Program
Prompt Design Certification
A hands-on program for teams that want to move from prompt tinkering to testable, production-grade prompt systems with clear guardrails and evaluations.
We cover patterns, safety, and evaluation—then apply them directly to your product or internal tools with graded exercises.
Program overview · Audio
A short overview of the program: who it's for, what we cover, and how to get the most value out of it as a busy professional.
What you’ll be able to do after this program
This isn’t about one clever prompt. It’s about a repeatable way to design, test, and ship many of them.
- • Design prompts with clear roles, tasks, constraints, and examples.
- • Use few-shot examples and structured outputs (JSON, tags, fields) your systems can rely on.
- • Build golden sets and evaluation harnesses for key flows.
- • Apply safety and governance patterns without blocking progress.
- • Collaborate with PMs, designers, and legal on prompt changes.
Who this is for
- • Product, applied research, or platform teams
- • Folks already shipping features with GPTs / Gemini
- • Teams that need reliability, not just novelty
Typical contexts
- • Support assistants & triage
- • Content drafting & editing flows
- • Internal tools & analytics copilots
- • Review / QA pipelines for generated content
Curriculum at a glance
Four core modules, each with examples, exercises, and a graded project.
Module 1
Prompt foundations
- • Roles, tasks, constraints, and examples
- • Designing prompts for clarity over cleverness
- • When to use system vs. user vs. tools
Module 2
Few-shot & structured outputs
- • Designing examples that actually help
- • Patterns for JSON and schema-constrained outputs
- • Handling uncertainty and fallbacks gracefully
Module 3
Guardrails & safety
- • Policy prompts vs. heuristic filters
- • Red-teaming prompts and flows
- • Working with compliance & legal stakeholders
Module 4
Evaluation & change management
- • Golden sets, test cases, and A/Bs
- • Model-graded vs. human-graded evals
- • Versioning prompts and documenting changes
Capstone project: your own prompt & eval stack
Instead of a generic exam, we certify you on something connected to your actual product.
Each participant (or team) picks one real flow—a support classifier, content generator, QA reviewer, or similar—and builds:
- • A well-structured prompt with examples
- • A small golden set of real cases
- • A basic evaluation harness (script or notebook)
- • A one-page change log and rollout plan
How certification works
- • We review your project against a clear rubric
- • You get written feedback & suggested improvements
- • Teams receive a summary we can share with leadership
- • Optional follow-up session to review production impact
Format & logistics
Flexible enough for busy teams, structured enough to actually finish.
Schedule
- • 3–4 weeks total
- • Weekly live sessions (60–90 minutes)
- • Async exercises between sessions
Team size
- • 3–12 participants per cohort
- • Mix of PMs, engineers, designers, and ops
- • Private org-only cohorts by default
Deliverables
- • Prompt pattern library tailored to your use cases
- • Example golden sets & eval harness templates
- • Certification summary for each participant
FAQ: Prompt Design Certification
A few details teams usually ask about before enrolling.
Do participants need to know how to code?
Coding helps but isn't required. We focus on patterns, examples, and evaluation. Engineers can wire prompts into systems; non-technical folks still get a ton of value from the design and governance pieces.
Can we use our own product as the focus?
Yes—that's encouraged. We'll help you pick flows that are meaningful but not so high-risk that they slow the cohort down.
How is this different from a generic LLM course?
We stay close to the work: concrete prompts, examples, policies, and evaluations that you can plug into existing systems. Less theory, more prompts and test runs in your context.
Want your team certified on prompt design?
We run private cohorts for product and platform teams who are already shipping AI features and want a shared language for prompts, safety, and evaluation.
We'll usually start with a quick call to pick the right participants, flows, and schedule.