Your AI Stack Is a Team, Not a Model

GPT and Claude are not the whole stack.

For most people, the AI stack is one chat tab. ChatGPT or Claude, and every job goes in there. Design this screen. Write this function. Check my code. Same tab, same model, every time.

That works, up to a point. After that, it’s one person doing design, code, review and demos. They’ll do all of it. They won’t do all of it well.

A team, new era. One model, old era.

Claude and ChatGPT are still the seniors. They think, plan and write. Around them sit tools built for one job each.

Four of them complete the team.

Google Stitch: the designer

Stitch is a Google Labs tool for UI. Describe the screen in plain words, “a booking screen for a clinic, calendar on top, open slots below”, and you get the design plus the front-end code behind it. Not just a picture. Code you can build on.

Its job is the first draft, front end only. You refine it instead of starting from a blank page.

CodeRabbit: the reviewer

CodeRabbit connects to your repo on GitHub or GitLab and reviews every pull request automatically: a summary of what changed, plus comments on the lines that look wrong.

The point is the order. The PR gets reviewed before anyone on the team opens it. So the human review skips the missing null checks and typos, and gets back to the question only a person should answer: is this even the right approach?

It doesn’t replace the human review. It’s the first pass, so the second pass is worth something.

GLM from Z.ai: the cheap coder

Z.ai is the Chinese lab behind the GLM models, and GLM is strong at code. You can run it inside tools like Claude Code or Cline.

This part is my experience, as of June 2026 when I made the reel: almost the same coding quality, at about a quarter of Claude’s cost. I build my own software with agentic tools, so that adds up fast.

Watch the word “almost”. On the hardest problems, the gap can show. On everyday features and fixes, a quarter of the cost is hard to say no to. Test it on your own work before you believe me. And like any API, your code goes to their servers, so check the data policy before you send client code.

Claude Artifacts: the prototyper

In Claude, you describe an idea and it builds a working page right next to the chat. You use it live: click the buttons, break it, ask for changes.

Its job is closing the gap between “I have an idea” and “look at this”. You share a prototype, not a document, and you learn from people using it, not reading about it.

The stack is a team

The stack is a team, not one model.

One job each. Artifacts proves the idea. Stitch designs. Claude or GLM builds. CodeRabbit reviews. The big models do the thinking.

You don’t need all four tomorrow. You need to stop sending every job to the same place.

Try it

Move one job to its teammate today. Paste this into Notion or Obsidian and fill it in:

MY AI TEAM: one job, one tool

- [ ] Show an idea people can click:  Claude Artifacts
- [ ] Design a screen:                Google Stitch
- [ ] Everyday coding:                GLM (Z.ai)
- [ ] First review of every PR:       CodeRabbit
- [ ] Think, plan, write:             Claude / ChatGPT

1. Next to each job, write who does it today (usually: the same chat).
2. Tick ONE: the job you do most this week.
3. Hand it to its teammate for 5 working days.
4. Day 5: compare time, cost, and how much you fixed.
5. Keep it or send it back. Then the next row.

GPT and Claude are not the whole stack. They’re the seniors. Hire the rest of the team.