Maddy Zhang

Had a wonderful time at ‪@Microsoft‬ Build 2026! Across the announcements, demos, and conversations, the through-line was impossible to miss: agentic AI is no longer just a concept but is now permanent infrastructure.

A few of the announcements that stuck with me:
- Microsoft Scout: built on OpenClaw, this is an always-on agent that runs across Teams, Outlook, OneDrive, and SharePoint without waiting for a prompt. Microsoft is calling this a new category: "Autopilots." It proactively surfaces risks, handles coordination, and keeps work moving in the background.
- Seven new MAI models, a Surface RTX Dev Box capable of running 120B-parameter models locally, and GitHub Copilot moving to a full desktop agentic app.
- Majorana 2: Microsoft's next-gen quantum chip, with 1,000x better qubit reliability than the previous generation and a mean qubit lifetime of 20 seconds. Microsoft now expects a scalable quantum computer by 2029, cutting its original timeline in half.

In addition, I was lucky enough to watch both Satya Nadella (CEO Microsoft) and Kevin Scott (CTO Microsoft) talk in smaller sessions. And I was pleasantly surprised when I wandered over to the ‪@AMD‬ booth and saw myself on their screen!

Some other fun highlights:
- I ran into Peter Steinberger: it was so surreal to shake hands and chat with the creator of OpenClaw
- A pre-event at GitHub with a hackathon and talks
- Chainsmokers concert: they kept on pretending not to want to sing Closer, but ended up giving us the finale we wanted haha
- The people: I got to see so many friends (‪@NeetCode‬‪@tom.developer‬ ‪@sadie.stlawrence‬ ‪@SundasKhalid‬ ‪@JessRamosData‬ ‪@SajjaadKhader‬ ‪@raroque‬ ‪@ceciliakimdesign‬and so many more), including a few who had been Internet friends for years but I’d never actually met IRL.

Can’t wait for next year, thank you for having me ‪@MicrosoftDeveloper‬ :)

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2 days ago | [YT] | 698

Maddy Zhang

System design feels hard when you try to memorize everything.

But once you understand the principles behind how real systems scale, stay reliable, and handle millions of users, it finally starts to click.

In this video, I break down the 6 system design ideas that completely changed how I think about architecture.

💡 Here’s what you’ll learn:
✅ Statelessness — why scalable servers should not remember previous requests
✅ Caching — how systems trade freshness for speed using Redis, CDNs, and browser caches
✅ CAP Theorem — why distributed systems must choose between consistency and availability
✅ Message Queues — how Kafka, SQS, and async workflows make systems more resilient
✅ Databases — when to use SQL vs NoSQL and why ACID guarantees matter
✅ API Design — how REST, GraphQL, versioning, and contracts shape reliable systems

👉 Watch the full breakdown here: https://youtu.be/3Pusamd6BO4

1 week ago | [YT] | 733

Maddy Zhang

Claude Code helps you write code.

Claude Co-work helps you handle everything around the code.

Instead of using AI only for quick summaries or generic productivity tasks, Claude Co-work can connect to your tools, run scheduled tasks, process files, generate documents, and work in the background while you focus on higher-value engineering work.

In this video, I will breaks down how Claude Co-work can actually help engineers with recurring, tedious, multi-source workflows that usually waste time every single week.

Here’s what I cover 👇
✅ What Claude Co-work is and how it’s different from Claude Code
✅ Why engineers should care about background AI workflows
✅ How scheduled tasks, connectors, skills, workspaces, and artifacts work
✅ How to use Claude Co-work to summarize newsletters into one weekly digest
✅ How to clean up messy project directories before handoff
✅ How to draft postmortems from incident data
✅ How to turn notes, papers, and technical concepts into interactive HTML explainers
✅ Why connectors are more powerful than manual file uploads
✅ When to use the Claude Co-work browser extension
✅ Practical ways engineers can use Claude Co-work beyond simple chat prompts

👉 Watch the full breakdown here: https://youtu.be/d6inuuWiQzU

2 weeks ago | [YT] | 748

Maddy Zhang

Most developers trying to land remote software engineering jobs in 2026 are doing it completely wrong.

They’re mass applying on LinkedIn, grinding LeetCode endlessly, and wondering why they keep getting ghosted.

But the remote hiring market has fundamentally changed.

In this video, I break down how remote-first companies actually hire engineers in 2026, what hiring managers are secretly screening for, and the exact 5-part strategy I would use today if I had to restart my remote job search from scratch.

Here’s what I cover 👇
✅ Why most developers fail to land remote jobs
✅ Why remote work is NOT treated like a perk anymore
✅ Why remote-first companies hire differently
✅ How to identify real remote-first companies
✅ Why senior engineers dominate remote hiring
✅ The “async proof portfolio” companies actually want
✅ Why timing matters massively when applying
✅ The best places to find high-signal remote roles
✅ How remote interviews differ from onsite interviews
✅ What hiring managers secretly evaluate during interviews
✅ The long-term networking strategy most developers ignore

👉 Watch the full breakdown here: https://youtu.be/JKZgkFiDA14

3 weeks ago | [YT] | 836

Maddy Zhang

Everyone keeps saying AI is replacing software engineers.

But if that’s true… why are software engineering job postings at a 3-year high while tech companies are still laying people off?

The reality is much more complicated than the headlines make it sound.

In this video, I break down what’s actually happening in the 2026 tech job market, why companies are quietly rehiring engineers they previously laid off, and where the real demand is shifting inside software engineering.

Here’s what I cover 👇
✅ Why 52,000+ tech layoffs don’t tell the full story
✅ The hidden reason software engineering roles are still growing
✅ Why the “AI replaced engineers” narrative is already breaking down
✅ How companies are quietly rehiring former employees
✅ The difference between jobs getting eliminated vs jobs still exploding
✅ Why senior engineers are becoming even more valuable
✅ The real skills companies are hiring for in 2026
✅ How to position yourself if you want to break into tech or level up your career

👉 Watch the full breakdown here: https://youtu.be/CC7g1K8e-LE

4 weeks ago | [YT] | 1,016

Maddy Zhang

Which video should I make next ?

1 month ago | [YT] | 50

Maddy Zhang

AI skills are commanding massive salary premiums in 2026, with companies willing to pay significantly more for professionals who can actually work with AI systems, not just talk about them.

But here’s the problem:
Most people chasing AI certifications are wasting their time.

They’re picking random, low-quality certs, going too advanced too early, or collecting credentials that hiring managers simply don’t care about.

This video cuts through the noise.

🚀 What you’ll learn
✅ How to evaluate if an AI certification is actually worth it
✅ The biggest mistake beginners make when choosing certifications
✅ Best AI certifications for non-technical roles (PMs, analysts, ops)
✅ AWS AI Practitioner – who it’s for and why it matters
✅ Microsoft Azure AI Fundamentals (AI-901) breakdown
✅ Best certification for developers building real AI apps
✅ What separates “AI demos” from production-ready systems
✅ Google Cloud ML Engineer – is it worth it for advanced engineers?
✅ Certifications vs real skills (what actually gets you hired)
✅ How to build a smart certification roadmap based on your level

👉 Watch the full breakdown here: https://youtu.be/1LlW9rdtWZ4

1 month ago | [YT] | 638

Maddy Zhang

Most people building AI projects right now are unknowingly lowering their chances of getting hired.

They follow tutorials, build chatbots, clone existing apps… and wonder why no recruiter responds.

But hiring teams in 2026 aren’t looking for “AI users.”
They’re looking for engineers who understand how AI systems actually work under the hood.

In this video, I break down 6 AI projects that actually matter - the kind of projects that signal real engineering skill, system design thinking, and production-level understanding.

Here’s what I cover 👇
✅ Why most AI projects are useless for getting hired
✅ What an MCP (Model Context Protocol) server is and why it matters
✅ Building offline AI apps for privacy-first use cases
✅ How to design a RAG pipeline with proper evaluation + telemetry
✅ Why most multi-agent systems fail (and how to build them right)
✅ Building real-time voice AI applications
✅ When fine-tuning actually makes sense (and when it doesn’t)
✅ How to think like an engineer, not just an AI tool user

👉 Watch the full breakdown here: https://youtu.be/uciWAw7XKM0

1 month ago | [YT] | 877

Maddy Zhang

Everyone is talking about AI agents, but most people still don’t understand how they actually work.

If you want to build real systems, automate workflows, or stay relevant in 2026, you need more than buzzwords you need fundamentals.

In this video, I break down what AI agents really are, how they work under the hood, and the patterns that separate demos from production systems.

💡 Here’s what you’ll learn:
✅ What AI agents actually are (and why ChatGPT isn’t one)
✅ The shift to model-driven decision making
✅ The 5 core components (LLMs, memory, tools, orchestration, context)
✅ Memory + tool usage in real-world systems
✅ Context engineering (what actually makes agents good)
✅ Core patterns: ReAct, planning, multi-agent, human-in-the-loop
✅ How to test agents (and why it’s different)
✅ Eval systems, metrics, and observability
✅ The real opportunity in AI agents

👉 Watch the full breakdown here: https://youtu.be/TzxplsWf0BI

1 month ago | [YT] | 705

Maddy Zhang

Zach went from sitting in a jail cell at 17 to becoming a Staff Data Engineer in Big Tech earning over $600K a year and his journey is anything but normal.


In this conversation with Zach Wilson, we break down the real story behind his rise from rock bottom to the top 1% of tech including the mistakes, strategies, and uncomfortable truths most people ignore.

💡 Zach shares:
✅ How he turned his life around after jail and completely rebuilt his future
✅ The exact steps that took him from $15/hour to $600K+ in Big Tech
✅ The real compensation structure at companies like Meta and Netflix (salary vs RSUs vs options)
✅ Why most engineers massively misunderstand stock compensation
✅ The harsh truth about why “Easy Apply” on LinkedIn doesn’t work
✅ How job hopping actually accelerates your career (and when it backfires)
✅ The skill that matters more than coding in 2026
✅ Why most people fail to even get interviews (not fail them)
✅ The mindset shift that helped him get promoted every year in Big Tech
✅ How one of his students 7x’d their income in a year
✅ What it actually takes to stand out in today’s saturated job market
✅ A practical roadmap to break into AI Engineering from scratch

If you're trying to break into tech, increase your salary, or understand how top engineers actually think and operate. This podcast is a much watch

👉 Watch the full breakdown here: https://youtu.be/i0aEo8v55HE

1 month ago (edited) | [YT] | 620