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Everyone keeps asking which AI model is best. I think that is the wrong question. The best users do not use one model anymore, they switch between them based on the job. Here is the workflow I keep seeing.
Everyone keeps asking me the same thing. Which AI model is the best one? I get why people want a single answer. But I think it is the wrong question to ask.
The better question is not which model is best. It is which model is best for this task. The people getting the most out of AI stopped picking a favorite. They switch between models based on the job in front of them, and once I saw the pattern I could not unsee it. Here is exactly how it works.
The MethodThe Three-Model Workflow
The workflow I keep seeing has three steps, and you do not use one model for all of them. You hand each part of the job to the model that is best at that part. Think first, then execute, then review.
Step 1
Think
Start with your smartest model. This is the one you use to plan the strategy, break the problem into pieces, and map out the approach. You want deep reasoning here, not speed. Give it room to think before anything gets built. In my flow this is a strong reasoning model like Claude's Fable 5.
Step 2
Execute
Now switch to your fastest model. The hard thinking is done, so this part is about doing the work quickly. Building, writing, coding, churning through the plan you just made. You do not need your deepest thinker for this, you need speed. A quick model like GPT-5.6 Sol does the heavy lifting fast.
Step 3
Review
Here is the step most people skip. Take the finished work and hand it to a different model to look for mistakes. Not the one that built it. A fresh model reads it cold and catches what the others missed. This single step has saved me more times than I can count.
Why It WorksWhy A Different Model To Review
Every model has different strengths. Every model also has different blind spots. That is the whole point of switching.
When one model builds something, it tends to be blind to its own mistakes. It made the same assumptions on the way in and on the way out. Ask it to check its own work and it will often tell you it looks great, because it is reading the problem the same way it did the first time.
A second, different model does not carry those same blind spots. It reads the work cold, with no attachment to how it got made, so it notices the gaps the first one talked itself past. It is the same reason a friend catches the typo you read past ten times. Fresh eyes see what tired eyes cannot.
The One Rule
The reviewer has to be a different model than the one that did the work. Same model, same blind spots. If you send the work back to the model that built it, you are asking it to catch a mistake it was already blind to. Switch the model and you switch the point of view.
In PracticeA Real Lineup
Here is the kind of lineup I reach for. Think of it as a starting point, not a rulebook. The exact names change every few months. The pattern does not.
- Plan and strategy: your smartest reasoning model. For me that is Claude's Fable 5. This is the one I trust to think a problem all the way through before anything gets built.
- Build and code: a strong, fast model like GPT-5.6 Sol. Once the plan is set, I want speed to get it made, not another deep-thinking session.
- Review and critique: a third, different model. Anything but the one that did the work. Its only job is to read the result cold and tell me what is broken.
- Quick, simple tasks: your cheapest fast model. A short email, a quick rewrite, a fast answer. No need to spend your best model on small stuff.
One honest note. Do not get too attached to the exact names. New models come out constantly, and the best pick for each job shifts with them. What stays true is the shape of the workflow. Smartest to think, fastest to build, a different one to review.
The AnalogyThink Streaming Services
Here is how I explain it to people. AI models are like streaming services. Netflix, Hulu, all of them. If you only ever open one, you miss all the good stuff sitting on the others.
Nobody watches only Netflix and thinks they have seen everything worth watching. The good shows are spread across all of them. The skill is knowing which app to open for what you are in the mood for.
AI works the same way. The advantage is not owning the one perfect model. It is knowing which one to open for the job in front of you, and being able to switch in seconds.
The Takeaway
Stop hunting for the one best model. Start building a lineup. Your smartest model to think, your fastest to build, and a different one to review. That switch, from a favorite to a workflow, is what separates the people getting real work out of AI from the people still asking which one is best.