My AI Workflow Was a Mess. Here's What I Did About It.

My AI Workflow Was a Mess. Here's What I Did About It.

Let me tell you about a Tuesday afternoon that broke me a little.

I had a great idea for an automation. Clear in my head. Simple enough. I opened an AI agent, typed out what I needed, and started building.

Forty minutes later, the agent had confidently edited the wrong folder, drafted a "polished" version of something I hadn't approved, and treated a private project note like it was ready to publish.

Nothing was broken beyond repair. But nothing was right either.

And the worst part? I had done this to myself.

The Real Problem Nobody Talks About

Everyone's talking about which AI model is smarter. Which agent framework is faster. Which tool connects to which API.

Nobody's talking about the mess that lives around the AI.

The scattered notes. The half-finished prompts. The browser tab with the actual setting you need. The project folder that made sense three weeks ago and is now a mystery box.

When your context is scattered, even a brilliant AI agent will confidently do the wrong thing.

I kept bumping into the same four failure points:

The agent didn't know what the project actually was. So it guessed. Badly.

There were no rules about what it could touch. So it touched everything.

Draft and published files lived in the same folder. So it treated rough ideas like finished work.

There was no clear next step. So every session started by rediscovering the same things I figured out last time.

Sound familiar?

What I Tried First (And Why It Didn't Work)

My first instinct was the wrong one: write a bigger, longer, more detailed prompt.

More context. More instructions. More words.

What I got was more confusion with better grammar.

The problem was never the prompt. The problem was that I was trying to fix a system problem with a sentence solution.

The Shift That Actually Helped

Here's the thing I finally understood:

An AI agent is only as organised as the project around it.

So I stopped trying to explain everything in a single prompt. I started leaving trails.

A simple project file that answers the questions every AI agent will eventually ask:

What is this project, in one sentence? Which folders matter, and which ones don't? What can the agent do without asking me? What needs approval? What does done actually look like here? What's the very next step?

I started calling this file AGENTS.md. It's not fancy. It's not long. But it changed how every session started.

Instead of re-explaining everything from scratch, I could say: read the project file first. And the agent could actually follow a workflow instead of inventing one.

The sessions got calmer. The outputs got closer to what I actually needed. I stopped losing the thread between ideas and shipped projects.

One Thing You Can Do Today

If your AI workflow keeps going sideways, don't reach for a new tool.

Open a blank file in your current project and write five things:

Save it as README.md or AGENTS.md or whatever makes sense to you.

That one file is worth more than any prompt hack or model upgrade.

A Quick Checklist Before Your Next AI Session

Run through this before asking an agent to work on anything real:

☐ Is there a one-sentence description of the project?
☐ Are the key folders named and explained?
☐ Are draft, approved, and published files in separate places?
☐ Are approval rules written somewhere the agent can read?
☐ Is there a do not touch list?
☐ Is the next action obvious?
☐ Is there a way to verify the work before calling it done?

If you can check all of those, your next session will be a different experience.

Before You Go — I Want to Hear From You

Where does your AI workflow actually break down?

Is it context? Too many half-started ideas? Approval rules that live only in your head? Automation that moves faster than your thinking? That last 10% before something is actually done?

Reply and tell me the one place your builder workflow keeps falling apart.

I'm collecting real workflow problems for upcoming issues — and if yours is a common one, I'll write the whole next issue around it.

What DevSan Dispatch Is

This is a practical newsletter about building with AI agents — the honest version, not the highlight reel.

Each issue is a real problem, the messy attempt, what finally worked, and something concrete you can use. Checklists, small playbooks, prompts, and project patterns from actual builds.

No AI news roundups. No hype. Just the working log, cleaned up and made useful.

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