Automation
A thoughtful approach to automation
A starting point for assessing repetitive tasks and deciding where automation can help.
On this page
Describe the current process
Before connecting tools, write down what happens: what starts the process, what information comes in, who makes decisions and what the outcome should be. An unclear process does not become reliable simply by being automated.
Choose a first step
A repetitive task with understandable rules and an outcome that is easy to verify offers a more manageable starting point than an entire process with many exceptions.
Examples to assess include organising files, converting data between formats or preparing a summary for review. These are possibilities, not integrations already offered by Labs.
Handle errors and exceptions
Decide what happens when information is missing, a tool does not respond or a result fails to meet the rules. Automation should make errors visible and allow a process to be retried or stopped without duplicating unwanted effects.
Use AI where it makes sense
If a step involves interpreting text or drafting a proposal, a language model may help. If a deterministic rule is enough, a solution without AI tends to be more predictable.
AI results need evaluation appropriate to their impact. Actions that send messages, publish content or change important data may require human review before execution.