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Sixteen Colleges Rejected This Google Engineer · Elon Musk Podcast

0:00
Stanley Zong, a high school student from Palo Alto, was
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rejected by 16 universities but was immediately hired by Google
0:08
for a software engineering position that normally requires
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A doctorate or equivalent experience.
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I mean it is just a completely absurd contrast.
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You have this teenager getting rejection letter after rejection
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letter from basically every college he applied to, and then
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the response to that single localized failure is the launch
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of this massive multi state civil rights lawsuit that is
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written almost entirely by artificial intelligence.
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Which brings us to the core cushion here.
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How does a student who is deemed completely unqualified for a
0:39
basic undergraduate degree use an AI chat bot to prove that
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they are the victim of systemic institutional bias?
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Right. And to really get into that, we
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have to start by looking at the objective reality of his
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background, because all the friction in the story begins
0:53
with the raw data of his academic profile compared to the
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actual outcome of his applications.
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Let's actually look at his resume, because saying he was
1:01
just a student, I mean, that doesn't even begin to cover it.
1:03
No, not at all. The credentials are
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mathematically extraordinary. We're talking about an
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unweighted grade point average of 3.97 and a weighted GPA well
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over 4 point O. Wow.
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He attended a highly competitive high school, placed in the top
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9% of his class, and he achieved a near perfect SAT score.
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He literally missed the maximum score by exactly 10 points.
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Which is wild. Those academic metrics alone
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place him in this incredibly elite bracket.
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I mean that test score puts him in the top fraction of 1% of
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millions of annual test takers. Exactly.
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And his class rank actually qualified him for a state
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specific program that guarantees admission to at least one public
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university campus for high performing residents.
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But, you know, plenty of students have high grades.
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Right grades aren't everything. Exactly what elevates this
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beyond just a standard rejection complaint is the professional
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validation he built on his own. Yeah, because beyond the
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classroom, he founded a free electronic signature startup
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called Rabbit Sign. And I want to be clear, this was
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not some minor side project or a high school coding club
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assignment. It was a fully functional, high
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pay compliant platform. We really should pause on what
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that actually means, because building a high pay compliant
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platform as a solo high school developer is a staggering
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technical achievement. Seriously, high paid compliance
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means the software meets these incredibly stringent federal
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guidelines for protecting sensitive patient health
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information. You can't just throw some code
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together on a server in your bedroom.
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Right, you have to build end to end encryption.
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Yes, encryption, secure key management, robust audit trails.
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You have to ensure that data is completely protected both in
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transit and at rest, because if a medical clinic uses your
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platform to sign patient forms and there's a security breach.
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You are facing massive legal consequences.
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Exactly, and he built this to handle heavy user demand without
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charging any fees. And Amazon Web Services actually
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recognize this startup for its exceptional efficiency and
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secure architecture. They selected it to be featured
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in a professional case study. Which is just huge.
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For Amazon to look at a high schooler's architecture and say,
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yes, this is an example of how to build efficiently on our
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servers, that is incredible validation.
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It's the exact kind of real world application of skill that
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usually commands immediate attention.
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And I mean, it did command attention, just not from the
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universities, right? So the Google recruitment
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process is fascinating. A recruiter from the company
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actually reached out to him when he was in middle school.
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Middle school, That's insane. The recruiter was completely
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unaware of his age, they just reached out based entirely on
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his online technical contributions and open source
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commits. Once they got him on a call and
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realized he was literally a minor, they paused the process,
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but they kept his file and right as he finished high school, they
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brought him in for the real thing.
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And the evaluation he endured is brutal.
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It was a 10 hour process involving 5 randomly selected
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Google engineers. 10 hours. Yeah, and these engineers are
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specifically trained to assess both technical capabilities and
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soft skills, completely blind to his background, his age, or any
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external influence. Let's explore what that 10 hour
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evaluation actually looks like. Yeah, because it is not just
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answering basic questions about your resume.
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Oh. No.
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A technical interview at that level involves multiple rounds
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of intense whiteboarding and problem solving.
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They are testing you on data structures, complex algorithms,
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graph theory, dynamic programming.
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Sounds exhausting. It is they will present this
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massive abstract problem, something like designing the
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back end for a globally distributed caching system or
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like a ride sharing dispatch algorithm and the candidate has
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to write functional code on a whiteboard while explaining
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their logic, optimizing for speed and memory usage and
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accounting for all these weird edge cases.
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And after running that gauntlet, they offered him an L4 position.
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That specific level designation is crucial here.
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L3 is the standard entry level role for a recent college
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graduate with a computer science degree.
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L4 is a mid level software engineer.
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It's a position typically reserved for individuals holding
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APHD or someone who possesses several years of high level
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industry experience. I'm looking at these stats and
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they just seem flawless, but are we sure they didn't just go easy
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on him because he was this young prodigy?
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Well, the structure of the process prevents that.
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The compensation structure at the company naturally
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disincentivizes interviewers from over assessing a
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candidate's qualifications, right?
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Because if you hire someone at an L4 level and they cannot
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actually perform L4 work, it actively damages your team's
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productivity and your own performance metrics as an
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interviewer. Oh, I see.
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The evaluation was strictly tied to verifiable merit.
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The code works efficiently or it doesn't.
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He gets that, but then we have the university rejections. 16
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highly selective engineering programs denied him admission.
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16 This included five separate campuses within the University
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of California system, alongside MIT, Stanford, Carnegie Mellon
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and Cornell. Out of 18 applications, he was
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only accepted to two state universities.
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So the corporate sector validated his abilities at the
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highest possible level, while the academic sector
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systematically excluded him. It is honestly like passing a
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grueling multi day audition for a principal seat in a major
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Symphony Orchestra playing Florida State behind a blind
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screen, only to be told the next day that you are not qualified
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to take an introductory music theory class at the local
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Community College. The contrast is just jarring.
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It really is. But I have to ask you, is this
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actually a failure of the system or is it just the mathematical
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reality of elite schools? I mean, when an institution has
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thousands of applicants with a perfect scores for only a few
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100 spots, incredibly qualified people are going to be turned
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away. Well, that mathematical reality
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is exactly the defense these institutions rely upon.
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They argue that perfect metrics are merely A baseline, you know,
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not a guarantee of admission. They look at a pool of 5000
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applicants with four pointer GPA S and they just have to find a
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way to select 500. But the presence of the
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corporate offer changes the equation entirely.
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What this changes is that it shifts the burden of proof onto
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universities to articulate exactly what they are evaluating
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if verifiable world class technical mastery is somehow
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insufficient for admission. Wait, back up.
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We need to look at the other side of this.
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We really cannot view this purely through the lens of a
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flawless underdog. Story OK, that's fair.
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Following his hiring, he underwent a performance review
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under the company's revamped evaluation system.
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Right. This new system was designed to
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be significantly more rigorous, actually cutting payouts for
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average employees to heavily reward top performers.
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And in that review, he received an outstanding impact rating.
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Which is huge. Yeah, it places performance
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above the majority of high performing engineers at one of
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the most competitive technology firms globally.
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And the family uses that rating as definitive empirical proof of
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his merit. They're basically saying, look,
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not only did he pass the test, he is actively outperforming the
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adults in the room. But there is fierce criticism
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circulating on public forum like Reddit and Hacker News regarding
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his background. Critics point out a highly
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relevant detail. His father, Nan Zong, is already
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a software engineering manager at Google.
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Yeah, the critique centers heavily on the environment he
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grew up in. He attended Gunn High School in
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Palo Alto. Right.
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This is an environment known for its hyper competitive atmosphere
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and its proximity to immense wealth.
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Students in that district are surrounded by the children of
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venture capitalists, tech executives and Stanford
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professors. And critics argue that in that
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specific demographic, having near perfect test scores,
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participating in coding competitions and even founding A
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nonprofit are simply standard resume fillers.
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Wow, standard. Yeah, we are talking about an
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ecosystem where parents hire private tutors for middle
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schoolers to learn advanced machine learning.
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They suggest that despite his objective intelligence, he's
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essentially a dime a dozen applicant in the context of
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Silicon Valley overachievers. Like in a vacuum, building
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rabbit sign is incredible. But when evaluated against his
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immediate peers in Palo Alto, critics argue he lacked a unique
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standout quality that a holistic admissions board looks for.
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There is also the reality of public university mandates that
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complicate the narrative of this purely vindictive rejection.
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What do you mean? Well, critics highlight that out
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of state public institutions such as the University of
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Washington are legally mandated to prioritize in state
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residents. How does that actually function
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in the admissions office though? A State University is funded by
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the taxpayers of that state, right?
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Their primary charter is to educate the students of that
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state. OK, makes sense.
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So a place at the University of Washington might cap their out
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of Rejection from those specific
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programs is purely a matter of geographic capacity, regardless
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of an applicant's academic perfection.
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But a parent's job title does not negate A10 hour blind
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technical interview conducted by 5 independent engineers.
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I mean, if the process is truly randomized and blind, the merit
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of the applicant stands on its own.
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They aren't asking his dad for the answers while he is
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whiteboarding his system design problem.
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See, I completely disagree with that framing.
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Really. Yeah.
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Networking, proximity to Silicon Valley wealth, and having a
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parent who understands the exact internal mechanics of the
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corporate hiring process provide an incalculable advantage.
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You think the father coached him on the specific rubrics Google
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uses? Absolutely.
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The father is an engineering manager there.
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He knows exactly what the interviewers are trained to look
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for. That's true.
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He knows the specific phrasing they prefer for problem solving,
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the optimal ways to structure code for those specific tests,
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and the behavioral signals they value.
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Claiming that this is a pure meritocracy while completely
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ignoring those structural advantages makes the the
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underdog narrative completely disingenuous in my opinion.
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The corporate evaluation may be blind on the day of the test,
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but the preparation for it was heavily resourced over years.
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OK, so the consequence of this is that it limits the pure
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meritocracy narrative presented by the family.
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It introduces the reality that privilege and insider access
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play a role in corporate hiring just as much as subjective
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criteria play a role in college admissions.
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Exactly. And because of these complex
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rejections and the lack of what they felt was a satisfactory
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response from university officials, the father and son
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decided to formalize their grievance right.
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They created a nonprofit advocacy group called SWORD,
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which stands for students Who Oppose Racial Discrimination.
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Yeah, after attempting to engage directly with university
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administration and feeling entirely dismissed, they
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established Sword to serve as a Co plaintiff and basically a
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vehicle to organize anonymous testimony from other families
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experiencing the same issues. They took their grievance and
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built a mechanism to sue universities across multiple
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states. And their multi jurisdictional
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strategy is highly specific. They are not just filing
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lawsuits indiscriminately in federal courts everywhere.
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No, they are specifically targeting states that have
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pre-existing state laws explicitly banning race based
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preferences in public education. Why focus on state law instead
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of federal? Because state constitutions and
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state level voter initiatives can offer stricter protections
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than federal law in certain states, voters have passed
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propositions that completely outlaw any consideration of race
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in public university admissions right.
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By focusing on states with these established legal mandates, they
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are arguing that the institutions are actively
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circumventing the will of the voters and violating their own
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state constitutions through the use of qualitative proxies.
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A crucial part of this strategy relies on a novel concept the
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father developed, which he calls Evergreen legal standing.
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We really should explain what standing actually means in a
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courtroom context. Yeah, in the legal system, you
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cannot just sue someone because you're angry or because you
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think they broke a rule. Obviously, you have to prove
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Article 3 standing, which requires showing that you
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suffered a concrete, particularized injury.
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In university admissions cases, the injury is the actual denial
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of admission. And because his son has declined
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to enroll in any degree granting institution and remains employed
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in the corporate sector, he is legally classified as a
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potential student. Exactly, and that status
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prevents the universities from utilizing a common, very
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effective legal defense called mootness.
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Yeah, normally if a student is rejected, attends a different
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college, and then sues, the defending university can argue
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the case is moot because the student is already receiving a
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college education elsewhere. Oh, I see.
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The immediate harm has passed. The courts often agree and
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dismiss the case, which allows the universities to basically
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run up the clock on these lawsuits simply by waiting for
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the student to graduate from their backup school.
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It is exactly like a ghost haunting a house.
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As long as the student refuses to actually go to college, the
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legal threat can never truly be exercised or dismissed by the
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court. The grievance remains perfectly
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preserved indefinitely. Right.
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And what this opens up is a pathway for plaintiffs to
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maintain perpetual legal pressure on institutions without
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having to prove immediate, ongoing enrollment harm.
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It completely changes the procedural playbook.
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Hold on, we have to talk about how they are actually fighting
14:40
these legal battles because the mechanics of this lawsuit are
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wild. They really are because you
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would assume a multi state federal litigation campaign
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would require a massive legal team.
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We are talking about suing multiple heavily funded state
14:54
institutions simultaneously. But traditional law firms
14:57
universally refused to take the case.
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Some cited overwhelming existing caseloads, while others
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reportedly expressed deep concern over the political
15:05
controversy. Taking on major universities
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over admissions policies is a massive lightning rod.
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Oh, for sure. Firms were worried about public
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backlash and even potential physical safety risks associated
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with challenging these specific institutional policies.
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So left without traditional representation, they had to
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proceed pro SE, meaning they are representing themselves in
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court. But the father, leaning heavily
15:29
into his background as a software engineer, did not just
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start typing up documents in Microsoft Word.
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He utilized conversational generative artificial
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intelligence models, specifically ChatGPT and Gemini,
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to draft the initial federal complaints.
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And these were not short summaries or basic template
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letters. The AI generated highly
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structured legal filings that exceeded hundreds of pages in
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length. Hundreds.
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The documents included deep constitutional analysis,
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jurisdictional comparisons and specific formatting required by
16:00
federal courts. The cost disparity here is just
16:03
staggering. Sustaining complex civil rights
16:06
litigation against state entities usually requires
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massive financial retainers, I mean, hundreds of thousands of
16:13
dollars just to get through the discovery phase.
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Yeah, the father described securing what he calls a team of
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deep lawyers available around the clock for a nominal monthly
16:23
fee of roughly $20. $20 and the capability of the software was
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proven during a specific procedural clash.
16:30
A defending university objected to the scope of a litigation
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hold notice. For those who haven't been
16:35
through corporate litigation, A litigation hold is basically a
16:38
legal freeze ray. That's a good way to put it.
16:40
Yeah, when a lawsuit is filed, you send this notice to the
16:43
opposing party and it legally forces the university to stop
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deleting any emails, internal Slack messages, server logs, or
16:50
admission files that might be relevant to the case.
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It entirely freezes their data retention policies.
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The university's legal team pushed back, likely arguing the
17:00
hold was too broad or overly burdensome.
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So the father fed their legal objection into the AI.
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He prompted it to analyze the objection.
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Based on Federal Rules of Civil Procedure.
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The AI drafted a highly technical, legally rigorous
17:15
response, citing precedence on electronic discovery.
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And that AI generated response was so effective that it
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successfully forced the institution to back down and
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fully comply with the document retention requests.
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I mean, imagine fighting a heavily armored Goliath.
17:29
Yeah, the university legal teams are backed by massive
17:32
multibillion dollar endowments and they use top tier outside
17:35
counsel like Wilmer Hale. The plaintiff is fighting them
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using a slingshot made of predictive text.
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The consequence of this is that it democratizes high stakes
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legal advocacy, it dismantles the financial barrier to entry
17:48
and directly threatens the institutional advantage
17:50
previously held by well funded university legal departments.
17:54
It really forces us to ask whether the artificial
17:56
intelligence is actually generating sound, innovative
17:59
legal strategy, or if it is simply overwhelming the judicial
18:03
system with highly articulate, perfectly formatted paperwork
18:07
that the courts and opposing counsel are forced to spend time
18:11
in mental processing. But relying on this technology
18:13
in a federal courtroom carries severe, documented risks.
18:17
The broader legal community is currently struggling to manage a
18:20
wave of AI malpractice. There are global examples of
18:23
this technology feeling disastrously in legal settings.
18:27
In China, a judge caught lawyers citing completely fabricated
18:30
cases. Yeah, the AI had simply invented
18:33
rulings and assigned them sequential patterned case
18:36
numbers. And in New York and California,
18:38
federal judges have issued formal sanctions and steep
18:41
financial penalties against lawyers who submitted briefs
18:44
relying on legal decisions that literally do not exist.
18:48
These events are known as hallucinations, where the model
18:51
generates false information presented with absolute
18:53
confidence. We need to explore how an AI
18:57
actually hallucinates because it isn't a search engine looking up
19:01
files in a database. Exactly.
19:03
Large language models generate text by predicting the most
19:06
mathematically probable next token or piece of a word based
19:10
on the massive data set they were trained on.
19:12
If you ask it for a legal citation, it doesn't search a
19:15
law library. It predicts what a legal
19:17
citation should look like. It knows that citations often
19:20
have a volume number, a reporter abbreviation, a page number, and
19:23
a year. So it strings those tokens
19:26
together perfectly, creating a citation that looks incredibly
19:29
convincing but points to absolute nothing.
19:31
The father claims to avoid these pitfalls through a very specific
19:34
prompting methodology. Instead of asking the models to
19:38
find obscure case citations which triggers that predictive
19:41
hallucination, he uses multiple different models to cross verify
19:46
every piece of information. That's smart.
19:48
Yeah, if ChatGPT generates a legal theory, he feeds it into
19:51
Gemini and asks it to find logical flaws.
19:53
He focuses the AI prompts entirely on constructing the
19:56
logical architecture of constitutional arguments under
19:59
the 14th Amendment and Title 6. The 14th Amendment guarantees
20:02
equal protection under the law, and Title 6 prohibits
20:05
discrimination on the basis of race, color, and national origin
20:09
in programs and activities receiving federal financial
20:12
assistance. He is using the AI to build the
20:15
framework of how the universities are allegedly
20:18
violating these specific statutes, rather than asking it
20:21
to fetch case law. Furthermore, he is employing A
20:24
fascinating tactical delay. He is deliberately withholding
20:28
the service of legal papers to certain institutions for as long
20:32
as procedurally allowed under the statute of limitations.
20:35
His stated reason is to grant the AI models more time to
20:38
receive updates and grow in their capabilities before
20:41
advancing the case. He knows that the models
20:44
available six months from now will be vastly superior to the
20:47
ones available today. See Delaying a federal civil
20:50
rights lawsuit simply so your software subscription can
20:53
receive an update makes a complete mockery of the judicial
20:57
system. You think so?
20:58
Yes, it treats the federal courts like a beta testing
21:01
environment for consumer technology.
21:04
The courts are designed to resolve actual immediate
21:07
disputes, not to wait around for a tech company to release a new
21:11
language model. I push.
21:12
Back on that completely, I think it is a brilliant, highly
21:15
rational utilization of rapidly advancing technology.
21:18
Really. Yeah, If your opponent has
21:20
unlimited financial resources and an army of paralegals, and
21:24
your primary weapon improves exponentially every few weeks
21:26
through software updates, stalling for an upgrade is the
21:29
most effective legal strategy available.
21:31
Why fight today with version 3.5 when you can fight tomorrow with
21:35
version 4.0? I mean, I see your point.
21:37
What this limits is the effectiveness of traditional
21:40
legal defense strategies. Universities are no longer just
21:44
fighting a human's intellect or a static legal team.
21:47
They are fighting an evolving algorithm that gets smarter,
21:50
faster and more articulate every single week.
21:53
To understand the core allegations drafted by this
21:55
software, we really have to look at how universities allegedly
22:00
achieve their demographic targets through unstated
22:03
methods. Now, as we get into these claims
22:05
about admissions policies, we want to be totally clear with
22:08
you, the listener. We are neutrally reporting the
22:10
claims made in the lawsuit and the provided source material
22:13
regarding politically charged topics like race and admissions.
22:16
Yes, we're not endorsing or taking a side on these
22:18
viewpoints, but merely detailing the exact arguments presented in
22:22
the litigation. The lawsuit heavily details the
22:25
concept of the shadow quota. The plaintiffs highlight that
22:29
several university campuses have a stated official objective to
22:33
become a Hispanic Serving Institution.
22:35
And achieving this specific designation requires a
22:38
university to reach a strict enrollment threshold.
22:42
Specifically, 25% of their full time equivalent undergraduate
22:46
students must identify as Hispanic.
22:49
Reaching this threshold unlocks significant federal funding.
22:53
We are talking about millions of dollars in federal grants
22:55
designed to expand educational opportunities and improve the
22:59
academic attainment of Hispanic students.
23:01
The legal argument presented by the plaintiffs is that setting a
23:04
specific numeric demographic enrollment target of 25% is
23:08
fundamentally incompatible with a strict race neutral admissions
23:12
mandate. If a state law requires you to
23:15
be entirely blind to demographics, but federal
23:18
funding requires you to hit a 25% target, you have a massive
23:21
conflict. The plaintiffs This creates a
23:23
massive financial incentive for admissions officers to utilize
23:27
qualitative subjective proxies to select for specific
23:30
identities, ensuring the university hits the necessary
23:32
threshold for the funding. They support this by citing a
23:35
state auditor report. This report investigated
23:39
admissions practices and found that certain highly selective
23:42
canvases had systematically admitted less qualified
23:45
applicants over more qualified ones.
23:48
Really. Yeah, the auditor noted.
23:49
These decisions were often driven by personal connections
23:52
or institutional priorities that superseded objective academic
23:56
evaluation. Furthermore, the lawsuit cites
23:59
public statements made by a prominent law school Dean.
24:03
According to the complaint, this Dean allegedly discussed methods
24:06
for achieving demographic diversity using subjective
24:09
criteria that cannot be explicitly documented as
24:12
constitutional violations. The plaintiffs characterize
24:15
these methods as deliberate workarounds designed to evade
24:18
state laws while still engineering the demographics of
24:21
the incoming class. But how can a university
24:24
mathematically balance the demographics of an incoming
24:26
class without using some form of a thumb on the scale?
24:30
It is exactly like trying to bake a perfectly balanced cake
24:33
while being legally prohibited from using measuring cups.
24:36
You know you need a specific ratio of flour to sugar to make
24:39
the cake rise properly, but you are legally blindfolded when
24:43
adding the ingredients. You are forced to guess, adjust
24:46
subjectively, and rely on instinct, which leaves a trail
24:50
of inconsistent results that plaintiffs can point to as
24:53
evidence of manipulation. The consequence of this exposes
24:56
the intense friction between a university's desire to secure
24:59
federal diversity funding and their legal obligation to
25:03
maintain strictly race neutral admissions.
25:06
It opens them up to claims of systemic deception, where
25:09
plaintiffs argue the holistic review is just a smokescreen for
25:12
hidden quotas. This entire conflict ultimately
25:16
reveals a fundamental clash between 2 completely different
25:19
philosophies of selection and merit.
25:21
Right on one side we have the Corporate Merit model, which we
25:24
can call the Google Standard. This model relies entirely on
25:27
objective performance validation, technical testing,
25:30
and direct assessment of output. Think about it like testing a
25:32
car's engine output on a dynamometer.
25:35
The dynamometer doesn't care what color the car is, where it
25:37
was built, or who the previous owner was.
25:39
It only measures raw horsepower and torque.
25:42
In the corporate environment, the financial and operational
25:45
cost of a bad hire is incredibly high.
25:48
If an engineer ships broken code, servers crash and millions
25:52
of dollars are lost. Therefore, the organization
25:55
rigorously prioritizes verifiable capability over
25:59
educational pedigree or demographic background.
26:02
And on the other side is the holistic academic model, the
26:04
university standard. This philosophy views the
26:07
selection process not as a reward for past excellence, but
26:10
as a curation process aimed at creating a participatory Society
26:14
of minds. The history of holistic
26:16
admissions actually goes back to the 1920s in the Ivy League.
26:19
Originally, admission was based strictly on entrance exams, but
26:23
when institutions noticed demographic shifts in who was
26:25
passing those exams, they introduced qualitative measures,
26:29
character assessments, personal essays, interviews to basically
26:32
regain control over the social composition of their student
26:35
bodies. Under the modern holistic model
26:37
quantitative excellence, you know the 4.0 GPA and the perfect
26:40
SAT is just a baseline prerequisite.
26:42
It gets your application read. The final selection relies
26:45
heavily on subjective assessments of character, life
26:48
experience, and potential social contribution to the campus
26:51
environment. It is less about testing the
26:54
engine on a dynamometer and more about judging how the car fits
26:57
aesthetically into a curated showroom.
27:00
College admission is not a prize given to the person with the
27:02
highest test score. It's the deliberate construction
27:05
of diverse community. The fact that he was rejected by
27:08
the university but hired by the corporation honestly proves the
27:12
system works exactly as intended.
27:14
You. Really think so.
27:15
Well, he possesses pure technical skill, which the
27:17
corporation needs to build products, but perhaps lacked the
27:22
varied life experiences that a university curates for its
27:25
community. I mean, treating university
27:27
admission as a subjective social engineering project destroys
27:30
national technical competitiveness.
27:32
It's a strong statement. It's true, though.
27:34
It punishes objective, verifiable excellence by moving
27:38
the goal posts based on opaque criteria.
27:41
If a student can perform at a mid level corporate tier writing
27:44
code that is evaluated by blind industry experts, rejecting them
27:49
for an undergraduate degree based on subjective holistic fit
27:52
is a massive institutional failure.
27:55
What this changes is that it forces you, the listener, to
27:59
confront what a university degree actually represents.
28:02
Is it a certification of absolute intellectual
28:04
capability, or is it a subjective marker of social and
28:07
institutional fit? This story is the ultimate
28:10
collision of algorithmic validation, the democratization
28:13
of legal tools, and the opaque nature of elite institutions.
28:17
And if artificial intelligence is now capable of performing the
28:20
job of a top tier corporate lawyer drafting hundreds of
28:23
pages of constitutional analysis for $20.00 a month, how long
28:27
before it can perform the job of the software engineer whose
28:30
merit is at the center of this entire debate?
28:32
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