React Advanced London is a community organizing quarterly in-person events and an annual hybrid conference in October.
Engineers of all levels are welcome to join, our meetups are always free to attend and a great place to meet other likeminded people and share some insights about your work and experience from the stage.
Contact email: hi@reactadvanced.com
Want to give a talk at our next meetup? We welcome talk ranging from 5 to 20 min length on any topic related to React and/or React Native, submit them here and we'll be in touch https://forms.gle/rCiQ8Y4jajiC8AHMA
Venue proposal from: https://shorturl.at/FOT34
By joining this group you agree to comply to our Code of Conduct
Practical AI for Software Engineers - dev tools in SDLC, core patterns for LLM implementation
AI for Engineers London is a community for software engineers who want to harness AI to build better software, faster.
We focus on the engineering side of AI, not ML/data science, sharing battle-tested approaches, practical tools, and proven patterns that transform how you write, test, deploy, and maintain code today.
Join us for monthly meetups featuring live demos, case studies from London tech companies.
For collaborations, reach events@gitnation.org
Topics covered:
š ļø AI-Enhanced Development & Delivery
Development Acceleration
- Code generation with Claude Code, GitHub Copilot, Cursor, and emerging tools
- Automated code reviews, refactoring, and documentation generation
- Test generation and intelligent debugging assistance
- Building with MCP servers, LangGraph, CrewAI, and agent orchestration frameworks
- Smart monitoring, alerting, and root cause analysis
- Self-healing systems and automated incident response
š§ Practical LLM Integration Patterns
Learn proven patterns for adding AI capabilities to your applications without complexity:
Core Integration Patterns
- RAG (Retrieval-Augmented Generation): Connect LLMs to your databases and documentation to answer questions using your own data ā no model training required
- LLM optimizations
- Prompt Templates & Chaining: Structure prompts for consistent outputs and chain multiple AI calls for complex tasks
- Input/Output Validation: Add guardrails to ensure AI responses meet your requirements ā from JSON schemas to content filtering
And other topics within core theme of the group
React Advanced London is a community organizing quarterly in-person events and an annual hybrid conference in October.
Engineers of all levels are welcome to join, our meetups are always free to attend and a great place to meet other likeminded people and share some insights about your work and experience from the stage.
Contact email: hi@reactadvanced.com
Want to give a talk at our next meetup? We welcome talk ranging from 5 to 20 min length on any topic related to React and/or React Native, submit them here and we'll be in touch https://forms.gle/rCiQ8Y4jajiC8AHMA
Venue proposal from: https://shorturl.at/FOT34
By joining this group you agree to comply to our Code of Conduct
Practical AI for Software Engineers - dev tools in SDLC, core patterns for LLM implementation
AI for Engineers London is a community for software engineers who want to harness AI to build better software, faster.
We focus on the engineering side of AI, not ML/data science, sharing battle-tested approaches, practical tools, and proven patterns that transform how you write, test, deploy, and maintain code today.
Join us for monthly meetups featuring live demos, case studies from London tech companies.
For collaborations, reach events@gitnation.org
Topics covered:
š ļø AI-Enhanced Development & Delivery
Development Acceleration
- Code generation with Claude Code, GitHub Copilot, Cursor, and emerging tools
- Automated code reviews, refactoring, and documentation generation
- Test generation and intelligent debugging assistance
- Building with MCP servers, LangGraph, CrewAI, and agent orchestration frameworks
- Smart monitoring, alerting, and root cause analysis
- Self-healing systems and automated incident response
š§ Practical LLM Integration Patterns
Learn proven patterns for adding AI capabilities to your applications without complexity:
Core Integration Patterns
- RAG (Retrieval-Augmented Generation): Connect LLMs to your databases and documentation to answer questions using your own data ā no model training required
- LLM optimizations
- Prompt Templates & Chaining: Structure prompts for consistent outputs and chain multiple AI calls for complex tasks
- Input/Output Validation: Add guardrails to ensure AI responses meet your requirements ā from JSON schemas to content filtering
And other topics within core theme of the group
Get in touch!
hi@guild.host