Many automation efforts fail because nobody really understands the task in enough detail. People jump straight to tools and agents and try to automate based on assumptions. A hands-on, “manual first” approach starts from how the work is actually done in real life and gives you both learning and documentation before you automate anything.

Start by doing the task that should be automated manually several times. Click through the systems, fill out the forms, send the messages, move the files. If you cannot do it yourself, do it together with someone who has the domain expertise. Ask them to talk through what they are doing and why at each step. This is how you uncover the small rules and decisions that are usually not written down anywhere.

While you perform the task, write down the details of what is done, step by step. For each step, note what you look at, what you decide, and what the result is. Capture which tools or systems are used and who is involved. Do not worry about perfect structure at this point; focus on capturing what actually happens.

Then look at which variations of the task can occur. Real processes are rarely linear. Identify different paths: what happens if something is missing, delayed, in the wrong format, or unusual? List these variations and try each one manually at least once. This shows you how the process changes and which conditions and branches exist.

The result of this work is both learning and documentation. You get a clearer understanding of what needs to be done and a written description of what is done and how it is done. You can turn your notes into a simple description, checklist, or flow with the key steps, decision points, rules, and exceptions. If you worked with a domain expert, review this together and adjust it until it matches reality.

The next step is to identify what can be automated. Go through the documented process and separate repetitive, rule-based steps from judgment-heavy or unclear steps. Some parts are good candidates for full automation, some are better suited for human-in-the-loop, and some are not worth automating at all. How the automation should be solved must be evaluated based on the concrete task: sometimes a simple script or integration is enough, other times you might use a workflow tool or a language model or agent to assist with unstructured parts like text or documents.

By starting with manual execution, detailed notes, and explicit variations, you avoid automating based on guesswork. You build automation on a solid understanding of the real process, which makes the result more robust, useful, and easier to improve over time.