#ai-coding (57)
- Your First AI-Powered Coding Steps: Core Agent Commands
Discover the power of omp.sh by learning its core commands and how to integrate AI directly into your terminal-based coding workflow for enhanced productivity.
- Collaborative Intelligence: Subagents and Hindsight Memory
Explore how omp.sh leverages collaborative intelligence through subagent-like workflows and learns from past interactions with hindsight memory, enhancing problem-solving in your terminal.
- Integrate omp.sh AI Agent into Your Dev Workflow
Readers will learn to integrate the omp.sh AI agent into their development workflow, configuring AI providers and leveraging advanced features to solve complex coding tasks.
- omp.sh: AI Coding Workflow from Setup to Advanced Features
Readers will learn to set up, use core commands, and apply advanced omp.sh features to streamline AI coding workflows and debug projects effectively.
- Integrate AI Agents in Kanbots to Automate Code Generation
Learn to integrate AI agents into Kanbots, enabling them to generate code and perform tasks within isolated git worktrees directly from Kanban cards.
- Kanbots: AI Agents, Worktrees, & Dev Workflows
Master Kanbots: integrate AI agents like Claude/Codex, leverage git worktrees for isolated runs, and orchestrate multi-agent dev workflows with practical persona-based examples.
- Develop Enterprise Applications with Modern Angular
Learn to build robust enterprise Angular applications using modern features, reactive state, scalable architecture, and AI-assisted development practices.
- Kickstarting Modern Angular with Standalone Apps
Begin your Angular mastery journey by setting up your development environment and creating your first modern Angular standalone application, leveraging AI for initial setup.
- Kickstarting Modern Angular with Standalone Apps
Begin your Angular mastery journey by setting up your development environment and creating your first modern Angular standalone application, leveraging AI for initial setup.
- Build a Secure Angular Enterprise Dashboard Core
Learn to build a secure Angular enterprise dashboard core, implementing robust authentication, routing with standalone components, and leveraging AI for efficiency.
- Build a Secure Angular Enterprise Dashboard Core
Learn to build a secure Angular enterprise dashboard core, implementing robust authentication, routing with standalone components, and leveraging AI for efficiency.
- Comprehensive Testing Strategies for Production-Ready Apps
Master comprehensive testing strategies for production-ready Angular applications, from unit tests to E2E, integrating modern tools and AI-assisted workflows for robust, scalable software.
- Comprehensive Testing Strategies for Production-Ready Apps
Master comprehensive testing strategies for production-ready Angular applications, from unit tests to E2E, integrating modern tools and AI-assisted workflows for robust, scalable software.
- AI-Assisted Development Workflows & Project 3: Enhancing a CMS
Explore AI-assisted Angular development workflows, from code generation to refactoring and testing, by enhancing a robust CMS project for enterprise applications.
- AI-Assisted Development Workflows & Project 3: Enhancing a CMS
Explore AI-assisted Angular development workflows, from code generation to refactoring and testing, by enhancing a robust CMS project for enterprise applications.
- Deploying, Securing, and Maintaining Angular Apps in Production
Learn to deploy, secure, and maintain Angular applications in production, leveraging CI/CD pipelines and modern AI tools for robust, scalable systems.
- Deploying, Securing, and Maintaining Angular Apps in Production
Learn to deploy, secure, and maintain Angular applications in production, leveraging CI/CD pipelines and modern AI tools for robust, scalable systems.
- Adapting Prompts for Claude Opus 4.7 System Changes
Learn to adapt your prompt engineering strategies for Claude Opus 4.7's updated system prompt, ensuring optimal model behavior and avoiding regressions.
- Prompt Engineering Fundamentals for Effective LLM Communication
Master fundamental prompt engineering techniques to effectively communicate with Large Language Models and build your first interactive AI applications.
- AI Coding Systems: From Copilots to Agents
Learn to leverage AI coding systems like Cursor 2.6 and GitHub Copilot to enhance your development workflow, from code generation and debugging to advanced agent-based automations.
- AI Security for LLMs and Agentic Applications
Secure AI systems, including LLMs and agentic applications, by understanding and mitigating prompt injection, data poisoning, and critical design flaws.
- AI-Native IDEs: Supercharging Your Development Workflow
Explore AI-Native IDEs, how they integrate LLMs and agents to enhance coding, debugging, and project management, and their role in the future of software development.
- Best Practices for AI-Augmented Development: Security, Ethics, and IP
Master best practices for secure, ethical, and IP-conscious AI-augmented development with tools like Cursor 2.6 and GitHub Copilot.
- Generate Functions, Classes, and Files with AI Coding Tools
Learn to use AI coding assistants like Cursor and GitHub Copilot to generate complete functions, classes, and files, improving your development workflow.
- Your First AI-Generated Code: Inline Suggestions and Autocomplete
Discover how to leverage AI coding assistants for inline code suggestions and intelligent autocomplete to boost your development speed and efficiency.
- Automating CI/CD with AI Agents and Coding Systems
Automate your CI/CD pipelines with AI agents, streamlining tasks like code generation, testing, and deployment to significantly improve development efficiency.
- Mastering the AI Conversation: Prompt Engineering for Code
Unlock the full potential of AI coding tools like Cursor and GitHub Copilot by mastering prompt engineering for code generation, debugging, and advanced agent tasks.
- Refactoring and Code Review with AI: Enhancing Quality and Readability
Learn how AI coding systems and copilots can significantly enhance your refactoring efforts and streamline the code review process, leading to higher quality and more maintainable code.
- Mastering AI Coding Systems & Copilots
Explore AI coding systems like Cursor and Copilot. Learn to leverage AI for code generation, debugging, testing, PRs, and reviews. Discover best practices and real-world applications.
- Setting Up Cursor 2.6 and GitHub Copilot for AI Coding
Learn to set up and configure Cursor 2.6 and GitHub Copilot, covering prerequisites, installation, and initial settings to enhance your AI-powered coding workflow.
- Welcome to AI-Augmented Development: Copilots vs. Agents
Explore the transformative world of AI-augmented development, differentiating between interactive AI copilots and autonomous AI agent systems, and understand their roles in modern coding workflows.
- Structuring Information for LLMs: Effective Context Design
Dive into effective context design for LLMs, learning how to structure information, manage data flow, and optimize inputs for superior AI performance and reliability.
- Akka Agentic AI vs LangChain: Complete Comparison 2026
Comprehensive comparison of Akka Agentic AI and LangChain - features, performance, pros & cons, and when to use each for LLM orchestration and agentic AI development.
- Empower AI Agents with Tools & Functions for Real-World Actions
Learn to define custom tools, implement function calling, and integrate external APIs to empower AI agents for real-world tasks.
- Best Practices for Securing AI-Generated Code
Learn to implement robust best practices for securing AI-generated code, mitigating unique risks and ensuring application integrity and compliance.
- AWS Kiro: Your AI Coding Companion
Learn to master AWS Kiro, the AI-powered IDE for efficient and intelligent coding.
- Setting Up Your AWS Kiro Environment
Learn how to set up your local development environment for AWS Kiro, including installing necessary tools and configuring credentials.
- Introduction to AWS Kiro and Agentic Development Setup
Readers will gain a foundational understanding of AWS Kiro and agentic development, then configure their local environment for immediate AI-assisted coding.
- Your First Kiro Agent: A Guided Tour
Learn to configure, deploy, and interact with your first Kiro agent for enhanced development workflow.
- Building Custom Kiro Agents
Learn how to build custom Kiro agents for enhanced AI-driven development workflows.
- Kiro's Four-Layer Architecture Explained
Explains the four-layer architecture of AWS Kiro, a powerful AI-driven development tool.
- Integrating Kiro with AWS Services
Learn how to integrate AWS Kiro with AWS services for seamless cloud-native application development.
- The Model Context Protocol (MCP)
Learn about the Model Context Protocol (MCP) in AWS Kiro, its role in facilitating communication and context sharing among AI agents.
- Testing Strategies for Kiro Agents
Learn how to effectively test AWS Kiro agents for correctness, consistency, and reliability.
- Advanced Prompt Engineering with Kiro
Learn advanced prompt engineering techniques for Kiro, the intelligent AI agent for AWS.
- CI/CD Pipelines with AWS Kiro
Learn how to integrate AWS Kiro into your CI/CD pipelines for automated code reviews and more.
- Security Best Practices for Kiro Development
Learn how to implement robust security best practices for AWS Kiro development workflows.
- Project: Enhancing a Web Application with Kiro Agents
Learn how to use AWS Kiro to enhance a Python Flask web application with agent-driven development.
- Performance Tuning and Optimization for Kiro
Learn how to optimize AWS Kiro for better performance, cost-effectiveness, and smarter AI solutions.
- Kiro in Team Workflows and Collaboration
Learn how AWS Kiro can transform team workflows and collaboration in software development.
- The Future of AWS Kiro and AI-Powered Development
Explore the future trajectory of AWS Kiro and its role in transforming AI-powered development.
- Project: Deploying a Kiro-Managed Microservice
Learn how to deploy a serverless microservice using AWS Kiro, from IaC generation to cloud deployment.
- How to Generate and Debug Code with AWS Kiro AI IDE
Learn how to use AWS Kiro, an AI-powered IDE, to generate and debug code with natural language specifications.
- Foreword
An exploration of agentic design patterns for building intelligent systems, essential for developers working with large language models.
- Build a Multi-LLM Chatbot with Dynamic Provider Switching
You will build a functional Python chatbot that dynamically switches between multiple LLM providers, manages conversation history, and incorporates robust error handling.
- A2UI Fundamentals - The Core Concepts
An introduction to A2UI, an open-source protocol for creating interactive AI interfaces.
- Develop A2UI Agent Interfaces with Local and API AI
Learn to build production-ready A2UI agent-driven interfaces, integrating both local and API-based AI models through practical projects.