Applying Engineering Discipline to AI Coding Agents

Behavioral Templates for Engineering Discipline

The 9arm-skills repository introduces a set of structured prompt templates designed to replace eager, error-prone AI coding behavior with disciplined engineering practices. Rather than increasing model capability, these skills enforce constraints that prevent agents from guessing fixes or writing speculative documentation. The repository provides four primary skills:

• Debug Mantra: Forces the agent to follow a four-step sequence before proposing a fix: reproduce the issue, trace the failing path, question the hypothesis, and treat every run as a breadcrumb.
• Post-mortem: Requires the agent to verify the existence of a reliable reproduction, root cause, and validated fix before generating an engineering record.
• Scrutinize: Shifts the agent into an outsider perspective to challenge the necessity of a change, evaluate simpler alternatives, and verify that tests cover the actual failure path.
• Management Talk: Translates technical implementation details into high-level updates for non-technical stakeholders, stripping out stack traces while retaining product context and ticket identifiers.

Operationalizing Workflows in Verdent

While these skills are built for Claude Code, they serve as a blueprint for configuring custom sub-agents within orchestration platforms like Verdent. By assigning specific skills to dedicated agents, developers can create a coordinated pipeline where implementation, review, and communication are handled by separate, specialized instances. This separation prevents the bias inherent in an implementation agent reviewing its own code. A recommended workflow involves spawning a debugger agent to establish evidence, an implementation agent to apply the fix, a reviewer agent to perform the scrutinize step, and finally a communications agent to generate the necessary project updates. This approach treats agent performance as a function of workflow design rather than raw model intelligence.