I Stopped Using AI for Individual Steps and Started Giving It the Whole Task

pierre — Thu, 03 Sep 2026 02:46:22 +0000

Most of my AI workflows have been surprisingly manual.

Ask ChatGPT something.

Copy the answer.

Open another tool.

Search for additional information.

Paste everything into a document.

Ask AI to restructure it.

Repeat.

AI made individual steps faster, but I was still the workflow engine connecting everything together.

Recently I tried a different approach with NoteGPT’s AI Agent.

Instead of asking it to complete one step, I gave it the end goal.

For example:

Research five competing products, find their recent updates, compare their features and positioning, and produce a structured report.

The agent breaks that goal into smaller tasks, decides which tools it needs, browses the web, processes the information, and combines the results into a final deliverable.

That’s a subtle but important difference.

Chat vs. delegation

A normal AI conversation usually looks like this:

User → prompt → response → next prompt → response → next prompt.

An agent workflow looks closer to:

User → goal → plan → tools → execution → result.

You’re moving some of the orchestration away from yourself.

I found this especially useful for tasks involving several different operations: research, summarization, comparison, writing and formatting.

No agent framework required

The other thing I appreciated was the lack of setup.

I’ve experimented with agent frameworks before, and many of them quickly turn into a project of their own.

Environment variables.

API keys.

Model configuration.

Tool definitions.

Workflow logic.

Debugging.

That flexibility is great when you need it, but sometimes I just want to delegate a task.

NoteGPT takes the opposite approach. It runs in the browser, requires no code or API key, and lets you switch between 20+ models including GPT, Claude, Gemini and DeepSeek.

There are also predefined skills for common workflows such as Deep Research, AI Documents, AI Slides, AI Sheets and Data Analysis.

Where I think this is useful

I wouldn’t hand an agent an important task and blindly trust the output.

Research still needs verification. Code still needs testing. Anything involving financial, legal or medical decisions obviously needs proper human review.

But there’s a large category of boring work where the cost isn’t intelligence — it’s coordination.

Finding information.

Moving information.

Restructuring information.

Turning it into another format.

That’s where agents are starting to make sense to me.

Instead of making each individual step 30% faster, they can sometimes remove several steps entirely.

NoteGPT’s AI Agent is free to start if you want to experiment with this workflow:

notegpt.io/ai-agent

The question I’m increasingly asking myself isn’t “Can AI answer this?”

It’s:

“Can I stop doing this workflow manually?”

DEV Community: pierre

I Stopped Using AI for Individual Steps and Started Giving It the Whole Task