RT
Training

Agentic engineering for the whole team.

Complete agentic engineering training, from the agent loop to fine-tuning, adapted to your stack and your rules.

A team in a workshop around laptops, with a whiteboard of diagrams behind them

What the program covers.

  • Agentic engineering
  • Harness engineering
  • Context engineering
  • AI-native SDLC
  • Spec-driven development
  • Multi-agent orchestration
  • Subagents
  • Agent skills
  • Hooks
  • MCP
  • A2A
  • AG-UI
  • Agentic RAG
  • GraphRAG
  • Hybrid search
  • Reranking
  • Evals
  • LLM-as-judge
  • Trajectory evals
  • Guardrails
  • Human-in-the-loop
  • Prompt injection defense
  • AgentOps
  • LLMOps
  • OpenTelemetry GenAI
  • AI gateway
  • Model routing
  • Prompt caching
  • Context compaction
  • Computer use
  • Fine-tuning
  • LoRA / QLoRA
  • RFT
  • Distillation

Curriculum.

  • Harness fundamentals

    • Agent loop and ReAct
    • AGENTS.md and CLAUDE.md
    • Skills, hooks and subagents
    • Harness versus model
  • Context engineering

    • Context rot and compaction
    • Progressive disclosure
    • Prompt caching
    • Cross-session memory
  • RAG in production

    • Chunking and embeddings
    • Hybrid search and reranking
    • GraphRAG
    • Agentic RAG
  • Tools and protocols

    • MCP: servers and OAuth
    • A2A between agents
    • AG-UI
    • Tool design
    • Computer use
  • Multi-agent orchestration

    • Planner, executor and verifier
    • Topologies and handoffs
    • Deterministic workflows
    • Parallelism with verification
  • Evals

    • Golden datasets
    • LLM-as-judge
    • Trajectory evals
    • Eval gates in CI
  • Guardrails and security

    • Prompt injection
    • Lethal trifecta
    • Sandboxing and permissions
    • OWASP Top 10 for LLMs
  • AgentOps: observability and cost

    • Tracing with OpenTelemetry GenAI
    • Token budgets
    • Model routing
    • AI gateway
  • Model customization

    • Fine-tuning with LoRA and QLoRA
    • SFT, DPO and RFT
    • Distillation
    • When not to fine-tune
  • Spec-driven development

    • Spec, plan and tasks
    • Specs versioned in the repo
    • Verifiable acceptance criteria
    • Reviewing agent-generated PRs
    • AI-native SDLC
  • AI governance

    • Data privacy for LLMs
    • EU AI Act
    • ISO/IEC 42001
    • Usage policy per team

Formats.

  1. 1 day

    Executive workshop

    For technical and product leadership. Where AI pays off, where it adds risk and how to decide.

  2. 3 days

    Technical immersion

    For engineers. Harness, MCP, evals and orchestration applied to a real repository.

  3. 8 weeks

    Full agentic engineering program

    The whole team, from developers to leadership, builds the company harness with our mentoring and ends the program with it running in production.

We shape the track around your stack.

A quick team assessment, the right modules and a real project as the final deliverable.

Talk to us