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Source channel @githubtrending · Post #15095 · Aug 25

#javascript#ai#anthropic#chatbots#chatgpt#claude#gemini#generative_ai#google_deepmind#large_language_models#llm#openai#prompt_engineering#prompt_injection#prompts There is a collection of system prompts used by popular chatbots like ChatGPT and others. These prompts are instructions that guide how chatbots respond. They are now available publicly on GitHub, which can be very helpful for users. By seeing these prompts, users can understand how chatbots work and even learn how to create their own AI tools. This can help developers build better AI applications and improve their understanding of AI technology. https://github.com/asgeirtj/system_prompts_leaks

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@githubtrending · Post #14904 · 07/03/2025, 12:00 PM

#go#ai_assistant#ai_generated_code#cloud_native#code_generation#custom_templates#developer_tools#development_framework#gin#go_sponge#golang#grpc#grpc_gateway#low_code#microservice#protobuf#restful_api#sponge#web Sponge is a powerful Go development framework that helps you quickly build backend services like RESTful APIs and microservices with minimal coding. It generates modular Go code automatically by parsing SQL, Protobuf, and JSON files, letting you create complete backend projects through a simple web interface without complex commands. Sponge supports custom templates and integrates AI assistants (like ChatGPT) to help write business logic, greatly speeding up development and reducing repetitive work. It also offers full support for testing, API docs, and deployment, making your project more stable, efficient, and easier to maintain. This saves you time and improves code quality. https://github.com/go-dev-frame/sponge

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@githubtrending · Post #14691 · 05/10/2025, 12:00 AM

#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