How do we prove model quality over time?
You will build regression-aware eval harnesses and quality dashboards that catch drift before users do.
COURSE 3 · SCALE + RELIABILITY
Ship AI systems that stay reliable in production.
Convert AI prototypes into monitored, scalable, and trusted production products.
Learn evaluation at scale, observability, structured outputs, safety engineering, deployment, multimodal systems, and career positioning.
Start
Dec 12, 2026
Format
Live mentorship + architecture clinics
Commitment
8 weeks · 4 hours/week
Eval -> Observe -> Deploy
Lifecycle coverage
End-to-End AI Product
Capstone
AWS / Azure / GCP
Cloud paths
70% overall
Passing threshold
In This Session
Everything you need to evaluate your next move
What should be monitored in production?
Latency, cost, failure classes, output schema compliance, and safety policy events become first-class signals.
How do we handle safety in real systems?
You will implement guardrails, red-team workflows, and incident-ready controls that are testable and auditable.
Can this become portfolio evidence?
Yes. The capstone is designed as a portfolio-grade artifact with architecture and trade-off justification.
What You Will Leave With
Practical outcomes, not just theory
- Create scalable evaluation systems and regression gates for release confidence.
- Instrument AI products with observability and actionable debugging telemetry.
- Enforce structured generation using schemas, validation, and repair loops.
- Deploy cloud-ready AI services with reliability, safety, and cost controls.
Certificate
Completion certificate for verified track milestones.
Capstone Project
Build and present a portfolio-ready final implementation.
Practical Labs
Hands-on exercises focused on real engineering workflows.
Assessments
Project-based evaluation with actionable instructor feedback.
Curriculum roadmap
Cohort Track
Part 1
Week 1 - Evaluation at Scale
Quality scoring pipelines and regression controls.
Part 2
Week 2 - Observability + Debugging
Tracing, logs, and failure classification for AI workflows.
Part 3
Week 3 - Structured Generation
Schema-first generation and parser-safe output guarantees.
Part 4
Week 4 - Safety Engineering
Prompt injection defense and policy-layer implementation.
Part 5
Week 5 - Deployment + Scaling
Containerization, CI/CD, and operational reliability.
Part 6
Week 6 - Multimodal Engineering
Image/text or audio/text features with structured outputs.
Part 7
Week 7 - Career Positioning
Role mapping, impact framing, and market-aligned portfolio strategy.
Part 8
Week 8 - Capstone
Ship an end-to-end production-minded AI product.
Live Calendar
Production AI Schedule by Date
Saturday and Sunday · 11:00 AM PST · 2 hours/session
Add All Sessions to CalendarSaturday
Sat, Dec 12, 2026
Upcoming
Week 1 - Evaluation at Scale
Quality scoring pipelines and regression controls.
11:00 AM PST · Upcoming
Sunday
Sun, Dec 13, 2026
Upcoming
Week 1 - Evaluation at Scale - Lab and Q&A
Hands-on implementation and feedback for week 1 - evaluation at scale.
11:00 AM PST · Upcoming
Saturday
Sat, Dec 19, 2026
Upcoming
Week 2 - Observability + Debugging
Tracing, logs, and failure classification for AI workflows.
11:00 AM PST · Upcoming
Sunday
Sun, Dec 20, 2026
Upcoming
Week 2 - Observability + Debugging - Lab and Q&A
Hands-on implementation and feedback for week 2 - observability + debugging.
11:00 AM PST · Upcoming
Saturday
Sat, Dec 26, 2026
Upcoming
Week 3 - Structured Generation
Schema-first generation and parser-safe output guarantees.
11:00 AM PST · Upcoming
Sunday
Sun, Dec 27, 2026
Upcoming
Week 3 - Structured Generation - Lab and Q&A
Hands-on implementation and feedback for week 3 - structured generation.
11:00 AM PST · Upcoming
Saturday
Sat, Jan 2, 2027
Upcoming
Week 4 - Safety Engineering
Prompt injection defense and policy-layer implementation.
11:00 AM PST · Upcoming
Sunday
Sun, Jan 3, 2027
Upcoming
Week 4 - Safety Engineering - Lab and Q&A
Hands-on implementation and feedback for week 4 - safety engineering.
11:00 AM PST · Upcoming
Saturday
Sat, Jan 9, 2027
Upcoming
Week 5 - Deployment + Scaling
Containerization, CI/CD, and operational reliability.
11:00 AM PST · Upcoming
Sunday
Sun, Jan 10, 2027
Upcoming
Week 5 - Deployment + Scaling - Lab and Q&A
Hands-on implementation and feedback for week 5 - deployment + scaling.
11:00 AM PST · Upcoming
Saturday
Sat, Jan 16, 2027
Upcoming
Week 6 - Multimodal Engineering
Image/text or audio/text features with structured outputs.
11:00 AM PST · Upcoming
Sunday
Sun, Jan 17, 2027
Upcoming
Week 6 - Multimodal Engineering - Lab and Q&A
Hands-on implementation and feedback for week 6 - multimodal engineering.
11:00 AM PST · Upcoming
Saturday
Sat, Jan 23, 2027
Upcoming
Week 7 - Career Positioning
Role mapping, impact framing, and market-aligned portfolio strategy.
11:00 AM PST · Upcoming
Sunday
Sun, Jan 24, 2027
Upcoming
Week 7 - Career Positioning - Lab and Q&A
Hands-on implementation and feedback for week 7 - career positioning.
11:00 AM PST · Upcoming
Saturday
Sat, Jan 30, 2027
Upcoming
Week 8 - Capstone
Ship an end-to-end production-minded AI product.
11:00 AM PST · Upcoming
Sunday
Sun, Jan 31, 2027
Upcoming
Week 8 - Capstone - Lab and Q&A
Hands-on implementation and feedback for week 8 - capstone.
11:00 AM PST · Upcoming
Inside the learning experience
Every session is built around implementation outcomes. These modules show exactly what you will build, practice, and carry into real projects.
Module 1
Week 1 - Evaluation at Scale
Quality scoring pipelines and regression controls.
Module 2
Week 2 - Observability + Debugging
Tracing, logs, and failure classification for AI workflows.
Module 3
Week 3 - Structured Generation
Schema-first generation and parser-safe output guarantees.
Module 4
Week 4 - Safety Engineering
Prompt injection defense and policy-layer implementation.
Module 5
Week 5 - Deployment + Scaling
Containerization, CI/CD, and operational reliability.
Session Host
Experience
25 years of IT experience across engineering delivery, quality, and modern platform transformation
Focus
AI, Automation, and Production Engineering
Deepak Kamboj
Founder and Lead Instructor
Deepak Kamboj is an AI and quality engineering mentor who helps teams move from tutorial-level learning to production-ready implementation. His teaching style combines architecture clarity, real delivery constraints, and execution patterns that engineers can apply immediately.
- Founder of DevBuild Studio with hands-on focus on modern engineering skills
- Mentors engineers across Playwright automation, agentic AI, and production architecture
- Known for practical frameworks, implementation checklists, and career-focused coaching
Where our learners and teams operate
Promptfoo
OpenTelemetry
Langfuse
FastAPI
Kubernetes
Docker
GitHub Actions
Pydantic
Learner outcomes
"This is the first program that treated reliability and observability as core AI engineering skills."
"I used the deployment module to move our AI feature from pilot to monitored production in one quarter."
"The capstone format gave me a portfolio piece that was directly useful in interviews."
Frequently asked questions
Who should take this course?Open
Engineers with prior AI agent/RAG experience who need production deployment and reliability depth.
Do we cover multimodal use cases?Open
Yes. You implement at least one multimodal feature and validate it with structured outputs.
Is there a certificate requirement?Open
You need an overall passing score and capstone submission to earn certification.
Final call
Build the skillset teams are prioritizing right now
Reserve your spot and receive your onboarding details, prep material, and implementation roadmap.