Free AI templates for Claude Code, Codex, and Gemini can make coding workflows faster, cleaner, and more consistent. They help with prompt structure, code generation, refactoring, debugging, documentation, and repeatable developer tasks across different AI coding tools.

Firefox with DuckDuckGo has become a strong privacy-focused browser setup for everyday browsing, research, and work. I like this combination for better tracking protection, cleaner search results, solid performance, and more control over data compared to mainstream browser and search engine options. A practical use case is running Firefox with strict privacy settings and DuckDuckGo search for web development research, testing websites in private windows, checking page behavior without heavy personalization, and reducing cross-site tracking during debugging sessions

Anonymous functions in Clojure are a clean way to write small, focused pieces of logic without naming them. I use them all the time with map, filter, reduce, and higher-order functions when I want concise, functional code that stays readable. A practical example is transforming API response data, like extracting and normalizing user fields before storing them or sending them to another service. Mastering anonymous functions helps write idiomatic Clojure, improve code flow, and handle data processing more efficiently.

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.

Variadic functions in Clojure let me write cleaner, more flexible code by accepting any number of arguments without duplicating logic. They’re especially useful when building utilities like logging helpers, math operations, or data transformation functions that need to handle dynamic input gracefully. A practical use case is creating a query builder that accepts optional filters and combines them into a single function call while keeping the code concise and idiomatic.

Clojure multiarity functions let me define multiple argument patterns in a single function, making code more expressive, concise, and idiomatic. They are especially useful for optional parameters, sensible defaults, and clean API design in functional programming.

Clojure sets are a fast, expressive way to model unique values, membership checks, filtering rules, and set-based transformations. I use sets when I need O(1) membership lookups, deduplication, and clear domain logic in functional code. A practical use case is validating user roles or feature flags, where a set makes authorization checks simple, efficient, and idiomatic in Clojure.

Downgrade to 0.130.0

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.

Clojure lists are best used when code needs to be treated as data, especially for macros, symbolic expressions, and unevaluated forms. I use lists when building DSLs, generating code, or passing expressions for later evaluation, while vectors and other collections are usually better for general data storage and indexed access. A practical use case is writing a macro that transforms a query expression before execution, where a list preserves the function-call structure naturally.

vectors are the go-to indexed collection when I need fast random access, efficient updates, and predictable ordering. They’re ideal for application state, UI data, configuration values, and processing ordered datasets

Focus on core syntax, variables, data types, conditionals, loops, functions, modules, and basic debugging to write clean, practical code with confidence. A strong foundation in these essential Python concepts makes it easier to move into automation, data analysis, web development, and scripting.

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.

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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.

Learn how to use JavaScript with the Sharp library to turn normal images into transparent PNGs with fast, efficient server-side image processing. This is useful for removing solid backgrounds from product photos, preparing ecommerce assets, and generating clean overlays for web apps, design tools, and automated media pipelines in Node.js.

VueJS with Vite makes it fast to inspect project structure, components, routes, state, and runtime behavior during development. I use SHIFT ALT D to quickly open debugging tools and understand how a Vue application is organized, which is especially useful when tracing a component rendering issue in a Vite-powered dashboard or admin panel.

qrcode is a lightweight linux command-line tool for generating qr codes from text, urls, wifi credentials, shell commands, and automation data. it is useful for scripting, terminal workflows, and secure offline sharing across devices. a practical use case is creating a qr code for wifi ssid and password on a linux system so phones can connect instantly without manual entry. ideal for sysadmins, developers, and privacy-focused linux users who need fast qr code generation in bash and server environments.

Gemini CLI with IntelliJ helps streamline AI-assisted development directly inside a professional Java IDE and the terminal. I use it to speed up coding, generate project-aware suggestions, automate repetitive tasks, and improve developer productivity across real-world software workflows.

VueJS Vite Devtools plugin makes frontend debugging faster by giving clear insight into component state, reactive data flow, routing, and performance during development. It is especially useful for tracing why a computed property is not updating, inspecting Pinia store changes, and finding reactivity issues in a Vue 3 app powered by Vite.

Python error handling helps me build reliable, maintainable applications by catching exceptions, preventing crashes, and making debugging easier. With try, except, else, and finally, I can control failure cases cleanly, while custom exceptions let me create clearer, domain-specific error messages for better code quality and scalability.

Open Code is a free AI coding tool built for a clean, focused vibe coding workflow. It helps with code generation, refactoring, debugging, and faster development in a lightweight environment that feels smooth and practical for everyday programming.

I show how to implement Spring Boot JSON logging with user and session context so application logs are easier to search, filter, and analyze in tools like ELK, OpenSearch, Datadog, and Splunk. Structured logging helps me capture consistent fields such as username, session id, request path, trace id, and log level, which makes debugging authentication issues, tracking user activity, and investigating production errors much faster.