Dimitris Kargatzis

Linear's webhook system and API have been also crucial for our post-action workflows. We're automatically updating statuses, leaving comments, and tracking progress based on GitHub events through their webhook integration. The API is good and the webhook payloads are well-structured, making it easy to map GitHub PRs and deployments to Linear tickets. Our AI agents can now automatically coordinate development workflows across GitHub and Linear.

Slack's Socket Mode and webhook APIs have unlocked some really cool agentic capabilities for us. We're building AI agents that can operate directly within Slack channels, responding to events, coordinating team actions, and executing post-action workflows. The real-time messaging combined with our webhook integration means our AI can notify teams instantly about PR reviews, deployments, or governance issues. Plus, the bot framework makes it feel like having an AI teammate that's always available in the channel.

PGVector's native vector operations with PostgreSQL's ACID compliance works perfectly. We're storing millions of embeddings with sub-millisecond similarity search using cosine distance. The async connection pooling handles concurrent connections, while the vector indexing makes our query super fast. Having vector search, full-text search, and relational data in one database eliminates the complexity of managing multiple data stores.

LangGraph's graph-based architecture with nodes and edges was the key on how we coordinate complex AI workflows. We're orchestrating multi-agent conversations where each node handles specific tasks (analysis, decision-making, action execution) and edges manage the flow between them. Memory lets us build operations that maintain context across conversations, while parallel execution nodes handle multiple AI operations simultaneously. The Pydantic formatted outputs ensure type-safe data flow between nodes, and the checkpoint system with PostgreSQL persistence lets us maintain state across these graph executions, so conversations can resume seamlessly even after server restarts.

FastAPI's async-first architecture with Pydantic validation and automatic OpenAPI generation helped a lot without implementing things manually. We're handling thousands of concurrent requests with really good response times. The dependency injection makes our service layer clean, while the built-in middleware stack handles CORS, authentication, and request context out of the box. Also, the automatic type checking and validation have caught bugs before they hit production.

GitHub is the heartbeat of our entire development workflow. Our GitHub App integration with webhooks has enabled us to we track and respond to development events in real-time. Every PR, deployment, issue, and commit automatically triggers our Agentic analysis and governance workflows. The webhook system is incredibly reliable - we're processing thousands of events daily without missing a beat.

Supabase Vector has been vital to kickstarting our RAG features. After experimenting with MongoDB, Pinecone, and SingleStore, Supabase stood out as the best fit for its learning curve, flexibility, and ability to meet our needs effortlessly.

It helped us integrate LangGraph agent tools, enhancing our AI capabilities by allowing seamless interaction and data processing between various language models.

Gemini's extensive token window makes it our go-to solution for one-shot analysis, enabling efficient and precise insights without the need for iterative processing.

We leverage GitHub Actions to govern pull requests with robust checks, ensuring well-crafted environments and thorough deployment reviews. Our approach promotes reusable workflows, streamlining operations for teams. Our assistant is equipped with full context of all GitHub Marketplace actions, enabling better workflow optimization and an intuitive creation process. Additionally, we provide clear workflow run analysis—whether at a glance through the dashboard or in detail with our assistant for iterative improvements.

LangGraph powers our assistant with robust capabilities. With support for over 15 tools, including an extensive GitHub toolkit, our assistant offers seamless out-of-the-box integration to handle almost every operation with confidence.

GitHub's app and webhook capabilities empower our dashboard to provide real-time insights. This allows teams to quickly identify priorities and tackle what’s next at a glance, streamlining daily operations.

Its ability to understand context and provide relevant suggestions, particularly for complex codebases, really sets it apart. Whether you're working on small projects or large-scale applications, Cursor.ai can help boost productivity and reduce development time. Highly recommend giving it a try if you're looking to streamline your coding process!

A great tool for quick and simple visual brainstorming. It’s perfect for sketching out ideas, creating flowcharts, or collaborating in real-time with a hand-drawn feel.

The go-to tool for design and prototyping. Its real-time collaboration is unmatched, making it incredibly easy for teams to work together, even remotely.