Blog
Analogies and real architecture behind building AI agents with Wetel.
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Workspace owner or member: who can do what?
Every person in a Wetel workspace is either an owner or a member. Members can build; only owners can decide approvals and hire a role. Here is the full list, how an owner is set, and what is not built yet.
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How do I try a workflow safely before customers see it?
Run your edits as a draft in a test session without publishing them, simulate each approval outcome, then read the run record. What a draft test does, what it does not do, and a short checklist before you publish.
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Screening job applicants with an AI employee: what it does, step by step, and where people decide
A walkthrough of the two documented ways to build an applicant-screening AI employee in Wetel: a scored first-round interview, and a messaging-app intake that collects a résumé and files it in your applicant tracking system. Plus what happens when a file is missing or wrong, and why a person still makes the hiring decision.
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Hiring a ready-made role instead of building an AI employee from scratch
A role template is an AI role with the job description already written: a persona, a conversation flow, knowledge and the connections it needs. Here is what hiring one in Wetel means today, who can do it, what you still set up yourself, and what is not built yet.
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An AI employee that starts on its own: scheduled work, and what stops it running away
How a scheduled workflow lets an AI employee do the Monday report without being asked, the three limits that keep it from spending or failing without end, and how to check on it, since it does not send an alert when it stops.
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Reverse engineering is now a commodity: what REA means for platforms like Wetel
REA gives AI agents a standardized interface to drive Ghidra, Hopper, and IDA. It can extract your frontend widgets and GraphQL schema in hours. It cannot touch your workflow engine, connector logic, or auth layer. Here's where the real moat lives.