Agent models

Claude Code, Codex, and GPT-5 Are Better as a Team

The best agent workflow is not about pledging loyalty to one model. It is about routing the right task to the right agent.

Victor Cheng

Victor Cheng

Founder, DecaSpeed

May 13, 20266 min read
Software team collaborating around laptops

I do not think the future of coding agents is one model forever. Different agents have different taste. Some are better at broad codebase reading. Some are better at tight implementation. Some are better at explaining tradeoffs. The practical workflow is to use more than one.

DecaSpeed is built around that assumption. Claude Code, Codex, GPT-5 style workflows, and whatever comes next should all be able to work inside the same project context.

The product should not force loyalty to one model. It should make the work reviewable no matter which agent did it.

Use the Right Agent for the Job

A research task is not the same as a UI patch. A flaky CI investigation is not the same as a brand-new prototype. When the job changes, the agent choice should be allowed to change too.

That is easier when the environment is stable. The project, branch, terminal, preview, and messaging thread should not disappear just because you switch from one agent to another.

A sane multi-agent workflow
Use one agent to inspect the codebase and narrow the plan.
Use another agent to implement against clear acceptance checks.
Use a final pass to review risk, tests, and the shape of the diff.

Orchestration Beats Prompt Piles

Without orchestration, agent work becomes a stack of disconnected chats. One conversation knows the plan. Another knows the error. Another knows the final patch. That is hard to review and easy to lose.

DecaSpeed keeps the agent work attached to the project. That is what makes texting your coding agents from iMessage practical: you can start work from outside, but the actual artifacts stay organized enough to review later.

The Durable Interface Is the Work

Models will keep changing. The durable interface is the work product: diff, tests, preview, logs, explanation, and a human decision. If DecaSpeed does its job, the team can benefit from better agents without rebuilding the workflow every time the leaderboard changes.