Curated shared instructions for software teams

As teams mature in their use of AI, relying on individual developers to write prompts from scratch is emerging as an anti-pattern. We advocate for curated shared instructions for software teams, treating AI guidance as a collaborative engineering asset rather than a personal workflow.

Initially, this practice focused on maintaining general-purpose prompt libraries for common tasks. We’re now seeing a more effective evolution specifically for coding environments: anchoring these instructions directly into service templates. By placing instruction files such as CLAUDE.md, AGENTS.md or .cursorrules into the baseline repository used to scaffold new services, the template becomes a powerful distribution mechanism for AI guidance.

During our Radar discussions, we also explored a related practice: anchoring coding agents to a reference application. Here, a live, compilable codebase serves as the source of truth. As architecture and coding standards evolve, both the reference application and embedded instructions can be updated. New repositories then inherit the latest agent workflows and rules by default. This approach ensures consistent, high-quality AI assistance is built into every project from day one, while separating general prompt libraries from repository-specific AI configuration.

For teams actively using AI in software delivery, the next step is moving beyond individual prompting toward curated instructions for software teams. This practice helps you apply AI effectively across all delivery tasks — not just coding — by sharing proven, high-quality instructions. The most straightforward way to implement this is by committing instruction files, such as an AGENTS.md, directly to your project repository. Most AI-coding tools — including Cursor, Windsurf and Claude Code — support sharing instructions through custom slash commands or workflows. For noncoding tasks, you can set up organization-wide prompt libraries ready to use. This systematic approach allows for continuous improvement: As soon as a prompt is refined, the entire team benefits, ensuring consistent access to the best AI instructions.