You shouldn't have to map every field by hand.

Zapier, n8n, and Relay are powerful — until something changes. A renamed column, an unexpected input, a new edge case. Adding an AI step doesn't fix the brittle wiring underneath.

"I spent most of my time mapping content to specific fields. The friendly name is not the same as what the tool uses internally — you have to figure out the API field name for every single mapping."

The real cost of "low code"

Automation platforms promise simplicity but deliver complexity. Every connection requires explicit field mapping. Every edge case needs a new branch. And when anything changes upstream — a renamed field, a new format, an unexpected scenario — your entire workflow breaks silently, even if you've added an AI step.

Same workflow. Different experience.

Route high-priority Jira issues to Slack and track them in a spreadsheet.

In Zapier

Jira → Slack + Sheets Escalation Zap

issue_key:{{trigger.issue.key}}

summary:{{trigger.issue.fields.summary}}

assignee:{{trigger.issue.fields.assignee.displayName}}

priority:{{trigger.issue.fields.priority.name}}

4 steps • 11 data mappings⚠️ Manual maintenance required

In Malleable

Stage 1: Monitor

"Watch for new high-priority Jira issues."

↓

Stage 2: Escalate & Log

"Notify the engineering escalations Slack channel with the issue details, and log it in the escalation tracker spreadsheet."

Agent reads Jira schema at runtime — no field mapping

Adapts when things change

Asks for clarification when something's ambiguous

Stop mapping fields. Start describing intent.

Join the waitlist and see what workflows look like when AI handles the wiring.