Become the AI engineer companies want in 45 days
Get the skills, the portfolio piece, and the interview confidence to land an AI engineering role or lead AI at the job you have now. Self-paced, built around a full-time job, no ML degree or math required.
Here's everything you get:
- A production AI system you built yourself. RAG, agents, evals, and observability, shipped and deployed. Your proof you can do the job.
- A mentor on your code every week. Engineers who have shipped this in production tell you exactly what to fix, so you stop guessing.
- Mock interviews and resume reviews. Walk into AI interviews already knowing the questions and the answers.
- The skill that gets you in the room. Explain your architecture to a CTO and become the person your team turns to on AI.
- Capstone built on your real work. Use a project from your job, so what you show off is also useful on Monday.
- Monthly guest speakers, office hours, and Slack. A network of engineers building this too.
$1,997 one time. Other AI bootcamps charge $5,000 to $15,000 and want you to move to SF or NY. Backed by a U.S. Department of Labor grant. Official Claude partner.
Do week one. Not what you wanted? Full refund. No payment to apply. The call is 15 minutes and not a sales pitch.
Got questions? See how it works
Curious what "AI engineer" actually means day to day? We walk through the exact path, step by step: RAG, production agents, evals, and observability.
We're all working software developers. Many of us have families, and live classes at a fixed hour do not fit everyone's life.
So the program is self-paced from here on.
I'm making changes to the self-paced program, including personal mentors, so everyone feels the pressure to succeed. You move at your own speed, with a mentor checking your work and the same people reviewing your code.
— Brian, founder of ParsityApply for self-paced.
- Full curriculum, start whenever you want
- 5 one-hour sessions with a mentor
- Weekly homework with written feedback
- Capstone project with feedback
- Monthly guest speakers and office hours
- Slack access
Do the first week. If it is not what you wanted, I will give you your money back. Put in the work, and if it is not worth it, tell me at the end of week one and I refund you in full. I do not take people's money and not deliver.
Your employer can probably pay for this. We provide invoices and a training budget request template. A lot of students go this route and it works.
Outside the US? We do purchasing power parity pricing. Email assistant@parsity.io and we will sort it out.
What everyone else charges
| Cost | Format | |
|---|---|---|
| Parsity self-paced | $1,997 | Remote, start anytime |
| Other AI bootcamps | $5,000–$15,000 | Most require relocating to SF or NY |
| CS or AI degree | $20,000–$60,000 | 18–24 months |
We are not cheaper because we cut the curriculum. We are cheaper because there is no campus, no admissions department, and no sales floor. The money goes to engineers who review your code.
Want to see the whole thing first?
Every project, every technology, week by week. I will send it to your inbox and then leave you alone unless you want to hear from me.
No spam. Unsubscribe whenever.
The skills gap
There's a massive difference between using AI tools and building AI systems. Most developers are stuck on the wrong side of that line.
They've experimented with ChatGPT. Called an API. Maybe built a demo. But companies increasingly need developers who can implement production AI systems: RAG pipelines, agent architectures, LLM orchestration, and observability.
RAG and AI agents are becoming foundational engineering skills. The engineers who can build these systems are the ones companies cannot find.
Companies are not short of applicants for these roles. They are short of engineers who have actually built these systems, which is why the listings sit open for months.
The fix: six focused weeks on the exact stack companies are trying to hire for.
Short call, 15 minutes. Not a sales pitch. I have done about 1,000 of these over the last 5 years, and if it is not the right fit I will tell you.
What you learn
RAG, agents, orchestration, and production LLM systems. This is the stack companies are hiring AI Engineers, Applied AI Engineers, LLM Engineers, AI Product Engineers, and AI Systems Engineers for.
RAG Architecture
Build it from scratch: embeddings, chunking strategies, vector storage, semantic search, retrieval, generation. Understand the math and the tradeoffs that separate production systems from demos.
Vector Databases
Hands-on with Pinecone, one of the most popular choices for production RAG systems. Learn similarity search, indexing strategies, and how to optimize retrieval quality.
Agent Architecture
Design multi-agent systems with specialized agents, routing logic, and structured outputs. Build agents that actually work in production, not agents that work once in a notebook.
LLM Observability
Performance monitoring, usage tracking, cost management with Helicone. Know what's happening inside your AI systems and catch problems before users do.
What developers are saying
A student moved to the next interview round just from mentioning he was learning this. Another built the first AI proof of concept his company ever shipped.
"This course has taken me from wondering how working with RAG, agents, and LLMs work, to now building these things myself, with the understanding of exactly what's happening. It has really empowered me to learn by building things."
"Brian's course cut through so much of the AI hype fog for me. Not only did he do an amazing job scaffolding AI literacy onto my full-stack background in general, he provided super practical pathways into implementing AI within very real world circumstances. This is one of those courses that'll keep on giving for me."
"The course was brief but jam-packed with so much information. Brian has a great teaching style that keeps you engaged and encourages discussion. The course flew by, but I feel very empowered to build my own AI apps with RAG (and be able to explain how it works)."
"I truly enjoyed my time in this course. It was a privilege to get to learn from Brian and from the other students. I loved the hands-on experience we gained building robust RAG pipelines. I highly recommend this course to anyone who wants to grow in their skills with AI development."
"I thought I had a solid understanding of AI and LLMs going into Parsity's program, but finishing it made me realize I was only scratching the surface. Getting a hands-on walkthrough of how these systems actually work and going beyond prompting was a complete game changer. If this is something you're even 10% interested in, give him a call. I did, and it's already proving to be one of the best decisions I've ever made."
"This was my first bootcamp after almost 10 years in the industry and I have to say that it exceeded my expectations. Brian is a great communicator and I felt like I got the inside scoop from a colleague working in the field of AI engineering. I now have the confidence and skills to go out into the world and build awesome agentic RAG apps."
Watch him actually teach this
Real videos from Brian's YouTube channel (10,400+ subscribers) — not a highlight reel, the actual RAG/agent teaching.
Is this right for you?
This program positions you for roles like AI Engineer, Applied AI Engineer, LLM Engineer, and AI Product Engineer. But it requires serious commitment.
This is for you if:
- You're a working developer who can already build and deploy apps
- You want the pay and the offers that come with AI implementation skills
- You're willing to commit six weeks of focused work, not passive watching
- You want production AI projects that demonstrate genuine engineering capability
This is not for you if:
- You haven't built a full-stack app before
- You want a certificate without doing the projects
- You're not willing to record yourself explaining your work out loud
What's included
Everything you need to go from "I've experimented with AI" to "I can build and ship production AI systems."
Self-paced includes:
- Full curriculum. RAG from scratch, vector databases, agent architecture, LLM observability
- Weekly homework with written feedback from a mentor who has shipped AI systems
- 5 one-hour sessions with your mentor
- Capstone project with written feedback
- Mock interviews, resume reviews, and career positioning, so you walk into AI interviews ready
- Monthly guest speakers, office hours, Slack
Get hired. Get paid more.
AI skills carry a wage premium. PwC's 2025 AI Jobs Barometer puts it at 56% over peers in the same role. This program is built to put you on the right side of that number.
Walk into interviews ready
- Mock interviews on RAG, agents, and system design, so the real ones feel familiar
- Resume reviews that turn your new projects into the first thing a hiring manager reads
- A deployed capstone you can demo live, instead of talking about side projects
Step into bigger roles
- Qualify for AI Engineer, Applied AI Engineer, LLM Engineer, and AI Product Engineer roles
- Explain your architecture to leadership and become the person your team turns to on AI
- Negotiate from strength with production AI work on your resume
Communicating to leadership
Every week you record yourself explaining what you built, as if you were presenting to a non-technical CTO. Then you get notes on it.
Developers from this program who moved into AI lead roles say the same thing: being able to walk leadership through their decisions, without making anyone feel stupid, was the difference. Nobody else trains this. We do.
Frequently asked questions
Do I have to get on a call to sign up?
No. The price is on this page and you can apply right now. If you want to talk to me first, book a call. Most people who join do talk to me first, but that is because they want to, not because I make them.
What level do I need to be?
Any level, junior to senior. You need to be able to build and deploy apps. You don't need AI experience. You'll have it when you're done.
How is this different from other programs?
Most programs teach you to call OpenAI's API and call it AI engineering. We teach the architecture companies are actually hiring for: RAG from scratch, agent systems, LLM orchestration, vector databases, production patterns.
How much time does this take?
A meaningful amount. The people who get the most out of it treat it like a serious commitment for six weeks. They come out with skills and a portfolio that compound for years.
Why the communication module?
Engineers who can build and communicate are worth far more than engineers who can only build. Developers who've moved into AI lead roles say the same thing: being able to explain their work to leadership was the difference. Nobody else trains this. We do.
Can my employer pay for this?
Yes. We provide invoices and training budget request templates. Many companies have L&D budgets specifically for upskilling engineers.
What if I don't find it valuable?
Do the first week, and if it is not what you wanted, email me at the end of it and I will refund you in full. You have to actually do the work, but that is the only condition. I don't take people's money and not deliver. Contact assistant@parsity.io and we will take care of it.
I'm outside the US, is pricing adjusted?
Yes. We offer purchasing power parity pricing for international students. If you're in a country with different economic conditions, reach out to assistant@parsity.io and we'll work with you.
45 days from now you can be the person your team asks about this.
You already have the hard part. You can build and deploy software. What you are missing is a specific stack that companies are hiring for and cannot fill.
Self-paced starts whenever you want.
Want to talk first? The call is 15 minutes and 100% not a sales pitch. I have done about 1,000 of these over the last 5 years. Money-back guarantee: do the first week, and if it isn't what you wanted, you get a full refund. Questions? assistant@parsity.io
