Basic workflow

1. Choose the page that matches your work: Scrum meetings, Coding agents, Jira helper, Image generation, or Video generation.
2. Select a purpose, such as retrospective, bug report, feature request, or acceptance criteria.
3. Use the favicon info buttons beside each field when you need an example of what to write.
4. Add concrete context: goals, constraints, expected behavior, acceptance criteria, risks, and test notes.
5. Review the generated prompt, copy it, and paste it into the AI assistant or agent you want to use.

Clojure maps are a core data structure for modeling structured data, passing configuration, and building clean, composable functions. I use maps when I need fast key-based lookup, immutable updates, and a simple way to represent domain entities like users, orders, or application state.

I focus on the practical path to getting started quickly while still building a solid foundation. That includes setting up the Pulumi project, configuring the GCP provider, working with a Python-based infrastructure definition, and understanding how Pulumi tracks state and applies changes. I also cover the basic developer workflow for previewing updates, deploying resources, and making iterative changes safely. The goal is to make the first experience with Pulumi and GCP feel approachable, especially if you already know Python and want to use that skill set to manage cloud resources.

Get Clojure up and running in IntelliJ for a fast, productive Lisp development workflow on the JVM. I focus on practical setup for REPL-driven development, dependency management, code evaluation, and debugging so I can build and iterate efficiently. A strong use case is developing a data transformation pipeline that ingests EDN or JSON, applies functional business rules, and validates results directly from the IntelliJ Clojure REPL.

Leiningen on Windows is a practical way to manage Clojure projects, handle dependencies, and build and run applications from the command line. I use it to streamline Clojure development, automate project setup, and package JVM-based programs efficiently. A common technical use case is creating a command-line data processing tool in Clojure, then using Leiningen to compile, test, and run it consistently on Windows.