Vibe coding without a plan is like gambling. It's sending prompt to a coding agent, and hoping the result will meet your desire.
But you never really know what you want. You probably won't fully explain your intent in one prompt.
The agent could misunderstand your intent, and execute the wrong thing, and reversing that and rebuilding takes more time than just planning upfront.
Both Traycer and Antigravity try to solve this. Instead of jumping straight to code, they make you plan first. They just do it very differently.
Antigravity: The Fast Food Cook
Antigravity is a standalone AI IDE built by Google.
When you send a prompt in Antigravity, it goes into plan mode first and immediately produces a single Markdown plan file. The plan has sections: proposed changes, example workflow, a verification checklist. It looks thorough, until you realise it assumed the wrong thing entirely.
But once you click proceed, it starts right away and builds. It has an action bias. It wants to move. It would rather start building and let you correct course than slow down to ask questions.
If you want more control, you have to explicitly state it in writing — just like telling a fast food cook exactly how you want your order. And to be clear: I'm not saying the code quality is as bad as fast food. But the process can end up far from the result you actually wanted.
The interesting part: Each line in the plan has a comment button… like Google docs. You can click on a line and leave a text comment to give feedback on that specific point. It’s a clever interaction model.
Traycer: The personal chef
Traycer is a VS Code extension that runs inside whatever editor you're already using: Cursor, VS Code, and even Antigravity — yes, you can layer Traycer on top of Antigravity. It's not a replacement for your tools, it's a layer on top.
When you send a vague prompt to Traycer, it doesn't plan immediately. It asks you questions. At least four in the first round, then more rounds as the picture gets clearer. The questions come as an interactive form: multiple choice, clickable options. You're not typing paragraphs, you're clicking answers.
This matters more than it sounds. When your idea isn't fully formed, writing a response is work. Clicking an option is easy. The clickable Q&A means you can participate in the clarification process without having already figured out what you want.
After the Q&A, Traycer builds out multiple plan files progressively:
- A simple problem statement
- A detailed plan with mermaid diagrams
- A detailed plan with design and an HTML wireframe: a visual preview of what you're building before any code is written
- Tickets: the execution units passed to your coding agent
That last step is the key architectural difference. Traycer doesn't execute code itself, instead it hands tickets to your agent (Cursor, Claude Code, etc.), which breaks them down further and runs them. After each ticket, Traycer runs a verification pass to check the implementation against the spec.
Side by Side:
| Traycer | Antigravity | |
|---|---|---|
| Planning interaction | Interactive Q&A (clickable multiple choice) | Inline comments on plan (text only) |
| Plan output | Multiple files, built progressively | Single Markdown file |
| Visualizations | Mermaid diagrams + HTML wireframes | Text only |
| Verification | Automatic after each ticket | Manual review |
| Execution | Passes tickets to external agent | Builds internally |
| Architecture | VS Code extension | Standalone IDE |
| Speed | Slower, more checkpoints | Faster, fewer decisions |
When Each One Makes Sense
Here's the framing I keep coming back to: it depends on whether you're starting from scratch or editing something that already exists.
When you're starting fresh, your idea is vague and that's okay. You can build fast, see what comes out, and iterate. The cost of a wrong assumption is low — nothing is broken yet.
When you're making changes to an existing codebase, wrong assumptions don't just produce imperfect output. They break things that already work. You want the AI to understand exactly what you mean before it touches anything. That's where Traycer's intent-extraction process earns its slower pace.
Use Antigravity if:
- You're prototyping something new and want to move fast
- Your idea is already fairly clear and you don't need to be questioned
- You want everything in one environment — plan and build in the same place
- You're comfortable correcting course after seeing an initial output
Use Traycer if:
- You're working on an existing repo and need precision
- Your idea isn't fully formed and you need help articulating it
- You want visual output during planning — wireframes, diagrams
- You want automatic verification at each execution step
- You're already using Cursor or Claude Code and don't want to switch environments
I also compared Traycer with Kiro. read the full comparison here
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