Developing Production-Ready Apps in Collaboration With AI Agents

AI agents in software development are used to automate repetitive tasks, provide assistance in code generation, testing, and deployment, and act as virtual developers to help improve productivity. They follow agentic design patterns such as tool use, planning, reflection, and multi-agent collaboration.

AI agents differ from traditional coding assistants by using agentic design patterns. They can use tools, plan tasks, reflect on their work, and interact with other agents. This allows them to perform more complex tasks autonomously compared to traditional assistants that primarily focus on code generation and refactoring.

The tools and platforms mentioned include Zencoder for AI agent integration, VS Code, JetBrains IDEs, Docker, Postgres, Prometheus, Grafana, and various MCP (Module Context Protocol) libraries for tool access.

Best practices include being specific in your tasks, providing relevant details, splitting large tasks into subtasks, avoiding high-level task delegation, defining rules and instructions for AI, experimenting with prompts, and not overloading the agent with too much information.

No, AI agents are not seen as replacements for developers but as productivity boosters. They automate repetitive tasks and assist in coding, allowing developers to focus on more creative and complex aspects of software development.

The ZenCoder plugin is used to integrate AI agents into your existing IDEs to assist with coding tasks like code generation, testing, and deployment. It serves as a tool to enhance productivity by automating routine tasks.

MCP connects LLMs (Large Language Models) with various tools, allowing them to perform tasks using structured inputs and outputs. It includes MCP clients and servers, where clients request tool usage and servers execute these requests, providing results back to the LLM.

The future of AI in software development involves AI acting as a true co-pilot, automating routine tasks, and enabling developers to focus on creative work. AI is expected to transform how developers work by managing virtual agents and optimizing productivity, rather than replacing developers.

During the workshop, a conference website was developed with a React frontend, Node.js backend, PostgreSQL database, and Docker for containerization. The application included features like page navigation, talk submission, and monitoring setup with Prometheus and Grafana.