Find similar content

A lot of wisdom. Majority of the learnings are pretty generic and high-level, but still worth a read due to its completeness. https://addyosmani.com/blog/software-engineering-soft-parts #post#software_engineering

#typescript#ai_agents#ai_assistant#ai_coding#ai_coding_tools#ai_engineering#ai_tools#anthropic#anthropic_claude#claude#claude_ai#claude_code#claude_context#claude_mem#claude_skills#claudecode#mcp#model_context_protocol#software_engineering#spec_driven_development Claude Pilot enhances Claude Code by enforcing production-grade quality automatically. It adds mandatory testing, automatic code formatting and type checking, and persistent memory across sessions so your AI assistant maintains context on complex projects. Instead of babysitting Claude's output, you start a task, grab coffee, and return to verified, tested code ready to ship—saving hours on manual review and catching bugs before they reach production. https://github.com/maxritter/claude-pilot

#csharp#architecture#aspnetcore#clean_architecture#cqrs#ddd#dotnet#dotnetcore#event_driven_architecture#event_sourcing#kubernetes#masstransit#messaging#microservice#microservices#oauth2#opentelemetry#software_architecture#software_design#software_engineering#vertical_slice_architecture Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5]. https://github.com/meysamhadeli/monolith-to-cloud-architecture