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Project · LLMOps

LLMOps Curriculum

A structured path through the operational side of LLM systems — observability, eval discipline, cost routing, model gateways. Each phase ends at a working commit, not a quiz.

Certifications

  • Anthropic not started

    Claude Certified Architect Foundations

    Agentic architecture, MCP tool design, Claude Code workflows, context management. ~70% of exam surface overlaps existing daily practice.

  • AWS studying

    AWS AI Practitioner (AIF-C01)

    Foundational GenAI-on-AWS vocabulary. Pre-SAA warmup that fills the Bedrock/SageMaker gap SAA skims over.

  • AWS studying

    AWS Solutions Architect Associate (SAA-C03)

    Locked legibility cert. Standalone study (Cantrill + Tutorials Dojo); curriculum Phase 7 deploys provide hands-on.

41 tasks · 13 with commit evidence

  1. Phase 0 You've already done more than you think pending
    2 tasks
    • Reframe existing work in LLMOps vocabulary
    • Flag the one gap that feels embarrassing and write why
  2. Phase 1 The 4-layer mental model pending
    3 tasks
    • Read [Applied LLMs sections 1 + 3](https://applied-llms.org/)
    • Skim [ZenML's 457 case study roundup](https://www.zenml.io/blog/llmops-in-production-457-case-studies-of-what-actually-works)
    • Build the 4-layer tool-slotting table
  3. Phase 2 The retrofit in progress
    4/10 tasks with evidence
    • Stand up self-hosted Langfuse
    • Install the three deps in reasonable-ux venv
    • Find and wrap Claude-call entry points through LiteLLM
    • Add Langfuse instrumentation
    • Wrap scoring outputs in Instructor
    • Document the stack in reasonable-ux CLAUDE.md
    • Run /session-review before commit
    • Copy the three-dep install + LiteLLM wrap from reasonable-ux
    • Point Langfuse at a second project in the same self-hosted instance
    • Instructor for the multi-model scoring output
  4. Phase 3 Eval discipline in progress
    3/5 tasks with evidence
  5. Phase 4 Routing + cost strategy in progress
    1/7 tasks with evidence
    • Read [Anthropic prompt caching docs](https://platform.claude.com/docs/en/build-with-claude/prompt-caching)
    • Scan [LiteLLM router docs](https://docs.litellm.ai/docs/routing)
    • Configure a fallback chain in reasonable-ux
    • Enable split cache-token telemetry
    • Create a LiteLLM virtual key with a hard budget
    • Capture the win (or loss) in a vault note
  6. Phase 5 LangSmith at work / Langfuse at home (ongoing, not sequential) pending
    3 tasks
    • Scaffold the comparison note on day one of LangSmith onboarding at work
    • Fill one row per week as work surfaces each feature
    • Hard-boundary check every session
  7. Phase 6 Public artifacts (the marketability layer) pending
    5 tasks
    • Gate — 2 weeks of real Langfuse data on reasonable-ux
    • Pull the three hero numbers from Langfuse
    • Draft writeup #1 — "A solo dev's minimum-viable LLMOps stack"
    • Publish to portfolio-site
    • Share on X under @reasonequals
  8. Phase 7 Adjacent platform engineering (parallel track) deferred
    6 tasks
    • Take AWS AI Practitioner (AIF-C01) as the warmup
    • VPC / subnets / security groups
    • IAM + secrets
    • Serverless deployment — Lambda + API Gateway
    • Container deployment — ECS Fargate
    • AWS SAA (SAA-C03)