The REAL Reason Tech Hiring Has Slowed Down (Surprising)
Summary
TLDRThe video discusses the misconception that AI and automation are the primary reasons for the current slowdown in tech hiring. It argues that despite advancements in AI, such as GitHub Copilot and GPT-3, they are not yet capable of fully understanding or editing complex codebases. The real economic drivers behind the hiring downturn are the end of the zero-interest-rate era and changes in tax code, specifically Section 174, which affects how software development costs are treated for tax purposes. The video suggests that if these factors change, tech hiring could rebound quickly. It also advises aspiring developers not to give up on learning and recommends interview preparation for those seeking opportunities in the tech industry.
Takeaways
- 🚫 The notion that AI and GPUs are replacing coding jobs is premature, as AI tools like GitHub Copilot and GPT-3 still struggle with complex coding tasks.
- 📉 The tech hiring downturn is not driven by AI advancements but rather by economic factors, specifically the end of the zero-interest-rate era and changes in tax code.
- 💰 The low-interest-rate environment previously encouraged riskier investments like Venture Capital, which significantly contributed to tech industry growth and high salaries.
- 📈 Inflation and subsequent rate increases have had a downstream effect on tech hiring, as less money is available for investment and more is流向 risk-free investments.
- 🔄 Section 174 of the tax code changes have made software development costs more expensive for companies by requiring amortization of R&D expenses over time, impacting startups and the overall industry.
- 🌐 The pressure on the tech industry may be alleviated if Section 174 is repealed or amended, potentially leading to a surge in hiring.
- 🤖 AI is expected to enhance productivity in software development but is unlikely to eliminate software engineering jobs; it may simply change the nature of coding work.
- 🌟 Despite the current challenges, the tech industry is expected to recover, and those who continue to learn and prepare for a career in tech could be well-positioned for future opportunities.
- 📚 For those pursuing a career in tech, it's crucial to prepare thoroughly for interviews and consider comprehensive programs like Interview Kickstart to maximize the chances of success.
- 🔍 AI's role in coding is currently limited to assisting with error detection and minor improvements in efficiency, rather than taking over the majority of development work.
- 🔄 The ideal use of AI in coding currently involves generating starter functions or boilerplate code, while more complex tasks still require significant manual work and understanding.
Q & A
What are the two main reasons tech hiring is struggling, according to the speaker?
-The two main reasons are the end of the zero interest rate phenomenon (zerp) and changes to the tax code under Section 174, which affects how software development costs are treated for tax purposes.
Why does the speaker believe that AI and automation are not currently the primary drivers of the tech hiring downturn?
-The speaker argues that AI, such as GitHub Copilot and Chat GPT, are still in their early stages and struggle with basic programming tasks like closing parentheses correctly, let alone understanding and editing large code bases.
How has the zero interest rate phenomenon (zerp) influenced tech industry salaries and investment?
-The zerp led to cheap borrowing costs, encouraging more risky equity investments like venture capital, which in turn inflated the tech industry and increased salaries for software engineers and developers in the US.
What is the impact of Section 174 on software development costs and how does it affect startups and larger companies?
-Section 174 requires software development costs to be amortized over time, which means that companies cannot fully deduct developer salaries as a tax expense in the year they are paid. This puts short-term financial pressure on companies, especially startups, as they have to pay taxes on the undeducted portion of salaries.
What is the speaker's view on the potential of AI in the future of software development?
-The speaker believes that AI will continue to improve and could potentially double productivity for developers, but it will not eliminate software engineering jobs. Instead, the nature of coding jobs may change, similar to how new programming languages and frameworks have historically increased productivity.
What advice does the speaker give to those considering entering the tech industry despite current challenges?
-The speaker suggests that individuals should continue to learn and prepare for a career in tech, as they could be well-positioned for opportunities when the industry recovers. They also emphasize the importance of taking interview opportunities seriously and investing in comprehensive interview preparation.
How does the speaker describe the current limitations of AI in code generation?
-The speaker points out that while AI can generate code that is mostly correct, it often lacks the final 5% needed for perfect accuracy. This is problematic because a single line of incorrect code can cause the entire program to fail, and AI is currently unable to understand and debug code at the level required.
What is the speaker's recommendation for preparing for technical interviews?
-The speaker recommends a multi-month program like Interview Kickstart, which is developed by Fang-level software engineers and offers personalized help from a team of mentors and instructors from top tech companies.
How might the potential repeal or amendment of Section 174 impact the tech industry?
-If Section 174 is repealed or amended, it could relieve some of the financial pressures on the tech industry, potentially leading to a surge in hiring and investment in software development.
What is the speaker's perspective on the role of AI in the evolution of software development?
-The speaker sees AI as a tool that will help developers become more productive but does not believe it will replace the need for human developers. They predict that as AI continues to improve, established software engineers will be able to use it effectively to adapt to the evolving landscape of software development.
What does the speaker suggest is the best approach to learning and preparing for a career in tech during the current climate?
-The speaker encourages individuals to go against the crowd, continue learning, and invest in serious interview preparation to be ready for opportunities when the tech industry recovers.
Outlines
🚀 Economic Factors Affecting Tech Hiring
This paragraph discusses the misconception that AI and GPUs are the primary reasons for the struggle in tech hiring. It highlights two economic factors that are actually driving the downturn: the end of the zero-interest-rate era ('zerp') and the changes to the tax code under Section 174. The speaker explains how low interest rates previously led to an influx of money into the tech industry via venture capital, inflating salaries. The current shift towards higher interest rates has reversed this trend, affecting the budget for hiring developers. Additionally, Section 174 now requires companies to amortize software development costs over several years, increasing the short-term financial pressure on companies and startups.
🌐 Impact of Section 174 and Potential Repeal
The paragraph delves deeper into the impact of Section 174, a tax code change that has significantly affected the tech industry. It explains that this legislation requires companies to amortize software development costs over a longer period, increasing taxes in the short term and putting pressure on companies' finances. The speaker mentions a movement to repeal or amend this legislation, which, if successful, could relieve some of the financial pressure on the industry and potentially lead to a surge in hiring. The paragraph emphasizes the importance of keeping an eye on these economic factors for those looking to break into the tech industry.
🤖 AI's Role in Software Development and Interview Preparation
This paragraph addresses the role of AI in software development, clarifying that while AI can assist with catching errors and potentially increasing productivity, it is not yet capable of replacing human developers. The speaker argues that AI can generate code but struggles with understanding and debugging complex codebases. The paragraph also emphasizes the importance of preparing for interviews, suggesting a comprehensive program like Interview Kickstart for those serious about entering the tech industry. The speaker advises viewers not to give up on the potential of AI in the future, suggesting that established software engineers may be well-positioned to leverage AI advancements.
🔍 The Reality of AI in Coding and Future Outlook
The final paragraph focuses on the current limitations of AI in coding and the nature of software development work. It explains that AI is far from being able to understand and work with large, complex codebases, and that debugging and making meaningful changes to existing code remain human tasks. The speaker suggests that AI might reach a plateau in productivity gains within coding, similar to how new programming languages and frameworks have increased productivity in the past. The paragraph concludes with a hopeful analysis, encouraging viewers to gain confidence and stay informed about economic factors affecting the tech industry.
Mindmap
Keywords
💡Tech Hiring
💡AI and Coding
💡Zero Interest Rate Phenomenon
💡Section 174 Tax Law
💡Venture Capital
💡Inflation
💡Software Engineering Jobs
💡Interview Prep
💡AI Productivity
💡Legacy Code Bases
💡Economic Drivers
Highlights
Tech hiring struggles are not due to AI advancements as commonly believed, but rather economic factors.
Nvidia CEO's claim that AI will replace coding is premature, as current AI technologies like GitHub Copilot and GPT still struggle with basic coding tasks.
The downturn in tech hiring is primarily driven by economic factors, specifically the end of the zero-interest-rate era and changes in tax code under Section 174.
Low interest rates previously led to an influx of money into the tech industry, inflating salaries and investment.
Rising interest rates to combat inflation have a downstream effect on tech hiring and investment.
Section 174 of the tax code now requires companies to amortize software development costs over several years, increasing the short-term cost of hiring developers.
The changes under Section 174 have made software developers more expensive from a tax perspective, especially impacting startups.
There is a movement to repeal or amend Section 174 due to its negative impact on the tech industry.
AI technologies are improving but are still far from replacing human developers, as they require human oversight and cannot yet understand or debug complex code.
AI may increase developer productivity but is unlikely to eliminate software engineering jobs, similar to how new programming languages and frameworks have historically improved efficiency.
Despite current challenges, the tech industry is expected to recover, and those who continue to learn and prepare for a career in tech may be well-positioned for future opportunities.
Interview preparation is crucial for those looking to break into the tech industry, with comprehensive programs like Interview Kickstart offering structured guidance.
AI's role in coding is currently limited to generating simple code snippets or functions, rather than managing larger, more complex projects.
The human element in coding remains essential, as AI-generated code often requires manual debugging and refinement.
AI's potential in coding is compared to the assembly line, where it can produce near-perfect results but still requires human intervention for the final touches.
The current state of AI is not yet capable of understanding and working within large, legacy codebases, limiting its utility in real-world development scenarios.
The speaker advises against giving up on learning to code due to AI advancements, as the technology is still developing and has not yet reached a point where it can replace human developers.
The video encourages viewers to stay informed about economic factors affecting the tech industry and to be prepared for the eventual recovery of the market.
Transcripts
it's surprising to me that no one's
talking about the two real reasons Tech
hiring is struggling because despite
what the Nvidia CEO is telling you don't
even learn to code anymore because you
could just use our gpus and write
everything with AI That's not a reality
yet because GitHub co-pilot and Chad GPT
they have a hard time closing
parenthesis for now let alone editing a
code base and understanding it a million
lines and being able to reli make
changes that actually work so we're a
long way off from that and that is not
currently at least driving the tech
hiring downturn which has been going on
for quite a while now so the things that
most people aren't talking about which
are the clear economic drivers of this
which if their reverse can overnight
really turn things around are number one
the end of zerp or the zero interest
rate phenomenon and number two something
barely anyone even knows about which is
section 174 the change to the tax code
now we're going to get into both of
these because if you're trying to break
into the industry if you're deciding
whether it's worth it to still learn
then it's really important to have your
eye on these two things because again if
they change it can have an overnight
surge back to hiring and in fact we'll
talk about the AI thing a bit more but
we do have reason to believe that if
anything that's going to expand the tech
industry and while each developer will
of course become more productive as they
already have this may actually change
the nature of what coding jobs are to an
extent but doesn't necessarily mean that
software engineering jobs are going to
be eliminated they're just going to be
slightly altered in the way that new
programming languages new Frameworks and
paradigms have made people more
productive in the past so let's start by
quickly touching on zerp interest rates
were near zero for a long time so the
cost of capital was very cheap it was
basically free to borrow money with debt
and your risk-free return that is with
treasury bonds and similar was basically
zero so that combination led to people
making slightly more risky Equity style
Investments namely Venture Capital which
drives a huge part of the tech industry
this is the big reason salaries in the
US are much higher than other countries
when it comes to software engineering
software developer salaries because the
industry is basically inflated by all
this money flowing into it now when
there's less overall money coming in of
course that's less of a budget for
spending on developers reinvesting and
similar and more of that money is
Flowing to the risk-free Investments
because when you do the calculation on
return you of course have to factor in
the risk and we can get mathematical
about it but that is the high level
overview and this has been well
documented across history where lower
interest rates basically mean that
certain industries get inflated now the
cause of this of course inflation was
high the rates went up to combat that
and therefore you know it has this
Downstream impact however this is not a
permanent state of things ideally
speaking if things were to return to
their let's say last 30 years average
then that Trend could be reversed now
the other economic pressure is the
section 174 tax lot now just to briefly
cover it basically there was a change to
the tax code where software engineering
uh salaries and any investment into
software development is now counted as
R&D that has to be amortised now what
this means is even as crazy as it sounds
developer salaries you cannot deduct
them as a tax expense so if you're a
startup and you want to hire one
developer at 100K a year and you make
100K profit in the past you could fully
deduct that salary meaning you'd have
zero profit for that year and pay zero
taxes however under Section 174 you have
to deduct that salary over 5 years so
you can only deduct 20K in year one
meaning you have to pay tax on the
remaining 80k in that first year
therefore let's say your tax rate is 40%
on that 80k you have to pay around
33,000 of taxes meaning now you would
have a loss of
33k rather than a break even profit so
of course you can deduct it in the
following years how however that's very
difficult as a startup and it's even
difficult as a larger company though
there can be certain you know tax
benefits to this style of amortization
it puts a lot of short-term pressure on
how much you can actually spend all this
is to say that this is an additional
pressure driver on the industry at large
because now you have to think long term
and really second guess how you're
reinvesting your profits and your
Revenue because there are more tax
implications so this is particularly
devastating to startups however it again
puts that pressure on the entire
industry where now a software developer
in the short term is much more expensive
from an overall cost standpoint you
might be thinking okay companies are
just going to go overseas however for
overseas development work you have to
amortize it over 10 years so it gets
even worse there is a movement let's say
to repeal or edit this nonsensical new
legis ation that went into an effect
right around when the tech layoffs
started that was tax year 2022 so people
are moving to repeal it to change it
because the implications are pretty
devastating however that still hasn't
happened so if we cross our fingers keep
an eye on it this could also relieve
some of that pressure on the industry
bring back a surge of hiring and similar
so what exactly do you do at this point
because of course these two things seem
pretty bad you could just look at the AI
stuff completely give up however at this
stage I don't think that's a great idea
still number one because what's really
your alternative AI is putting pressure
on every industry and while yes software
development breaking into the industry
before was almost too good to be true
where you could just not have a degree
teach yourself and then break in and be
earning 100K it's still good it's still
possible however yes in the current
state of things it is a bit harder that
is also affecting the supply side though
people's sentiments around it have
changed boot camp Admissions and signups
have gone down so if you're kind of
willing to go against the crowd at this
point if you're willing to bet on the
recovery and still learning now you
could be in a very good position in the
near future for breaking in once things
do recover which I do think will happen
now before we talk about AI there is
simply one thing that I have to be blunt
about now more than ever when you get
those interview opportunities if you're
spending all that time applying when you
get your shot you cannot waste it rather
than casually doing Le code programs and
watching videos on YouTube I do think
it's a great idea to do something a
little bit more serious and
comprehensive like interview prep by
interview Kickstart this is a
multi-month program that will really
take you through each step that's needed
to Ace the interviews they are the top
market leader in the US for Tech
interview prep the platform is developed
by Fang level software Engineers hiring
man managers and similar and they have a
large team of mentors and instructors
from Fang companies that are going to
help you out personally with over 20,000
students and great reviews this is the
highest probability way to make sure you
don't miss your shot and that you're
fully prepared so take a minute check
out interview Kickstart see if it looks
great for you and they're going to make
sure that you get the result you want or
you're going to get half your money back
so check out the link and now let's
continue on talking about the industry
specifically AI let's talk a little bit
about AI which I fully believe it will
continue to improve it will let's say
help developers catch their errors as
they're going but it's more to the
degree of 2x in the right hands maybe
it'll speed up your work by 50% that
human element is still required the way
I'm thinking about it too is there's
sort of an ASM toote line for AI
productivity within coding what you see
even in the image and video generation
is it's like 90 to 95% perfect but
there's always a few things wrong and
it's the same with text generation llms
there will be one or two things off and
as suitable as AI is for code generation
that missing 5% which I think is going
to be very hard to get you know that
last 5% actually perfect which is what
we've seen so far that's a big issue
with coding because if one line doesn't
compile if one line doesn't work then
the whole thing breaks so you can't just
be generating code without understanding
in it because then you can't debug
things that are wrong you can't identify
them in a perfect world the AI would be
reading your entire you know 100,000
line code base and you could just tell
it hey I want to add this feature and it
would go and do that but as any
developer working with AI now would tell
you number one it can't do that at all
so you can't really feed it in a large
input even a full long file it won't
accept and even if you could it would
probably have a few of those errors
slash not really match your naming
patterns or conventions make certain
things up so you'd still have to go in
and fix it which could in the current
state even take longer than just writing
it yourself so the ideal way to use it
now is to maybe just generate a starter
function some boiler plate or complete a
line where it's already very clear what
you're going to write however for those
larger tasks it's still very manual and
the reality of working as a developer is
most of it is editing code is reading
understanding and changing things that
are already written to fix bugs make
small changes and similar that's the
reality of how things work now so with
the AI not being able to understand code
in the way that a human can it is still
a very long way from doing the majority
of development work especially when
you're dealing with production code if
you're dealing with a you know fun
sample project completely different
story it can probably build something
for you pretty quick but especially
within companies Legacy code bases huge
repositories it's not really doing the
heavy lifting for you it's just doing a
small sub routine so that's my uh
assessment of the current state of AI I
would not at this point in time listen
to the Nvidia CEO other Tech influencers
saying well it's over stopping to make
videos completely because of this we're
just not there yet and once we do get
there hopefully you could already be in
a position to take advantage of it where
you're maybe already an established
software engineer 5 10 years down the
road and then you already have that kind
of credibility you've mastered The Meta
programming aspects and you can just use
it as a tool to ride the wave of the way
software evolves that's my analysis not
a Doomer analysis more a hopeful one and
I hope you've gained a bit of Confidence
from this video um let me know what you
think of these economic factors I
mentioned of course section 174 is is
crazy do you think this is purely driven
by interest rates or do you think
there's other factors I didn't really
cover let me know in a comment what you
think and I'll see you in the next video
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