Develop Yourself

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Last year, I quit an AI startup where I helped build a multimodal RAG system and the agent layer of a production web app. Before leaving, I designed the interview process to hire my replacement — and the results were surprising.

In this video I break down what companies actually expect from an AI engineer, and why the role is usually less about training models and more about integrating LLMs into real products.

Most “AI engineer” jobs are really full-stack developers building AI-powered systems — agents, workflows, RAG pipelines, vector databases, evaluation frameworks, and observability.

I walk through what I expected candidates to know in the interview, including:

• Structured outputs

• Evaluating when AI systems are wrong (evals)

• Observability and tracing prompts/token costs

• RAG architecture and document chunking

• Metadata and data freshness

• Why re-ranking dramatically improves retrieval quality

I also share what happened when we caught candidates cheating during the interview — and the biggest gaps I saw between AI hype and real AI engineering.

This experience ultimately led me to build the Parsity AI Accelerator, focused on teaching developers how to build production AI systems rather than just prompting chatbots.

If you’re trying to become an AI engineer or preparing for AI interviews, this video will show you what actually matters.

If you're curious about Bryan's strategy, you can apply to work with him here: 👉 Application form.

The tech job market is brutal right now. Everyone knows it.

People are sending hundreds of applications, getting ghosted, and wondering what the hell is actually going on behind the scenes of hiring.

So in this episode I sat down with Bryan, someone I met on LinkedIn and later met up with in Reno, and he shared something that honestly blew my mind.

Last year he did what most people do:

Around 250 applications over 8 months… and almost no interviews.

This year he completely changed his approach.

Instead of blasting applications everywhere, he used a targeted strategy and applied to only 58 roles.

That turned into 16 interviews across 9 companies and multiple final rounds.

Yeah… that got my attention.

In this conversation we talk about what he’s seeing on the front lines of the hiring market, including:

• Why most resumes never get seen

• What hiring managers are actually filtering for

• The mistake developers make in behavioral interviews

• Why STAR stories matter way more than people think

• The reality of DSA interviews and why speed matters

• Why applying to the “right level” can dramatically increase your chances

• And why job searching is really a game of probability

If you’ve been applying to jobs and feel like everything is disappearing into a black hole, this episode should help you understand how the hiring game actually works right now.

And honestly, Brian’s story proves something important:

You don’t need hundreds of companies to say yes.

You just need one

In 2026, you can’t “avoid LinkedIn” and expect to get hired BUT you can't use it like 2023.

In this episode, I break down the exact LinkedIn + resume strategy I’d use today to maximize recruiter inbound, increase your surface area for luck, and stop making the most common mistakes that quietly kill your chances.

We cover:

• Why “Aspiring Junior Developer” and “Open to Work” often backfire

• How to make your first visible experience look software-related (even if you’re career-switching)

• The keyword/tech-stack problem that makes you invisible in recruiter search

• A simple formula to improve your resume

• Why “learn in public” is optional now—and what to do instead

• The fastest way to hit 500+ connections (without cringe networking)

• The 80/20 application approach: when to “Easy Apply” vs when to go aggressive

• Messaging tactics that stand out in a world of AI-generated slop

• A realistic volume target (and what to change if you’re getting zero responses)

If you want a practical plan to start getting interviews again—this is it.

Brian sits down with Fardeen Khimani, a 21-year-old Georgia Tech ML student and co-founder of Rounds, to talk about why technical interviews are broken and why AI just made it worse.

They cover why LeetCode is dying, why companies have no idea how to respond, and what skills actually matter now. Fardeen's take: if AI can pass an interview that maps to the real job, just hire the AI.

Find Fardeen: linkedin.com/in/fardeenkhimani

AI didn’t kill software jobs.

But it did throw a grenade into the hiring funnel.

In this episode, I break down 8 harsh truths about getting hired as a developer in 2026 — and none of them are the feel-good LinkedIn advice you’re used to hearing.

• Why vibe coding isn’t a career

• Why no one cares about your certificate

• Why your portfolio probably doesn’t matter

• Why full stack is now the baseline

• Why AI productivity claims are mostly nonsense

• Why waiting until you feel “ready” is killing your momentum

• Why titles matter more than people admit

• And why hiring is broken — but not hopeless

This isn’t theory. I’m sharing what I’ve seen as a hiring manager, what I’ve seen in interviews, and what I’ve seen work for developers I’ve mentored.

The market isn’t dead.

But the rules have changed.

If you want to land your first job — or level up in this AI-first world — you need to understand what actually matters now.

If you’re serious about switching careers and becoming a software developer, go to parsity.io or schedule a chat using the link in the show notes.

Disclaimer: this episode is my thoughts on coding bootcamps and online education and where Parsity is going in the future.

If you're interested in either of the programs I mentioned in this you can check them out here:

Parsity AI Accelerator

Full Stack Accelerator

Should you get a computer science degree, enroll in a coding bootcamp, or teach yourself how to code?

You’re probably not going to love the answer… but it depends.

In this episode, I shares my unfiltered, experience-backed take after working with hundreds of aspiring developers and hiring developers myself.

Let's breaks down what actually matters when trying to land your first software job — and where each path (college, bootcamp, or self-taught) helps or hurts.

• Why a college degree might help… but often not for the reason you think

• When bootcamps give you an edge — and where they fall short

• The uncomfortable truth about the “self-taught developer” myth

• How hiring really works at startups vs big tech companies

• Why fundamentals and computer science matter more later in your career

• How AI is changing the skills new developers need to stay employable

• The role of structure, accountability, and mentorship in actually getting hired

If you’re trying to break into software development and feeling overwhelmed by all the options, this episode will help you choose a path based on your time, money, learning style, and career goals — not hype.

If you are considering a coding bootcamp program, I encourage you to consider Parsity. Apply Here.

What if I had to break into tech today… with no degree, no connections, and a completely unrelated job?

In this episode, I sit down with entrepreneur and self-taught developer Jeremy “Smitty” to map out exactly how we’d do it if we were starting from zero in 2026.

We walk step-by-step through a realistic path from beginner to hireable — not theory, not hype, but the practical moves that actually work in today’s market.

We cover:

• How to choose what to learn (without wasting years)

• The fastest way to build real, job-ready skills

• How to escape tutorial hell for good

• When you’re actually ready to apply for jobs

• How to create experience before anyone hires you

• The smart way to network when you don’t know anyone in tech

• Why AI isn’t the career killer people think it is

• The mindset shift that separates people who make it from those who quit

If you’ve ever thought:

“I want a tech career, but I don’t know where to start”

or

“I’m stuck in a job that has nothing to do with coding”

This episode gives you a clear, actionable roadmap.

You don’t need to be special.

You don’t need a CS degree.

You just need the right plan — and the consistency to follow it.

Shameless Plugs:

1. Become an AI engineer. In 45 days, you'll learn the specific skills and technologies to transition from full stack to AI. We use project-based-learning and the teach-back method to accelerate your learning. Apply here. 

If you're a CTO or engineering manager, this is the program your team needs BEFORE you drop 200K+ on an AI engineer. Reply "AI" to learn more about how we can make your roadmap a reality.

2. Become a hireable software engineer in 2026. Follow a proven system to go from 0 to HIRED with 1 on 1 mentorship and project-based-learning. Take the self-assessment test here to see if you're ready to join.

The hiring bar for junior developers has changed, and pretending it hasn’t will only slow your career. 

Let's break down a simple strategy to beat the “no experience” trap: 

Ship a small product you intend to sell, get one or two real users, and use those lessons to tell stronger stories in interviews. Instead of another tutorial portfolio, you’ll learn to show autonomy, reliability, and ownership—the exact traits teams are optimizing for in tighter markets.

By the end, you’ll know how to replace vague “potential” with proof of autonomy: shipped features, hard-earned trade-offs, and stories that map directly to the realities of modern teams.

Resources:

Side project planner: https://docs.google.com/document/d/1uJ5Bom0WmS410K5B2m5TkbZ7d1G9BdTaX4nKprYschI/edit

Side project video: https://youtu.be/2TWioJCIaxE

Send us a text

Shameless Plugs

🧑‍💻 Free 5 day email course to go from HTML to AI

🤔 Got a question you want answered on the pod? Drop it here

Apply for 1 of 12 spots at Parsity - Learn to build complex software with AI integrations.

AI Bootcamp - for software developers who want to be the expert on their team when it comes to AI

AI is writing more code than ever, layoffs are everywhere, and it feels like software careers might be disappearing. In this episode, we explore why that narrative is misleading—and what’s actually changing in tech.

We break down why learning to code still matters, how to use AI without becoming dependent on it, and which core skills will help you stay relevant as the industry evolves. If you’re trying to make sense of the noise and figure out how to move forward in software development, this episode is here to help you navigate what’s next.

If you want to join our next cohort to learn AI through project based learning - sign up here: https://parsity.io/ai-dev

Send us a text

Shameless Plugs

🧑‍💻 Free 5 day email course to go from HTML to AI

🤔 Got a question you want answered on the pod? Drop it here

Apply for 1 of 12 spots at Parsity - Learn to build complex software with AI integrations.

AI Bootcamp - for software developers who want to be the expert on their team when it comes to AI