Intro In this episode of Appian Rocks, Stefan turns the spotlight on one of the most fundamental aspects of Appian development: expressions. Though they often operate behind the scenes, expressions power nearly every part of an Appian application—from interfaces to process models, decision logic to integrations. With the right approach, expressions can elevate a project’s maintainability, performance, and developer experience. But when misused, they can quickly become a source of confusion and technical debt. TL;DL Expressions are the lifeblood of Appian applications. In this episode, Stefan explains how to write clean, reusable, and performant expressions, shares practical tips for improving readability and maintainability, and discusses common mistakes that Appian developers should avoid. On the role of expressions in Appian Expressions in Appian are not just scripting snippets—they're integral to building dynamic and flexible applications. Stefan emphasizes the importance of understanding the typed expression language deeply, especially when working with complex data structures. Expressions are used across every layer of an application, which makes writing clean and modular logic not just a best practice, but a necessity for scalability and collaboration. Writing reusable expression rules A major theme of the episode is the value of modularity. Stefan encourages developers to think of expression rules like functions: small, focused, and parameterized. Avoiding hardcoded logic and opting for reusable rules makes applications easier to update and test. Clear parameter naming and avoiding generic inputs like pv!input are also highlighted as critical for long-term maintainability. Design and performance best practices Stefan discusses how poor design choices—like deeply nested logic or repeated inline expressions—can quickly degrade both the performance and readability of applications. Instead of duplicating logic, developers should extract reusable patterns into separate expression rules. He also stresses the importance of minimizing rule chaining and understanding how and when expressions are recalculated, especially in interface contexts where performance can be affected by unnecessary re-evaluation. Making expressions readable and maintainable Readability is another key theme. Stefan suggests using tools like a!localVariables() to better structure logic in interfaces and avoid clutter. He cautions against overusing if() when constructs like a!match() or choose() would be clearer and more concise. Commenting logic is encouraged—especially for nested or non-obvious sections—to help both current and future developers navigate the application more effectively. Collaboration and team alignment Since expressions are touched by many developers over the course of a project, Stefan advocates for team-wide standards and code reviews specific to expression logic. Naming conventions, centralized utility rules, and internal documentation all contribute to making shared codebases more understandable. He emphasizes that expressions are not just technical elements—they're collaborative artifacts that should reflect collective understanding and intentional design. Avoiding common pitfalls The episode wraps up with a discussion of mistakes Stefan frequently sees: expression rules that try to do too much, hardcoded assumptions that limit reuse, and dynamic evaluation bugs caused by lack of context awareness. His advice: keep logic modular, test thoroughly, and never underestimate the power of a well-named rule and a thoughtful comment.