Forward Deployed Engineering Bootcamp

Engineer ReAct agents with structured tracing, decision auditing, memory, and termination control.

Implement perceive-think-act loops, planning agents, reflection, and tool-use architectures.

Build a production-grade agent harness and unpack what makes Claude Code powerful beyond the model.

Serve production LLMs with predictable latency, lower cost, and benchmarks you can defend.

Master GPTQ, GGUF, QLoRA, AWQ, prefill, decode, KV caching, and speculative decoding.

Measure TTFT, inter-token latency, throughput, and the economics of each deployment choice.

Build retrieval that actually reasons, not a single vector lookup bolted onto a prompt.

Add semantic caching and knowledge graphs for hybrid memory that stays fast and grounded.

Scale your pipeline to potentially millions of documents without it falling over.

Design multi-agent systems with clear topology, communication protocols, and operational judgment.

Implement orchestrator-worker, hierarchical, debate, and handoff workflows for real use cases.

Connect agents with MCP and A2A, and evaluate when single-agent systems are the better choice.

Ship agent systems with measurable quality, layered safety, and production-ready eval loops.

Implement Llama Guard, NeMo Guardrails, validation, and prompt-injection defenses.

Build trajectory-based evals with golden tasks, partial-credit grading, and LLM-as-judge scoring.

Split your product into independent services (app, inference, retrieval, workers) that each scale on their own.

Wire a React frontend, Node.js backend, and AI backend into one seamless product.

Take a project from an empty repo to a live, deployed product that handles real traffic, not a demo.