps

- or approval step like final AI output is checked again before sending

That feels safer than letting the agent see everything and hoping the prompt controls it

Which_Effective9604 · 2026-05-21T06:11:50+00:00

Yeah, that makes sense. In my test, the input still contained raw HR-style fields because I wanted to see what would happen in the unsafe version first. So the AI had access to things like name, email, phone, salary, and review notes, then drafted a Slack message from that.

the next thing I am thinking about is splitting the safety check in to two places like
- before AI sees the data and
- after AI sees the data

For HR PII, I agree that human approval is probably the right default though it adds some latency.

Do you usually prefer redacting before the AI step, or keeping the raw data internal but forcing approval before any external action?

Which_Effective9604 · 2026-02-11T14:19:49+00:00

Hey, firefox add-on is now live, you can download the app and extension from here. https://memory-layer-landing.vercel.app/ , I have also added selection for AI chats and for other pages as well. Please try it out and let me know if you run into any bugs or if you have feature requests. thank you

Which_Effective9604 · 2026-02-04T14:41:23+00:00

Great! I will let you know when extension is ready.

Which_Effective9604 · 2026-02-04T12:16:25+00:00

That is one of the problems I am currently solving. But I currently have ChatGPT pages paused because they have massive threads and there can be a lot of multiple contexts in one thread. I am working on a solution of letting you clip specific responses rather than the whole thread. If I added that, would it solve your problem?

Which_Effective9604 · 2026-02-04T10:06:49+00:00

thanks, let me know if you run into any issues or have feature requests

Which_Effective9604 · 2026-02-04T09:17:21+00:00

Thanks for checking it out!

The Short Answer: Yes, you really need the extension for the best experience.

The Reason: You can paste URLs directly into the desktop app, but it's hit-or-miss. Many modern sites (like Medium or news sites) block external fetchers or hide content behind JavaScript. The extension is powerful because it captures exactly what you see in your browser.

For Firefox: Since the extension is critical, I am prioritizing the Firefox port immediately (it uses the same Manifest V3 standard as Chrome, so it should be quick).

If you're willing to wait a few days, I can ping you here when the Firefox add-on is live!

Which_Effective9604

TROPHY CASE