I am using Antigravity CLI as part of a multi-agent software development workflow.
The issue is not only model capability, but the reliability of the coding agent during complex project execution.
I initially used the 3.6 high model. After encountering repeated issues, I switched to the 3.1 Pro model, but the same types of problems still occurred.
The main problems I observed:
- Project instruction following
The agent sometimes fails to consistently follow established project rules and constraints.
Examples:
- ignoring existing development rules
- changing files outside the assigned scope
- making assumptions instead of asking for clarification
- Completion status accuracy
The agent often considers a task “completed” when only a prototype or partial implementation is finished.
Examples:
- code generated but not fully integrated
- UI exists but API contracts are inconsistent
- tests pass in a limited environment but production conditions are not verified
- Engineering validation gaps
Important engineering aspects are sometimes missed:
- version control and backup verification
- commit/hash consistency
- API/DTO contract consistency
- security boundaries
- production permission models
- failure path testing
- Risky autonomous changes
The most serious issue is that incorrect changes can require other coding agents to repair them.
In a real software engineering workflow, an incomplete task is usually less harmful than an autonomous agent making incorrect changes to an existing system.
My expectation:
Antigravity CLI is very useful for rapid prototyping and implementation, but for complex projects it needs stronger:
- project rule adherence
- task boundary awareness
- completion criteria verification
- safer autonomous execution controls
This feedback is based on a real multi-agent development workflow where Codex and Claude were used for independent review and verification.
