AI & Machine Learning

Automation Patterns That Survive Real Teams

1m & 4 s read212 views0 listens

The article provides valuable insights into designing robust and effective automations in monday.com (or similar project management tools) by focusing on practical business operations rather than ideal theoretical processes. Here’s a summary of the key points:

Key Principles

  1. Build for Reality, Not Theory: Automations should handle how the business actually operates, including exceptions and human errors.
  2. Reduce Admin, Don't Replace Judgment: Automate repetitive tasks to reduce administrative burden but avoid automating decisions that require human judgment.

Patterns and Best Practices

1. Handle Predictable Cases Cleanly

  • Use automations for predictable state transitions (e.g., moving deals from "Won" to "Closed - Won").
  • Push context across boards (e.g., creating a project on the delivery board when a deal is won).

2. Route Exceptions to Humans

  • Flag and notify humans when exceptions or judgement calls are needed.
  • For example, if a deal has been in "Proposal Sent" for over two weeks without progress, flag it as "Stalled" and alert the deal owner.

3. Avoid Overly Clever Automations

  • Start with basic automations to handle common cases and refine them based on real-world

Read the full article at DEV Community


Want to create content about this topic? Use Nemati AI tools to generate articles, social posts, and more.

Views212
On this page
Ali Nemati
Ali NematiBlogUI.author_articles
BlogUI.view_profile