AI agents need tasks instead of long instructions

I have noticed that asking an AI agent to finish an entire business workflow often creates more work than expected. The AI agent may finish most of the work. Can miss an important step.

I get results when I split the workflow into smaller jobs. For example a research AI agent can collect competitor pricing another AI agent can organize the findings and a final AI agent can prepare a comparison, for review.

Each step needs a definition of success. The instruction "Research competitors" is too broad. The instruction "Find pricing pages for five named competitors and record their public monthly plans" gives the AI agent something specific to complete.

I also decide which actions need approval. Collecting information may need little supervision but sending emails, changing customer records or making purchases should have stronger checks.

It helps to test the workflow on a sample before running it at scale. Five records can reveal fields, incorrect assumptions and duplicated results without creating a large cleanup job.

My takeaway: Start with one task define the expected output and add approval points where mistakes matter. If you use AI agents, which part of your workflow would you automate first?