Bootcamps Curriculum Mentors Pricing Testimonials FAQ Corporate Contact Apply now Sign in
Agentic AI Bootcamp · Cohort 01 — Starts June 4, 2026
--DAYS
:
--HRS
:
--MIN
:
--SEC

Build real AI agents.
Engineer the future.

For developers who already use LLMs and want to build, evaluate, and deploy production-grade AI agents.

RAG Pipelines AI Agents Multi-Agent Systems MCP LangGraph LangSmith Guardrails Evaluation Deployment Demo Day Spec-based Development

COHORT 01 — STARTS June 4

5 weeks. 4 deployed agents. One live demo.
Drop your email — Reza will reach out personally.

No commitment. No spam.

Ready to apply?→

Information is free. Guidance, structure, and accountability are the new premium.

200+
Professionals trained
4+
Projects you ship
1:1
Expert feedback
TWO WAYS WE WORK WITH YOU
01 — LEARN

We train you
to build agents.

For individual developers and engineering teams. You learn by building real agents — on your stack, against real problems. 5-week bootcamp or custom corporate program.

  • ✦ Bootcamp for individual developers
  • ✦ Private cohorts for engineering teams
  • ✦ Hands-on — every session ends with shipped code
  • ✦ 200+ professionals trained this way
or contact us for team training
02 — BUILD

We build agents
for you.

For companies that want to go agentic — without waiting for their team to learn first. We design, build, and deploy production agents for your SDLC or your product. You tell us the problem.

  • ✦ SDLC agents — automate your dev workflow
  • ✦ Product agents — ship agentic features to customers
  • ✦ Built on your stack, deployed to your infrastructure
  • ✦ Production experience — we've done this at enterprise scale
Talk to Reza →
No sales team. Direct conversation.
What you'll build

You don't learn AI.
You build systems.

Every week ends with a real project — graded, reviewed, and shipped. Not notes. Not a certificate of watching.

WEEK 1
Prompt-Powered
CLI Tool
  • ✦ Multi-step prompt chains
  • ✦ Structured JSON output
  • ✦ Model fallback & error handling
  • ✦ Written design rationale
WEEK 2
Production RAG
Assistant
  • ✦ Ingest your own documents
  • ✦ ChromaDB vector store
  • ✦ Cited answers
  • ✦ RAGAS evaluation scores
WEEK 3
Agent with MCP
& Tracing
  • ✦ RAG system wrapped as MCP tool
  • ✦ Agent reasons over your docs
  • ✦ LangSmith tracing
  • ✦ Failure diagnosis submitted
WEEK 4 · CAPSTONE
Multi-Agent System
· Live URL
  • ✦ LangGraph supervisor routing
  • ✦ 10+ eval test cases
  • ✦ FastAPI + Railway deployment
  • ✦ Submit a live URL
The problem

Most AI courses stop right
before reality begins.

01
They teach demos, not systems
You build a chatbot that works in a notebook. Then you try to deploy it and everything breaks.
02
They ignore evaluation entirely
No metrics. No tracing. No way to know if your agent is actually working or just confidently wrong.
03
They never show production failure
Real systems fail. Handling that gracefully — guardrails, fallbacks, observability — is never taught.
04
Deployment is an afterthought
Most courses end with "nice work." We end with a live URL, an eval report, and a Demo Day presentation.
If it's not deployed, evaluated, and observable — it doesn't count.
Your instructor

Built by someone who ships —
not just teaches.

Reza Ahmadi
Reza Ahmadi, Ph.D.
Principal AI Engineer · Professor, Queen's University
✦ Builds and ships production AI systems in industry daily
✦ Trained 200+ professionals across organizations on AI engineering
✦ Professor at Queen's University School of Computing
✦ Ph.D. in Computer Science
↗ LinkedIn Profile
Course syllabus

5 weeks. Real skills.
Shipped projects.

Thu 7–9 PM ET · Live Async labs · 3–4 hrs/wk Graded project each week Evaluation in every assignment

AI Engineering Bootcamp — Cohort 01

5 weeks Live online Starts June 4 Thu 7–9 PM ET Sessions recorded Labs ~3–4 hrs Python or TS required ↓ Download Syllabus
—
Kickoff — Onboarding & Dev Environment Setup
Tools, repos, API keys, Python environment, first LLM call
Live session
W1
Week 1 — Advanced Prompt Engineering & API Patterns
Production prompt design · structured outputs · model selection · cost vs quality tradeoffs · Anthropic SDK + OpenAI · extended thinking · prompt caching
1.1
Lecture + Live Demo — Production prompt engineering
Model selection, context window strategy, temperature tradeoffs, system prompt design · Anthropic SDK + OpenAI SDK side by side · extended thinking for complex reasoning · prompt caching for cost reduction
Lecture
1.2
Assignment — Build a prompt-powered CLI tool
Multi-step prompt chains, structured JSON output, model fallback, error handling · written design rationale: what you built, key decisions, what you'd change
Assignment
W2
Week 2 — RAG: Retrieval-Augmented Generation
Embeddings · vector databases · chunking strategies · retrieval pipelines · RAGAS evaluation
2.1
Lecture — How RAG works end-to-end
Embeddings, semantic search, chunking strategies, retrieval quality tradeoffs
Lecture
2.2
Demo — Build a RAG pipeline live
Ingest a PDF, embed it, store in ChromaDB, query it, return cited answer
Lecture
2.3
Assignment — Build a RAG app over your own documents
Groups of up to 5 · ingest your own docs · ChromaDB vector store · cited answers · Pure Python or LlamaIndex · run RAGAS eval · analyze your lowest score, fix it, re-run · written rationale per person
Assignment
W3
Week 3 — AI Agents, Agentic Design Patterns, MCP & Claude
Agentic loops · function calling · Reflection · Planning · Model Context Protocol · Claude Code · Kiro · hooks · LangSmith tracing
3.1
Lecture — Agents, agentic design patterns & MCP
ReAct loops, function/tool calling, Reflection pattern (agent critiques its own output), Planning pattern (task decomposition), MCP architecture, connecting MCP servers
Lecture
3.2
Demo — Claude Code & Kiro: agentic IDEs, hooks & MCP wiring
Claude Code autonomous coding loops, hooks, and permissions · Anthropic invented MCP — Claude Code is its primary client · Kiro spec-based development · connecting MCP servers in agentic IDEs
Lecture
3.3
Assignment — Build an agent that calls your RAG system via MCP
Wrap your Week 2 RAG app as an MCP tool · agent reasons over your documents · cited answers · add LangSmith tracing · submit a trace showing one failed query and your diagnosis · fallback implementation provided if needed
Assignment
W4
Week 4 — Multi-Agent Systems, Production & Deployment
LangGraph · multi-agent orchestration · supervisor/subagent routing · safety & guardrails · Claude as evaluator/judge · prompt caching in workflows · observability · Railway deployment
4.1
Lecture — Multi-agent systems & production agentic software
Supervisor/subagent routing, shared state, multi-agent LangGraph workflows, safety guardrails, prompt injection defense, hallucination control · Claude as evaluator/judge in eval harness · prompt caching for production cost control · observability, Railway + FastAPI deployment
Lecture
4.2
Demo — Refactor your agent into a LangGraph workflow
Retrieve → reason → respond nodes · conditional retry on low confidence · run eval test cases · observe cost and latency per node
Lecture
4.3
Demo — Build a multi-agent research assistant
Supervisor agent routes to specialist subagents: search agent, RAG agent (from Week 2), critic agent · shared LangGraph state · Reflection loop · critic flags weak outputs and re-routes for revision
Lecture
4.4
Assignment — Orchestrate, evaluate, and deploy your agent
Refactor Week 3 agent into LangGraph workflow · add supervisor routing · eval harness with min 10 test cases · wrap as FastAPI · deploy to Railway · submit live URL
Assignment
W5
Week 5 — Demo Day
Present your live deployed agent · walk through architecture · defend your decisions · get expert feedback
5.1
Demo Day — Live group presentations
10 minutes per group · live demo of your deployed app · architecture walkthrough · show your eval scores · defend your design decisions · Q&A with mentors · graded after the session
Assignment
+
Also included with every cohort
Weekly Q&A with mentors · TA office hours · guest tech talks · career & LinkedIn session · private Discord community · completion certificate · Credly digital badge for LinkedIn
Included
↓ Download full curriculum
COHORT 01 · June 4, 2026
You've seen the curriculum. Ready to build?
How it works

From API calls to production —
in 5 weeks.

No intro content. No passive watching. You build production-grade systems, ship them, and get reviewed by working engineers.

01
✦

Register & join your cohort

Apply, get accepted, and join a cohort of serious AI builders.

02
✦

Learn through live sessions

Weekly live classes taught by your instructor — a working AI engineer and CS professor.

03
✦

Deliver real projects

Each module ends with a graded project. Build RAG apps, agents, and full pipelines.

04
✦

Get expert feedback

Detailed code review and written feedback on every submission. No auto-graders.

Why AiBricks

Built for engineers,
not beginners.

Every decision made for developers who already know how to code and want to build real AI systems — not watch intro videos.

Cohort-based learning

You learn with a group, not alone. Accountability, peer reviews, and shared momentum built in.

Graded projects, real feedback

Every project is marked by an expert — not an LLM. Expect detailed, honest critique.

Taught by a practitioner

Your instructor is a CS professor and industry AI engineer. Theory meets real production experience.

No fluff, no filler

Deliberately short curriculum. Only what matters. Every hour spent is an hour that compounds.

Small cohorts only

Max 100 students per cohort. Real access to the instructor, not just a Slack channel.

Private Discord community

Cohort-only Discord server — ask questions, share progress, and get help between sessions. Active 24/7.

Anthropic API credits included

API credits provided for all lab work — no out-of-pocket API costs for coursework. Additional usage beyond labs at student's expense.

Portfolio on graduation

Leave with 4+ shipped projects — RAG apps, agents, deployed APIs — ready to show employers.

Your instructors

Learn from people
who ship in production.

Not content creators. Working AI engineers with real industry experience. Each cohort also includes guest talks from leading figures in AI engineering and agentic AI.

Dr. Reza Ahmadi
Reza Ahmadi, PhD
Principal AI Engineer · Professor, Queen's University

With 15+ years of industry experience, Reza works at the intersection of industry and academia — building production AI systems by day, teaching software engineering at Queen's. He has trained 200+ professionals in AI engineering. His production work includes SDLC agents for developer productivity, deployed at scale in enterprise.

LLMs & Agents Production AI MLOps ↗ LinkedIn
Sami Riaz
Sami Riaz
AI Engineer in Industry · McGill University Alumni

Sami brings 7 years of professional software engineering experience to AiBricks. Currently working as an AI engineer in industry with a strong foundation from McGill University.

AI Engineering Software Engineering 7 Years Industry ↗ LinkedIn
?
Guest Speakers
Leading figures in AI engineering & agentic AI

Each cohort includes exclusive guest talks from practitioners at the frontier of AI engineering. Names to be announced.

Pricing

One cohort. Two options.
Zero fluff.

Cohort 01 is priced to get serious people in the room. Price increases for Cohort 02.

COHORT 01 PRICE
Early access
$1,097 USD
one-time · limited seats · all sessions recorded
Regular price $1,997 USD
  • ✦ Ship 4 real agents — RAG pipeline, autonomous agent, multi-agent system, deployed app
  • ✦ Get expert written feedback on every project you submit
  • ✦ Walk away with a portfolio of production-grade work you can show
  • ✦ Live sessions with Q&A — every session recorded and shared within 24hrs
  • ✦ Anthropic API credits included — no extra cost for labs
  • ✦ Private cohort community — peers building the same things in real time
  • ✦ Verified completion certificate + Credly badge for your LinkedIn
✓
Not satisfied after Week 1?Email us within 7 days for a full refund — no questions asked.
Payment plan
$365
USD × 3 months
$1,095 USD total · split over 3 months
Same full access. First payment due at enrollment. Remaining two payments billed monthly. No hidden fees.
  • ✦ Everything in the full plan
  • ✦ Split into 3 monthly payments
  • ✦ No interest, no penalty
Cohort 01 · Regular price $1,997 USD from Cohort 02 onwards
TEAMS & ORGANIZATIONS
Training your whole engineering team?
Custom cohorts available for companies. Same curriculum, delivered privately for your team — on your schedule.
Get in touch →
What people say

What people say.

Anonymous feedback from Queen's University students, and direct feedback from industry professionals after sessions with Reza.

"Even I was able to run the AI analysis today — and I'm not technical at all. I love it! Thanks Reza for the knowledge transfer."

— Rena · Engineer

"I'm finding the tool we made during the session more useful than Kiro for initial investigations right now. Hats off Reza for however you did that. I'd love to get a deeper understanding of how it works."

— James · Engineer

"Obviously cares a lot about the course. Quick to respond to questions. Assignments are well-written and unambiguous. The course is not very stressful."

— Software Engineering Student at Queen's University

"Great instructor — cares very much about the content. Well organized. Interesting material."

— Software Engineering Student at Queen's University

"Super helpful content, presented in a clear manner."

— Software Engineering Student at Queen's University
FAQ

Common questions.

Who is this for?
This is an advanced bootcamp for developers who have already used LLMs — called an API, built a toy project, or experimented with ChatGPT. You write Python or TypeScript daily and you're ready to go beyond tutorials and build systems that work in production. If you've never written code before, this is not the right course. Time commitment: 2 hrs live Thursdays 7–9 PM ET plus 3–4 hrs async lab per week. All sessions recorded.
What if I'm not satisfied?
Full refund if you email us within 7 days of the Week 1 session. No forms, no explanations required. We've made this easy on purpose — we want serious learners, not reluctant ones.
What if I miss a live session?
Every session is recorded and shared with the cohort within 24 hours. You won't fall behind. Labs are async and due before the next session.
Do I need a machine learning background?
No. This is an AI Engineering bootcamp — you'll learn to build systems that use AI, not train models. Python or TypeScript basics are all you need to start.
How does the payment plan work?
First payment ($365 USD) is due at enrollment and gives you immediate full access. Payments 2 and 3 are billed automatically each month via Stripe. All 3 payments are committed at enrollment — this is a structured plan, not a subscription you can cancel.
Do I get a certificate?
Yes. Students who complete all projects receive an AiBricks AI Engineering certificate. Cohort 01 graduates will also receive a Credly digital badge suitable for LinkedIn.
Is payment handled securely?
Yes. All payments are processed via Stripe — we never see or store your card details. You'll receive a Stripe receipt immediately after payment.
Can I show my projects to employers?
Yes — that's the point. After the cohort ends, your project repos become yours to make public. Your Week 4 capstone is a live deployed app with a real URL, LangSmith traces, and an eval report. You can link it directly on your resume and LinkedIn as a production-grade AI engineering project.
What is Demo Day exactly?
Demo Day is Week 5 — you present your Week 4 capstone project live to the cohort. You show the running app at its live URL, walk through the architecture, show your LangSmith traces, and defend your design decisions. It's 10 minutes per student with Q&A. This is your capstone — not a separate project, but your best work fully polished and deployed.
For Companies

We train your team.
We build your agents.

Two ways to work with us — or both. Either way, you leave with something real.

TRAIN

Corporate Training

Your team learns by building a real agent for your own process or product — hands-on, on your stack. They leave capable of building and maintaining agents independently.

"Even I was able to run the AI analysis today — and I'm not technical at all." — Rena, Engineer
BUILD

Agent Development

We design, build, and deploy production agents for your company — SDLC automation or product features. Built on your stack, your infrastructure. You tell us the problem, we ship the solution.

"The tool we made during the session is more useful than Kiro for investigations." — James, Engineer
Ready to talk?
Reza responds personally. No sales team, no pitch deck.
Get in touch →

Ready to build seriously?

Cohort 01 is forming now. 95 spots remaining out of 100.