Alex Shershebnev - Going Beyond Copilot with AI Agents | PyData Amsterdam 2024

AI agents go beyond simple code completion by understanding repository context, internal frameworks, and development patterns

Current code assistants like Copilot have limitations:

• No knowledge of internal repositories/frameworks
• Limited to open source training data
• Reset context between sessions
• Prone to hallucinations
• No understanding of dependencies

Developers spend only ~5% of time on actual code writing, with majority spent on:

• Understanding code
• Planning
• Debugging
• UI interactions
• Documentation
• Collaboration

Key AI agent capabilities:

• Repository-wide context awareness
• Multi-agent collaboration
• Test planning and generation
• Code improvement and optimization
• Error detection and fixes
• Memory of past interactions

Zencoder’s approach:

• Cloud-based service with VS Code/JetBrains plugins
• No training on customer data
• Support for custom documentation/context
• Pipeline for code verification and repair
• Custom agent definitions for specific tasks
• Plan to add self-hosting option

Benefits of AI agents:

• Better code quality
• Reduced debugging time
• Context-aware suggestions
• Understanding of internal practices
• Ability to handle complex requirements
• Support for test-driven development