Storyboard AI Workflow

Research. Plan. Execute. Test.

The only AI workflow that works. Four steps, in order, every time. Research gives the model better input. Planning activates its reasoning. Execution uses its generation strength. Testing catches errors. Based on the article from The Human Algorithm.

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April 12, 2026

rpet-featured - MsTimaj AI Education Platform

The only AI workflow that works. A four-step framework for getting real results from AI, whether you are building software, creating content, or solving business problems. Based on the article from The Human Algorithm by Fatima Jalloh.

AI Workflow

Research. Plan. Execute. Test.

The only AI workflow that works. Four steps, in order, every time. It does not matter what tool you use. Claude, ChatGPT, Gemini. It matters how you think. Based on the article by Fatima Jalloh in The Human Algorithm.

The Problem

Most people skip straight to "make me something." That is how you get AI slop. "Build me a fitness app" without research means wrong database, security holes, breaks at 10 users. AI output looks right and is formatted well, which makes it easy to accept without checking.

Step 1: Research

AI models have a training data cutoff. They know what they knew when training stopped. Tell the AI to search the web, pull current documentation, find recent data, look at competitors. You are feeding it fresh information it did not have before. You are giving it context it cannot get on its own.

Technical: Research fixes the cold-start problem. Without it, the model works from stale training data.

Expert Hat vs Expert's Research

"You are an expert in X" tells the model to weight expertise patterns. But it is still generating from old data. Making the model go find current information first is different. It is not just wearing the expert hat. It has the expert's latest research on the table. Real articles. Real documentation.

Step 2: Plan

Force the AI to think. Break the problem down. Consider architecture, sequence, dependencies. You can read the plan and push back: "Why that database?" "What about mobile?" "Is this secure?" You go from spectator to architect. Google Research (2022) found chain-of-thought prompting jumped accuracy from 17.9% to 56.5%.

Technical: Chain-of-thought prompting (Wei et al., 2022, Google Research Brain Team)

The Vibe Coding Problem

Andrej Karpathy, former head of AI at Tesla, coined "vibe coding": fully giving in to the vibes, letting AI write everything, not really looking at what it produces. The app will look right. It might work in a demo. But the database might be wrong, auth might have holes, it falls apart at scale. Planning fixes that.

Step 3: Execute

NOW you let it work. Execution comes third, not first. Generative AI: draft the article, create the image, build the proposal. Agentic AI: build the feature, process the files, run the deployment. The model knows what it is building. It knows the standards and constraints. All it has to do is produce.

Step 4: Test

Every AI output needs verification. Every single one. Software: run it, check for errors, test non-obvious cases. Content: is it accurate, did it slide into generic AI voice? Design: is it logical, consistent? Stanford researchers found developers using AI assistants were more likely to introduce security vulnerabilities because they trusted without checking.

Technical: Perry et al. (2023), Stanford University: AI assistant security vulnerability study

The Loop

Testing sends you back to earlier steps. You test, find something off, research why, adjust the plan, execute again. That loop IS the process. The best results come from iteration, not from a single pass. Research > Plan > Execute > Test > repeat until it is right.

Why This Works

Research gives the model better input. Planning activates its reasoning. Execution uses its generation strength on a focused task. Testing catches the errors every statistical system will produce. AI did not change the fundamentals. It changed the speed. The steps are the same. Use it once. You will feel the difference.

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Research. Plan. Execute. Test.

Research. Plan. Execute. Test.

Research. Plan. Execute. Test.

The Problem

Step 1: Research

Expert Hat vs Expert's Research

Step 2: Plan

The Vibe Coding Problem

Step 3: Execute

Step 4: Test

The Loop

Why This Works

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