Shadowing Practice: ex-Google Senior Engineer: How to Get Hired So Fast It Feels Illegal - Learn English Speaking with Video
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Software engineering companies have cut more than 100 ,000 jobs, but at the exact same time, job postings hit a three -year high.
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Both of these statistics are true, and if you don't understand how, you are wasting your time.
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This is Maddie, Senior Software Engineer ex -Google, interviewed at OpenAI, Meta, Databricks, and Netflix.
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And in this video, she's going to walk you through every single step of getting hired in 2026.
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The market, the resume, the projects, the skills, the interviews, and eventually the offer.
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Let's get started.
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So Maddie, everybody watching this has seen the layoff headlines.
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We've got Oracle layoffs, meta layoffs, Amazon layoffs, hundreds of thousands of total firings, job cuts, and layoffs so far in 2026.
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And because of that, most people think tech is dying.
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You're a senior engineer inside big tech, and you've actually gone through the data.
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So what's the truth?
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Is big tech actually dying?
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That's a good question, and that's something I myself have asked myself over and over again.
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The short answer, no, big tech is not dying software engineering is not dying, but the role itself is evolving very, very fast.
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So like I mentioned, there's a lot of layoffs, but on the other hand, companies like Google,
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OpenAI, Anthropic are hiring more and more engineers to build the AI
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that other people are saying are going to take over all of the software engineering jobs.
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So I like to say the market didn't actually shrink, it split.
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So what that means is there's now kind of like a bimodal distribution of jobs.
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the old way was basically
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if you were a junior engineer
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you would get in you'd spend some time getting acquainted with
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the code base you'd submit some rudimentary fixes some bugs some small projects
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and you build your way up nowadays with ai with you know clod
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or open ai chat gpt can understand a code base for you people no longer have
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that grace so what that means is instead now juniors are expected to use ai to onboard
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and to start producing code faster and faster and to more of a level compared to senior or sophomore engineers.
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I will say that even though when I was interviewing, people didn't as much ask system design questions for juniors,
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now more than ever, it is important, if you can, to study your system design fundamentals even as a junior
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because you can tell AI to write code for you and AI will write code for you.
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But if you don't understand how the code will fit in the big picture of your system, you could end up with just jarbled,
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unmaintainable, incorrect code that just happens to work with the specific use case that you prompted your AI with.
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So another thing I'm going to say is that I believe
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that AI is being used as kind of like a scapegoat for job cuts.
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So a lot of companies, like this has happened in cycles in the past, a lot of companies go through phases where they think,
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oh, we should cut costs and we can do this by, you know, moving headcount from high cost of living areas like
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New York and the Bay Area and moving them overseas use.
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And especially with AI, they're like, oh, we can replace engineers with AI.
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However, there are multiple instances of this not working the way that people intended.
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So for example, I don't know if you've heard of like AWS Kiro.
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Yeah, so what happened was there was an internal agent within Amazon.
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And what it did was it actually caused like a pretty big production outage in I think December of last year.
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And it basically triggered a whole set of protocols where now you need to have more human loop.
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This is an example of a big company trying to use AI to replace a software engineering role, but it ended up much worse for them.
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So I think that, yes, a lot of tasks are getting automated.
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And yes, like as a junior, you're expected to perform faster and faster, but fundamentally the job itself is here to stay.
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Like as we have more AI generated code, more AI in our day -to -day, we also need engineers who understand AI,
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who can, you know, run evals, who can build the infrastructure for the AI.
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So it's definitely like a two -way story.
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It's not just is tech big tech dead or not nice
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so one question i have as well maddie is
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that kind of back to those statistics we talked about earlier i mean layoffs just keep happening everybody knows
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that it's like you know oracle amazon meta etc
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but then the number of jobs is actually going up right
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so both layoffs and job postings are increasing
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so do you have any idea how this is happening
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because i would expect okay if there are layoffs happening
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that means there are too many roles companies are just hiring less in general
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but it seems like both are simultaneously happening that's a great question
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i will say there are a lot of engineers
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that uh i think they call it boomerang like they in the past
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it was by choice they would like leave one company to go to a different company
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and then come back for more pay and more comp nowadays i think software
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companies are realizing sometimes
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if they lay off uh you know a bunch of engineers they're actually going to need the same knowledge
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that some of those laid off engineers had
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so they're going to rehire them
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so that's actually some of the discrepancy
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it's um some of the engineers like talented engineers who got
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laid off through no fault of their own their original company realizes hey like we actually need
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you this is actually critical it's happened in many companies out there
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so that explains some of it and also um because it is kind of employer's market.
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I think employers have a little bit more leeway when it comes to, oh, like this is who we're going to keep,
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this is who we're going to get rid of.
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So because of that, they are able to get, quote, like the best software engineers because they are able to use like other engineers
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that got laid out by other companies and use those to fill the headcount
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and then release engineers from roles that are deemed like less important for the company.
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So unfortunately, that is the case.
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Like you can, through no fault of your own,
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lose your job and your company will have no problem right now replacing you because of the state of the job market.
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A lot of tech companies model the behavior after other big tech companies.
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So as soon as one tech company does this, and even if there's backlash, more and more companies realize,
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oh, this is a viable option that we can do because there's precedent now.
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Interesting.
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So it sounds like a lot of the time these companies will do massive layoffs and then realize they overlaid off.
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Similar to overhiring, they overfired.
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And they essentially rehire a of people
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i'm still confused about like why do they still keep doing rounds of layoffs is
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that just normal like the way it works is they over they hire a bunch
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and they just like try a bunch of projects
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and then just do layoffs with ones that don't work is
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that kind of like the normal cycle
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or essentially what i'm asking is are layoffs here to stay
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or will there be a point where they tend to slow down
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and stop essentially i think
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that they are here to stay for at least the next few years
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because there's also precedent and specifically nowadays it's in 2026
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so you know how in 2022 and 2021 and 22
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when everyone is telling everyone to get into self -engineering right
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now there's like a big surplus of people who are new grads
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or a year or two into like non -seniors who want jobs
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and because of that you know supply
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and demand the companies can then realize oh we have like
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so many people want jobs we can afford to pick
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and choose however i think this is a cycle thing we've seen this in the past once it becomes clear
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that software engineering is not just like the career to go into
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if you want to make money then people will no longer go just
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because they want to get rich right they'll you'll get there's less people into the field
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but people who are genuinely more passionate about the field
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and as a result i do think that will decrease the supply
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and then therefore like that will therefore shift the market more toward the employee
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so i think it's going to be similar to what it is for at least a couple of years.
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But I personally am optimistic that after a while, we'll reach a more steady equilibrium.
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Nice.
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It's kind of like how
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Warren Buffett says, when people are hyping up a stock, you should sell because it's overvalued.
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And when people are freaking out because they think an industry is dying, that's the time to actually invest.
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It feels like software engineering is in that second category where
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everybody and their mother are talking about how it's the worst field ever.
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Don't get into software engineering quit your degree go burn your degree get a job at chipotle
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but in actuality maybe
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if you actually double down still try to recruit build your
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profile get better at engineering in two to four years you'll be ahead of a lot of people at
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that point exactly okay so we just talked about how software engineering as a whole isn't dead
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and there are jobs that definitely exist
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but the real question is what kind of jobs are those
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and how do they differ compared to three to four years ago
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and who are the kind of people profiles backgrounds who actually get those jobs today
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so i think a big difference between a software engineering now
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and even like three four years ago was
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that it was totally fine to be a generalist three four years ago
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you could find good job without any specialization however i believe
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that that era is now dead with ai being able to do a lot of generalist roles
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and be able to take um be able to generate a lot of code that's general,
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it is more and more important to be an expert and to go into specific niches.
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And I'm not saying that everyone has to be an AI engineer per se.
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I'm just saying that you need to know how to like go deep into like, I don't know, like Docker,
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React or something like that and use AI effectively.
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I think a lot of engineers, even me up until like pretty recently, to be honest, like I would just like be,
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I would just prompt like randomly, just like type in words and see what comes out
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but more and more so prompt engineering is a more valuable skill as time goes on
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and even as the models get more powerful
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and more powerful um you can still get really bad results
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if you just prompt randomly versus if you are good about how you prompt
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and for example if you tell claude
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or tell chat gbt this is like the general design
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i want this these are the these are the um like this is the stack otherwise
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you'll always have like what like super base
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or you'll have like the the the react like whatever the ai spits out for you
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so you just mentioned how the era of the generalist is dead
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and gone and long live the specialist in software engineering
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so i'm curious to dive more into that what are those specialist niches
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that people can go into especially if they're a computer science student
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or a new grad with just zero to three years of experience at the junior level.
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I would say that it's important to explore and figure out what you are good at, what you want.
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So, for example, I have friends who are in, like, cybersecurity, databases, front -end, too.
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Like, there's, like, my friends who are really good at React, and I think, maybe it's a hot take.
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Like, I personally don't think front -end is going to die entirely.
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Like, to be honest, like, I have prompted AI to do front -end, and when I don't, if I'm not careful,
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it looks very, you know, like, AI purple haze.
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So I think there's still some time before AI can generate a front -end that doesn't look very AI -generated, in my opinion.
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So yeah, things like that, especially security.
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I feel like every other week you hear stories of someone who vibe -coded an app
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and lost thousands of people's personal data.
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That happens a lot.
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So knowing the fundamentals is more and more important as time goes on.
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And finally, I think infra is really important.
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Like, even if, you know, you have great models, you'll always need infrastructure to run those models on.
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So I don't think that role is anywhere near getting extinct.
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So how does one actually specialize in some of these niches at an early stage?
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Because I don't think these universities are adapting very quickly.
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People still do a general computer science degree with data structures, algorithms, maybe like a databases course and be like user interfaces course.
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But how does one actually pick a niche and specialize in it early on?
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That's a great question.
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I would say building your own projects
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and even it's like a really small project something
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that i don't think i was very good at
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when i was in university was i would just you know build only for my internships
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or for uh my classes
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and i would maybe build for like you know really small projects for hackathon
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but i never really dug deep so if i were to go back
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and redo things like i definitely would try to pick more than a toy project
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and i think especially now with ai it's much easier to prototype something
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so i would say pick a project
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that does have to do with the field
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that you're trying to specialize in and just like build something and then just like,
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you know, ask your AI the questions to understand actually the code is writing.
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Don't just like prompt and just like forget about it until it like messes up like months later.
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On that note, let's talk about projects.
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You made a video about four resume projects that got you into Google,
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but it's 2026 and AI can generate a slot project in seconds and every recruiter knows it.
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So what kind of projects today make recruiters drop scrolling?
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That's a great question.
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I'm going to fully echo that the projects
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that i personally made with my you know organic code with
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my own hands would probably not definitely would not raise would not meet the bar today the type of projects
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that would get you noticed are not toy projects not to do's
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they're not like oh i follow tutorial they're projects
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that would solve like a part like a legitimate problem in your life
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and it'd be and something that is a plus you don't have to it's like
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if you build in a way even you don't have
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that many users it is scalable to many users because
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that shows the recruiter that you understand things besides like how do I make it work for one user?
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You can understand like oh
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if I want to make
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it for like a thousand like this is how I can like shard a database it's like xyz.
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I also think that nowadays projects that utilize AI are also in more high demand.
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So for example if you can like build a second brain
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or if you can build like your own MCP server for a particular use case
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or if you're building a rag system those are very useful projects
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that will not only teach you a lot be very useful in your day -to -day,
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but also will show a recruiter that you know what you're talking about.
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I totally agree with that point.
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What I often tell people to do is forget projects in your bedroom and almost make like a mini micro startup.
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Find a real world problem, something that either you struggle with or friends and family struggle with and actually aim to solve that through software, right?
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I mean, that's the point of coding in the first place.
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It's like solving real world problems.
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And it's a lot more impressive to a recruiter or hiring manager when you've launched your project, you've launched your app, You have actual users,
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even better paying users, people who are getting real value and you're able to scale it to them.
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So that's what I'd recommend.
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Don't just build a calculator in your bedroom.
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Anybody can do that in half a second, right?
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Focus on building real world projects to solve real problems.
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But on that note, how useful are projects nowadays?
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Like if you're talking to someone who's a computer science student or an early career engineer, would you even recommend projects?
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Or should they focus more on other things like maybe internships, hackathons, research, etc.? I don't think those are mutually exclusive.
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I think having maybe I would say quality over quantity.
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So don't just like spin up 30 projects.
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Definitely, if you have like one or two that you want to focus on, actually productionize, focus on that.
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I will say some of the projects that I've heard of have come from hackathons.
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So hackathons are a great way to not just learn yourself.
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It's also to find a team.
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And if you find a team and you build a project
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that you're really excited and you want to build it to something real outside the hackathon, that's even better.
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I would say internships are still important if you can get internships.
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But I know currently there aren't as many companies, like as many roles open for internships.
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So like if you don't get an internship, totally fine to build your own thing to see what you can do.
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Kind of like you mentioned, like being like a mini startup mode.
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But if you can do an internship, I would still highly recommend that because I think that having internships on your resume.
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really, really helps future companies want to hire you.
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On that point about hackathons, I 100 % agree.
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I think hackathons by their nature are competitive.
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A calculator app isn't going to cut it.
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You're forced to build a project that's resume worthy in a hackathon setting
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because otherwise you wouldn't even place or do well at all in the hackathon.
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Another benefit of hackathons is it's done in a team setting, like you said.
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So you can get three or four people together, build those connections, and then build a project that's actually way better in
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that team than you could do on your own in a 24 -hour, very short window.
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So all in all, hackathons, 100 % worth it.
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I would highly recommend.
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Actually, I'll ask you, did you do any hackathons in college that you ended up building connections from or any projects from?
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Yeah, I did a couple.
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So I went to MIT.
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We had this hackathon called HackMIT.
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It's very, I think it's very popular, like a lot of people go.
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So I was able to meet friends from other schools as well and like form connections.
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I'm still friends with them for this very day.
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And also an example of how hackathons can help you find
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um really cool people to connect with i recently went to an opus 4 .8 hackathon that's hosted by
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anthropic in san francisco
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and one of the winners was a group of two guys um
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they didn't know each other before the hackathon they met one of them actually from mit
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which is why i ended up talking to him
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and like they built a really cool project like it was
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like basically being able to um build like a you you could take a photo
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and then a 2d photo
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and then you'd use like ai to generate like a 3D model of it
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and then you could place it into like a virtual world
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and you could world build it and I thought that was really impressive.
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So that's an example of a project that was really impressive
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that was made possible only
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because this hack fund brought two people who did not know each other from Oxford Science of the US together.
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Listen up, if you're struggling to land an amazing software engineering full -time job
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or internship or if you submitted dozens of applications
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and you feel like nothing is working or if you failed multiple online assessments and interviews,
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or you just feel like you don't understand the process to land a great offer in the market of today,
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I actually run a school for people like you called the Software Engineering Accelerator.
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Now, over the past year, we've helped dozens of people in incredible jobs at internships at companies like Google, Amazon, Microsoft, Tesla, Salesforce, Adobe,
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And the best part about our program is that we actually guarantee the outcome.
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So if you'd like to work directly with me
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and my team of FANG recruiters and engineers to land an incredible job in tech guaranteed,
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click the top link in the description and submit an application to join us.
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Cool, so we just talked about projects.
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Let's talk about learning, courses, and books.
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Most people are completely overwhelmed with random Udemy courses, leak code, some random AI tutorial,
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a system design playlist, but no idea what actually matters or what order anything goes in.
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So let's go from zero to hired.
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What are the few best courses and books that people should actually pay attention to?
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The first thing I say is it doesn't matter as much, especially in the AI era, what language you use when coding.
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So pick the one that is most comfortable for you in the interviews.
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I personally use Python.
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I have friends who use like Java, JavaScript.
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Some use C++.
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I'm not going to comment on that, but if it works for them, it works for them.
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They got good offers, so they know what they're doing.
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Second, I would say fundamentals still matter.
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Like I know right now, most companies are focusing on AI assist interviews.
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So lead code, the type of data destruction algorithms problems are probably going to like decrease a lot
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and maybe maybe just stop in the next couple years
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but as of right now
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when we're recording this video a lot of companies still ask those
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so for better for worse so for
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that i would highly recommend cracking the coding interview
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and rereading um clrs which is like the standard textbook
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that teaches all the fundamentals for data destruction algorithms i will also say
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that even if you don't use recursion or balance a binary tree every day in your job,
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knowing the fundamentals is still useful
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and you don't want to be in a position where you
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need to have your AI explain every single thing to you
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while you're trying to debug an issue because that's just bad for you and bad for the company.
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I feel like maybe everybody knows about this, but I think NeetCode genuinely the best resources online
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if you want a video format for learning data structures
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and algorithms rather than the book format but
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if you can somehow get yourself to read a book I think you'll also probably learn more
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that way so that's what I used I ended up using need code stuff back in the day
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and then next I would say system design especially
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if you are going for a more senior role is more
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and more important as someone who came from big tech even
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if you use system design in your company sometimes
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if you are work for a big enough company the stack
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that you use might not be standard so definitely recommend refreshing
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and like constantly learning what is new
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and what is widely used in the fields so for
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that i recommend personally um i really like hello interview
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so i think they have they have a bunch of youtube videos
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i think they have a page here as well
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i personally didn't pay for it like i use their free youtube videos the reason why i like them is
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because they basically give you mock interviews for very like standard
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system design questions like for example oh like design like youtube feed
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or design facebook but what is really good is that they not only tell you what is passing, They also tell you what isn't passing,
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like what are common mistakes that candidates make.
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They also tell you this is passing for a mid -level candidate.
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This is passing for a senior, for staff.
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So it's really a great way for you to calibrate yourself.
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And it gives you not just the right answer, but why that answer is the right answer.
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Do you think system design is a non -negotiable for early career engineers today?
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I would say to do well in the job, it is non -negotiable.
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So because of that, I would say if you have time, definitely learn system design.
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I personally didn't learn system design formally until I was interviewing to get the role I have now.
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So that, I think, took a lot of time
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because I was going from very little
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because I joined my previous company without any system design experience because I was joining as a new grad.
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So if you have time, would recommend system design.
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It makes you not only a better interviewee, it also makes you a better engineer.
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And finally, as we all know, AI is getting more and more important regardless of what part of engineering you're in.
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So I personally really like one of my friends, Her name is Chip Huynh.
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She has a book called AI Engineering, which is really, really comprehensive.
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And I would say if you're going to just read one AI book in 2026, read that book.
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It takes you through all the fundamentals.
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And she goes through a lot of concepts.
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She talks about like RAG, about agents, about MCP, about beddings.
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And it's very, very digestible in a format that you can understand even
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if you don't have a strong or any ML or AI experience.
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Okay, so we've just gone through the learning layer.
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Let's talk about the application layer.
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Most people spam thousands of applications and never hear back.
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But you've gotten interviews at OpenAI, Netflix, Databricks, and Google.
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So where do most people go wrong?
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I would say most people go wrong because they just like,
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like you said, submit thousands of applications without thinking about if the role is a good fit,
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without like, without reaching out to the company, without getting a referral.
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So unfortunately, because there are so many candidates right now that want job, if you don't have like a previous connection,
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like for example, if you didn't get a referral to the company, the chances of you getting an interview
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and a callback are much, much lower i will also say i personally got some interviews
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because a recruiter saw my profile on linkedin
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and then like reached out being like oh i think this would be a good fit for you so
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if it is possible for you to put yourself out
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there more on linkedin that'll make it more likely for recruiters to organically reach out to you by
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that i mean you could you know talk you could link your projects
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you could put like specific keywords like for example
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if you built a rag system for your company you can put rag you built mcp you could put mcp
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that just like makes it more likely if a recruiter is searching like candidates
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and a keyword for a job
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that you will be one of the people considered yeah on the referral note
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i think a lot of people hear that advice
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and then they'll get one referral to google
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and then they won't get an interview
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and then they'll throw their hands up in there and be like
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but i'm on but maddie it just didn't work like referrals don't work
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but in reality just
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because you get a referral it just increases your probability of getting an interview
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it doesn't guarantee anything you know what i mean and in fact,
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I've worked with a student who got a Microsoft referral and then within an hour or two got rejected.
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And then they messaged me, yo, what the hell am I got rejected?
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It didn't work.
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And I was like, bro, you didn't get ghosted.
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That means they actually looked at your application within a few hours and rejected you, which is a huge win.
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Like that's way better than being ghosted.
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So all it is is a referral just creates a different pool that they hire from.
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You're not guaranteed to get anything, but it just increases your odds from a cold application.
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So I would highly to recommend referrals.
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Yeah.
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And like you mentioned, it doesn't guarantee anything.
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And I think especially when it comes to larger companies, like there will be many hundreds of people who have referrals.
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So just scale wise, the recruiter will not give everyone an interview.
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I will say if you are able to, you can also focus on smaller companies,
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especially if you can get like a referral from a smaller company
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that will really greatly increase the chance
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that your application will be taking more seriously because they will not get like the hundreds, thousands of referrals that people get when applying to Google.
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They'll get like more curated ones and they know
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that they can trust their own referrals a little bit more than if it was just like a toss up.
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100%.
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I think the power of a referral scales the smaller the company, right?
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Like for example, startup referrals matter immensely.
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Most startups, the CEO or founder or whatever reviews basically every single referral, especially at the early stage,
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just because it's so valuable for them to get hiring right.
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And I personally know multiple startups of recruiting where like the
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referral just goes straight to the to the hiring person like every single one gets reviewed
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you might not get interviewed but at least you'll get reviewed
412
so going for smaller companies definitely makes sense yeah
413
and like it like like you mentioned it's like much better to know immediately
414
you're not a favorite rather than just like wait like i've there are many companies
415
that have ghosted me and other people
416
and it just like i would much rather just get like
417
a no immediately rather than like oh will they won't they for months another objection i often get
418
when it comes to referrals with the people
419
i work with is they often say come on i'm just
420
too nervous to ask for it i don't want to bother someone why would they refer me
421
so how do you get over the fear of rejection
422
when it comes to asking for referrals that's a great question
423
i'll say i myself am not really good at getting over
424
that fear i'm still super self -conscious like obviously i've not job interviewed for many like quite a
425
while but when i was interviewing to get to the job i currently have i felt
426
so self -conscious what kind of helped was thinking that
427
that oh it's not just good for me to get a referral a lot of companies if your person gets hired
428
you'll get a bonus
429
so i personally have gotten some bonuses from people i referred to at google
430
when i was there
431
so it's like a benefit it's mutualistic like it's not just good for the interview
432
it's not just good for the candidates also good for the fur
433
that's one thing also um it's kind of cliche
434
it's like they don't it's like you you miss 100 the shots
435
you don't take they don't have to say yes like obviously
436
if you're not a good fit they might not refer you and that's totally fine.
437
It's like, I feel like I was afraid of like, oh, like what if I'm like pressuring my friend to refer me?
438
But I think like, again, if they don't think you're a good fit, they don't have to refer you.
439
And like, I wouldn't take it.
440
I don't think anyone should take it badly if you are refused a referral.
441
So honestly, just putting, being more comfortable with putting yourself out there is a good trait for many, many different use cases, not just the referrals,
442
but for the referral in particular, I think it's just something, it's like getting over the initial fear is really, really powerful.
443
Okay, we've talked about applications and getting more interviews through networking, but you've actually been on both sides of the table.
444
You've interviewed at these big tech companies, and you've also interviewed people trying to get jobs at these tech companies.
445
And right now, interviews are crazy.
446
I mean, people are cheating using AI, left and right, and companies are redesigning their whole interview process.
447
So could you actually break down what do early career interviews look like in 2026, and how does someone navigate that minefield?
448
This is in flux because interviews are rapidly evolving
449
but as of right
450
now most companies will still start with your standard like phone
451
screen where they ask a candidate like oh like you know
452
why do you want for to work for xyz um are
453
you okay like you know logistics with the compensation the relocation
454
etc as of now they'll give you a legal style interview
455
so it's like your standard like data destruction algorithms challenge
456
i think some companies give multiple it depends on the company
457
and like especially startups i think do more of their own thing i noticed after
458
that usually you'll get especially if you're a senior you'll get on -site
459
which is like a more back -to -back hours of interviews.
460
So oftentimes companies will give you a system design round.
461
So for example like oh can you implement like a notification system?
462
Especially if the company is smaller you'll often get to talk directly to the hiring manager
463
that wants to fill the position so they can kind of judge if you're a good fit.
464
Some companies will have a round where they want you to basically explain a project that you built previously.
465
That's just like a way for them to gauge if you know how to like explain challenges that you face, drop like system design infrastructure diagrams,
466
any challenges and things like that.
467
And then finally, a lot of companies are starting to incorporate those like AI assisted interviews.
468
So I personally have not done any because when I was interviewing back in the day, a year and a half ago,
469
most companies weren't doing this.
470
But nowadays, a lot of companies will have a problem
471
that you're supposed to solve and they let you use your AI coding agent.
472
And then they'll they might ask you questions about how you're using that agent.
473
They might like kind of quiz you on that.
474
Recognizing that you haven't done one of these interviews nowadays, of course, but what do you feel like the best resources
475
or techniques are to prepare for those new kinds of interviews, right?
476
Everybody knows about Classic, LeetCode, DSA, etc. But what about those new AI enabled interviews?
477
That's a good question.
478
So my friends who have taken the interviews generally say like
479
a lot of it's just using AI naturally in your day to day workflow
480
and just finding ways that will make you faster and optimized.
481
Also, I know, for example, Anthropic has guides on prompting so they have found those useful as well
482
and those are free so I think those are good resources to help you optimize how you prompt.
483
Do you have any AI cheating stories where you were interviewing a candidate and you realized they were cheating?
484
Yes maybe it'll be different ones you know AI is condoned in the interviews
485
but I have given a couple of like standard data instruction algorithm questions
486
and it's maybe the people who cheat well I don't notice
487
but the people that I have noticed have been like super super obvious
488
so for example like I had a person who like was typing
489
and then at some point they like yawned
490
and it like it kept on typing i was like what like literally like they reached back they reached back
491
and went like went like this i was like are you seeing
492
this um another time i had a candidate had glasses
493
and there's a reflection in myself and i was like okay like you know
494
that kind of stuff there's been just my friends have also experienced like things
495
there's like someone who was reading like almost verbatim so for example
496
when I asked
497
when they asked a question there's like oh that's a great question the answer to this is blah blah
498
that would happen and I've noticed my friends have said
499
that sometimes the way to catch
500
if it's not super obvious is like you start asking a question
501
that is just wrong like a question doesn't really have good answer
502
and if the person is cheating with AI they're gonna the AI is gonna attempt to answer it
503
if the person's a real person they're gonna be like wait
504
that makes no sense
505
and like ask to clarify yeah I feel like the people I've talked to it ends up being pretty obvious
506
when someone's cheating with AI and I think another tell is like the imports like
507
if you do all your imports at once
508
and then start coding it's like what nobody actually does
509
that you know what i mean
510
so there's like some i feel like niche like micro tells for most people um
511
when it comes to revealing cheating but that's really funny for sure all right
512
so we've gone through projects courses learning the market resume applications and interviews let's talk about the offer.
513
So if you finally got a job offer, can a junior with essentially no leverage negotiate in this job market?
514
And two, how do you not get fired or laid off in this new economy?
515
That's a great question.
516
The first question, I would say if you're able to do all your interviews all at once, so you have competing offers,
517
that's like the best leverage you can get if you don't have prior experience, if you're not currently in a company.
518
A lot of companies will match, depending, especially if it's a competitor, like a good, if it's like a serious competitor to them they'll match
519
or even do more than your other offers
520
if you can show them proof
521
that you did get this other offer you can also use resources online
522
that give you information on what the companies are actually paying other people
523
so the top of my head blind is kind of toxic
524
but blind does have salary information
525
so sometimes people will post being like hey like i have this offer is this good
526
or bad and people will say it also levels .fi
527
if it's a bigger company you can anonymously submit your pay to levels at fi
528
and they check like i'm pretty sure they verify the pay stub they just don't obviously post the pay stub
529
so that's like a verifiable way that you can kind of see the range
530
that your your company is paying other people so
531
if they're offering you less you can counter
532
that makes sense all those seem like very good strategies to negotiate
533
but do juniors have leverage at all like have you heard of juniors entry -level people still negotiating
534
or is that something that just doesn't happen anymore nowadays i think
535
that if the company itself sometimes gives different stock options
536
that there's still possibility like i've heard juniors doing
537
that however i know a lot of companies like for the base pay
538
when it comes to juniors they don't negotiate at all
539
and that's just kind of company policy i think
540
this is also another place where the smaller the company the more negotiation power
541
so for for big tech at this point
542
and maybe i'm wrong about this
543
but a lot of these like entry -level roles are pretty
544
standardized especially internships like you can't really negotiate on an internship
545
but i guess the more advanced you get
546
and also the smaller the company like there's more power
547
there in terms of negotiation exactly there's no like definitive way to avoid layoffs
548
or avoid like getting pushed out unfortunately
549
but i think there's a couple things you can do to increase your chances of surviving
550
so one of them especially if you're a junior like definitely make sure
551
that your manager or your management chain is very much aware of what you've accomplished for example
552
if you like document all your wins that's like really good
553
because then your manager has like proof that you can list your prs
554
and you can like write your you put add your docs on there your manager
555
then has like a very easily accessible way for them to
556
check on your progress something else is to be honest like companies nowadays
557
i would say are a little bit more risk averse
558
and a little bit more they like to prioritize orgs
559
that make money i've noticed a lot of companies like this so if you want an org that probably won't get downsized,
560
perhaps it's the one in your company that's like ads or like that makes money or is doing like frontier AI stuff.
561
So again, there's no definitive way to not get laid off.
562
But those are two things you can do to help decrease your chances, in my opinion. For sure.
563
I feel like the best strategy to not get laid off is just accepting you might get laid off
564
and just keep up your resume and your AV skills so that even if you do get laid off,
565
you can find a new offer pretty quickly.
566
I think especially with layoffs
567
and like large scale big tech layoffs like i've spoken to
568
multiple people who went through the meta layoff a few months ago
569
i'm sure you know people as well went through
570
that it was almost like there's there was essentially no way to predict who was head
571
and i'd be really curious to talk to someone who actually decided who got laid off
572
because it feels like almost like voodoo like you have no clue who got laid off
573
there were people who felt like there were better engineers than others who were laid off
574
and other ones who were spared so you kind of have no idea
575
when it comes to this stuff all
576
you can just keep your profile your resume your applications your networking your interview skills up
577
so you can find a new job faster all right
578
so we've gone through the entire process end to end for how to survive
579
and get hired in the 2026 job market
580
i guess final point maddie what's your one piece of advice
581
to someone who's an early career engineer zero to three years of experience who's struggling to get a job today
582
i would say do not be afraid of rejection um even me as someone
583
you know who's like a classically okay like where's me like i went to mit
584
i intern at Microsoft Amazon Morgan Stanley worked at Google
585
I get a lot of rejections like over the years I used to be
586
so afraid of getting rejected I wouldn't apply
587
because I was like oh like I don't want to get like rejected
588
because that seems final but first everyone gets rejected like even the people
589
that you most admire they've gotten rejected from hundreds of places
590
like they just obviously won't put on their resume on their LinkedIn
591
that they got rejected right it only takes one offer
592
and then after you get the offer then it will help you move on
593
and on so I think that for me fear failure was something
594
that i'm still struggling with at this point
595
but definitely was really detrimental to my career when i was younger
596
and that's something
597
if i could go back i would be like i don't
598
i don't care i should have applied before i thought
599
i was ready i should have applied like you know i should apply to the companies
600
that i i thought i had no chance of getting into
601
and i will say that a lot of my A lot of my friends are doing very well now.
602
They did that.
603
They were not afraid to apply to all the really nice companies.
604
They were not afraid to apply before they studied data instruction algorithms.
605
And some of them did get in.
606
So even if there are requirements, those requirements aren't strict requirements.
607
Maddie, people want to connect with you further.
608
Where should they go?
609
You can find me on YouTube at Maddie Zhang.
610
And you can also find me on Instagram at Madeline .M .Zang.
611
Thank you.
612
Awesome.
613
Maddie, thanks for doing this.
614
Thank you for having me.
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Vocabulary and speaking notes for this lesson
This speaking lesson is built on the video “ex-Google Senior Engineer: How to Get Hired So Fast It Feels Illegal”. This video has 613 sentences and 7731 words to shadow. The speech runs for 35:17. The speaker talks fast, about 219 words per minute, so expect linked and reduced sounds. 84% of the words are among the 3,000 most common in English; the rest is worth studying before you start.
Key vocabulary in this video
15 words from the video worth learning, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| referral noun | /ɹɪˈfɜː.ɹəl/ | The act or process of transferring someone or something to another, of sending by reference, or referring. |
| hire verb | /ˈhaɪɹ/ | To obtain the services of in return for fixed payment. |
| internship noun | /ˈɪntɜːnʃɪp/ | A job taken by a student in order to learn a profession or trade. |
| nowadays adverb | /ˈnaʊ.ə.deɪz/ | At the present time; in the current era. |
| resume verb | /ˈɹɛz.ə.meɪ/ | To start (something) again that has been stopped or paused from the point at which it was stopped or paused; continue, carry on. |
| recruit verb | /ɹɪˈkɹut/ | To enroll or enlist new members or potential employees on behalf of an employer, organization, sports team, the military, etc. |
| prompt verb | /pɹɑmpt/ | To lead (someone) toward what they should say or do. |
| cheat verb | /ˈt͡ʃiːt/ | To violate rules in order to gain, or attempt to gain, advantage from a situation. |
| algorithm noun | /ˈælɡəɹɪðm̩/ | A collection of ordered steps that solve a mathematical problem. A precise step-by-step plan for a computational procedure that possibly begins with an input… |
| fundamental adjective | /ˌfʌn.dəˈmɛn.təl/ | Related to a foundation, base, or basis; serving as a foundation. |
| generate verb | /ˈd͡ʒɛn.ə.ɹeɪt/ | To bring into being; give rise to. |
| startup noun | /ˈstɑɹtˌʌp/ | The act or process of starting a process or machine. |
| guarantee noun | /ˌɡæɹ.ənˈtiː/ | Anything that assures a certain outcome. |
| essentially adverb | /ɪˈsɛnʃəli/ | In essence: by nature. |
| solve verb | /sɒlv/ | To find an answer or solution to a problem or question; to work out. |
Phrasal verbs you will hear
| Word | Pronunciation | Meaning |
|---|---|---|
| lay off verb | (of an employer) To dismiss (workers) from employment, e.g. at a time of low business volume or through no fault of the worker, often with a severance package. | |
| go through verb | To travel from one end of something to the other. | |
| end up verb | To bring to a conclusion. | |
| get over verb | To overcome. | |
| go back verb | To return to a place or state after having been there at a previous time. | |
| break down verb | To stop functioning. | |
| come out verb | /ˌkʌm ˈaʊt/ | To be discovered; to be revealed. |
| double down verb | To double one's wager, particularly, the name of a specific doubling bet allowed in blackjack. |
Sentences worth repeating
Short, complete lines from the video that you can reuse in everyday conversation:
- On that note, let's talk about projects.
- Don't just build a calculator in your bedroom.
- I don't think those are mutually exclusive.
- I'm still friends with them for this very day.
- Let's talk about learning, courses, and books.
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Conditional sentences if + clause, will/would + verb — a condition and its result | if you have time, would recommend · if you're a senior you'll get · if the company is smaller you'll often |
| Present perfect have/has + past participle — a past action that still matters now | have cut · has seen · you've actually gone |
| Passive voice be + past participle — the focus is on what happens, not who does it | are expected · being used · are deemed |
| Relative clauses who / which + clause — extra information about a person or thing | people who are · friends who are · someone who vibe |
Pronunciation to watch
The speaker uses 184 contractions and reduced forms, such as don't, you're, I'm. Say them the short way, as you hear them.
- The “th” sounds: algorithm /ˈælɡəɹɪðm̩/, bother /ˈbɑðɚ/, worthy /ˈwɝ.ði/, hackathon /ˈhæ.kə.θɑn/, anthropic /ænˈθɹɒp.ɪk/
- The “sh” and “zh” sounds: internship /ˈɪntɜːnʃɪp/, essentially /ɪˈsɛnʃəli/, negotiate /nəˈɡəʊ.ʃi.eɪt/, destruction /dɪsˈtɹʌkʃən/, specialist /ˈspɛʃəlɪst/
- Long words — get the stress right: fundamental /ˌfʌn.dəˈmɛn.təl/, essentially /ɪˈsɛnʃəli/, negotiate /nəˈɡəʊ.ʃi.eɪt/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, genuinely /ˈd͡ʒɛn.ju.ɪn.li/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like referral, hire, internship.
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.