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Kit · References

References

Papers, documentation, talks and tools to go deeper. Each one has a sentence on why it is here.

10 of 10

  • Designing Data-Intensive Applications

    O'Reilly · Recommended · The book behind most good decisions about storage, replication and consistency.

    Read
  • Building Reliable Agents with LangGraph

    LangChain · Useful reference · A practical talk on graph-based agent control flow with the failure modes called out.

    Read
  • OWASP Top 10 for LLM Applications

    OWASP · Recommended · The threat list to check any tool-calling agent against before it touches production data.

    Read
  • Attention Is All You Need

    arXiv · Deep dive · The transformer paper. Still the right starting point for understanding what the model underneath is doing.

    Read
  • AI Engineering on Kubernetes

    Kubernetes · Advanced · Workload primitives you need to understand before scheduling GPU-backed inference.

    Read
  • The System Design Primer

    GitHub · Getting started · The best free grounding in the distributed systems ideas every AI application eventually needs.

    Read
  • Model Context Protocol

    Anthropic · Useful reference · The specification agents and tool servers must agree on. Read before building any gateway.

    Read
  • OpenTelemetry Documentation

    OpenTelemetry · Useful reference · The reference for traces, metrics and logs, including the GenAI semantic conventions.

    Read
  • RAG at Scale: Architecture and Lessons

    Google Cloud · Deep dive · A production-oriented walkthrough of retrieval architecture choices and their operational cost.

    Read
  • Building Effective Agents

    Anthropic · Recommended · The clearest written case for simple, composable agent patterns over frameworks.

    Read
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