bug reportProductivity · Automation & WorkflowsstructuralWorkflowsReliability

Monday.com automations are unreliable and silently change behavior

Monday.com users report that workflow automations are incomplete and unreliable, sometimes changing without notice, undermining trust in the platforms automation features.

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3.9

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Similar Problems

surfaced semantically
Productivity92% match

monday.com Work Platform Crashes and Glitches Disrupt Workflows

Users report that the monday.com AI Work Platform crashes frequently and experiences glitches that interrupt daily workflows. This reliability issue undermines trust in the platform for critical project management.

Productivity91% match

Monday.com automations occasionally fire with significant delays

A user reports that Monday.com automations sometimes execute with noticeable delays, disrupting time-sensitive workflow triggers. The issue is acknowledged as intermittent and rated as acceptable by the user. No specific automation types or frequency of delay are described.

Productivity91% match

Monday.com Advanced Automations Are Hard to Learn and Expensive to Unlock

Users of a project management AI work platform find advanced automation features difficult to understand without guidance and describe the associated pricing tiers as costly, leading them to want more guided tutorials, ready-made automation templates, and more affordable access.

Productivity90% match

Workflow Automations Silently Deactivate With No Explanation

Users of project management platforms like Monday.com find their automations mysteriously deactivated with no notification or reason provided, causing business processes to silently fail. The lack of observability and reliability in no-code automation platforms is a recurring pain point across tools.

Productivity90% match

AI Features in Work Platforms Lack Predictability and Require Manual Verification

Users of AI-powered work platforms like Monday.com find that AI features still require refinement, especially around predictability and consistency of outputs. Complex tasks generated by AI often need manual verification and correction, preventing full automation trust.

Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.