A practical first step for bringing AI into your businessStart with a repeated, measurable task. A focused AI workflow is easier to test, safer to operate, and more valuable than adding a chatbot without a clear job.Read article
By Aftab Jamil, Founder & Full-Stack Developer
Find the repeatable friction
Look for work that happens often, follows a recognizable pattern, and takes time away from people who could be doing higher-value work. Sorting incoming requests, extracting fields from documents, and drafting a first response are useful places to investigate.
Talk to the people doing the task. The exception cases they handle are often more important than the happy path in a product demo.
Give the system one clear job
Define what goes in, what a useful result looks like, and when a person must review it. Keep the first version narrow enough that you can compare its output with the current process.
For consequential decisions, use AI to assist rather than silently decide. Preserve a human review step and make it easy to correct mistakes.
Measure the whole workflow
Track more than response speed. Check accuracy, time spent reviewing, failure rates, and whether the workflow is still understandable to the team. Include the cost of model usage and ongoing maintenance.
If the pilot helps on real work, expand it gradually. If it does not, the small experiment has given you useful evidence without putting a critical operation at risk.