LLM Integration
LLM Integration Studio
Tool routing, structured outputs, and latency-aware prompting patterns for assistants embedded in existing products.
- Duration
- 5 weeks · hybrid
- Format
- Cohort + build weeks
- Level
- Intermediate
- Tuition (informational)
- ₩1,450,000
Program narrative
We integrate with hosted LLM APIs and local small models for guardrails. You will design JSON-first tool contracts, backoff strategies, and user-visible failure copy that is truthful rather than evasive.
What is included
- · Tool schema design workshop with OpenAPI alignment
- · Streaming token budgets with UX copy variants
- · Red-team prompts scoped to your product verbs
- · Caching layers for idempotent reads
- · Latency tracing across gateway hops
- · Mentor review of a rollout checklist
- · Playbook for deprecating a brittle prompt version
Outcomes you can demo
- · Ship a tool-first assistant flow with measurable fallback rates
- · Author honest user-facing error strings tied to real failure modes
- · Document which model versions you will freeze per environment
Mentor of record
Jonas Meier
Product engineer who shipped multilingual copilots for developer tools.
Participant questions
Are API fees included?
Small shared credits are included. Larger fine-tuning jobs are billed to your own keys.
Fine-tuning coverage?
Conceptual overview only; we focus on integration and evaluation, not dataset curation for fine-tunes.
Limitation?
We do not cover on-device tiny models for offline mobile; that is a separate hardware track.
Recent participant notes
“LLM Integration Studio’s JSON-first tool contracts stopped our frontend from guessing shapes. On-call noise dropped noticeably.”
“Red-team prompts felt uncomfortably realistic—in a useful way.”