Ofer Mendelevitch, head of developer relations at BAND, used this episode of Zero to Agent in 30 Minutes to trace how coding workflows can give agents progressively more room to work on their own. Using a package version resolver as a running example, he compared step-by-step prompting with loop engineering and then showed how multiple agents can collaborate on the same task.
How to move from prompting to multi-agent coding
- Start with explicit prompts in every step. Give the coding agent a specification and tell it what to implement. Ofer used a package version resolver with existing Python tests, then followed up with prompts to verify the implementation, resolve open questions, and add packaging.
- Define a verifiable goal. Loop engineering replaces a sequence of individual prompts with an end result the agent can check for itself. In Ofer’s example, the agent had to implement the resolver and continue iterating until it was ready to ship with packaging. The agent can inspect the code, add tests, run them, fix failures, and verify the package without waiting for another human prompt after each step. He demonstrated how this approach allowed the agent to work through the task until the goal was met.
- Add a second agent as a reviewer. Ofer then moved from a single coding agent to two collaborating agents (using Jam), assigning one to write the code and another to review it. The reviewer examined the specification, provided feedback, and ran additional checks, including adversarial probes. A larger group of coding agents could include agents focused on security, compliance, testing, frontend, backend, or DevOps. He also described using different coding agents together so that one model can challenge work produced by another.
The shift toward more autonomous coding workflows starts with how the work is framed. By defining goals agents can verify, giving them room to iterate, and assigning complementary agents to review the work, developers can reduce the amount of human intervention required and achieve higher quality for the code generated by the coding agents.
Coming next week
Next week, Craig Hewitt will host Zero to Agent in 30 Minutes to focus on building a voice-first workflow with OpenAI Codex. The episode will show how natural voice commands can operate a development environment, run subagent workers in parallel, and trigger browser-use workflows. It will also cover structured Codex project directories and hands-free system-level execution, with the developer directing the work by voice.