2,642 karma · joined July 11, 2023
Some things you may have heard me say:
-- "If you find you're shooting yourself in the foot, do not reload."
-- "Videodrome was a documentary."
-- "Instead of saying 'no', ask how the world would have to change so your answer could be 'yes'."
-- "Belief flows towards that which can be monetized."
-- "Money is theft. The economy is a lie."
-- "Reflexive modernity has made Ballard's 'High-Rise' A love story."
Nortel, RSA, Borland, Linden and SiFive. I keep working for companies that don't know how to do an exit.
I don't do X, Facebook or LinkedIn. The closest thing I have to social media is [[ https://www.youtube.com/@OhMeadhbh ]] where I've uploaded a few retro-computing related videos.
Strangely, this is the video I'm most proud of: [[ https://youtu.be/J-tdfUXi9PI ]]
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I do text browsers because I live my life in a terminal and it's easier than double-clicking on another part of the screen and waiting for the graphical browser to launch. I also only have 16Gb of RAM, so I can only have a few browser windows open at a time.
And yeah... using a mapping site on a text only browser would suck.
It needs a sentence or two at the top of the page explaining what the app does and why I should be interested.
I'm viewing the content on a desktop web browser, not an iPhone. Maybe Safari renders this differently. In that case you should have text at the top saying "you need to have an iPhone to view this content."
What are you going to do with your new-found CS knowledge?
Are you going to make the next google? Are you going to
get a job at the local insurance company processing
claims? Teaching yourself without a degree is a bad path
if you want to do grad school.
Maybe you want to understand how software works so you can
have a better understanding of the world and participate
more fully in society? Well... I can't argue with that.
I'm bearish on using AI to teach yourself CS because AI
doesn't teach people CS. If you learn something about CS
because you're looking at the output of an AI model, it's
sort of a side-effect.
We probably have a very different idea about what "CS" is.
I think of it as an organized exploration of notation,
processes and proofs related to a branch of applied
mathematics whose subject is general purpose computing
devices. Asking an AI "give me a function to calculate
the fibonacci sequence in rust" isn't going to help you
understand a) where the fibonacci sequence came from, b)
what recursion is (and why and how it was introduced) and
c) how the lexemes in a programming language map to an
abstract process which when reified delivers the fibonnaci
sequence.
I've picked a pretty simple example as a straw-man, mostly
because I think it //should// be knocked down. If this is
what you're doing to "learn CS" then more power to you,
but you're probably not doing yourself any favours.
You probably can use AI with prompts like "generate
example code that implements the abstract factory pattern
and explain how each function relates to the pattern" and
get a fairly decent explanation. Modern agents can keep
enough of a context you can ask it some decent questions
if its examples aren't entirely clear.
I've used and seen other people use Claude Code to
interatively generate design work. Mostly APIs. It's
hardly ever right the first time and Claude Code sometimes
barfs if you ask it to explain why it did a particular
thing. But it's mostly decent and in a few cases it has
pointed out a few ragged edges I didn't notice.
But... I learned how to map between human requirements and
software on my own. I don't know if someone could learn
expert level design by examining the output of a tool that
was trained on mediocre code.
And Claude Code really doesn't understand how to interpret
my prompts about TLA+ and Coq/Roq. It doesn't generate
complete BS. I'm thinking there's just not enough
training data included.
In the old days, if you went to a decent school like
Harvard or Yale or CMU, you could be reasonably assured
the education wouldn't be bad. [[1]] You could go to a
cheaper state state school and get a decent education,
though there was always the chance you would get a crap
instructor or two.
There's an idea that you can teach most people to be
effective software developers by putting them in front of
a terminal with a man page and a c compiler. I believe
this is bullshit. This technique will work for //some//
people, but not as many as sitting you in a class-room and
having an expert explain what the important bits are and
stepping you through the reasoning of why.
I think "learning by AI" may work for //some// people, if
they figure out how to ask the right questions. I
recommend reading decent books like Gries' "The Science of
Programming" or Knuth's "Literate Programming." (You also
have to read SICP because it defines a base level
understanding that all those CS grads have supposedly
learned.)
But I'm reminded of the end of the movie Hidden Dragon,
Crouching Tiger (spoilers ahead) where it is revealed the
antagonist learned kung fu from a well regarded book, but
since they couldn't read, they only looked at the
pictures. They understood the forms but not the
motivations for why the forms were developed. The
antagonist was a formatable foe, but was eventually
defeated because that minor difference in context was
sufficient to lead to their defeat.
I don't think you can learn to be an expert computer
scientist exclusively by reading books / papers. But you
can come close. I don't think you can learn to be an
expert computer scientist exclusively by asking AI to give
you example code, explaining it and critiquing your code.
Mostly because "being an expert computer scientist" is
less about being a 10x coder and more about understanding
the relations between abstract concepts, notation and
symbolic manipulation, how concrete problems are
represented and manipulated and how this all relates to
concretization using computing machinery.
AI gives you an answer, not the understanding embedded in
the text from which the answer was derived.
But if you do it right and you ask AI the right questions,
that understanding can be revealed.
I think my sense is that it is very easy to use AI wrong
and difficult(ish) to use AI as a learning tool. I
sincerely wish you well and would love to read a blog
about your experience.
1. Do not ask about MIT. They're beyond salvaging. File under "old man yells at clouds."
I think it's worth asking what a CS degree is for. Is it
to teach you how to code and make you obviously hire-able
by industry? Maybe it's to teach you how to think about
data and code? If you think it's the former, then AI is
probably going to be a problem for you. If the latter,
it's neutral to somewhat good.
I've been hiring CS grads for 4 decades (yikes!) and
there's definitely been a shift. Not all existing
programs are bad. Not all young software devs are bad.
But... the percentage of recent grads that seem to
understand what data processing systems are about has
definitely fallen.
Us old farts in industry must share some of the blame
here. Our industry seems to be pretty boom or bust.
Someone comes in with a stack of money and tells people to
build { the web | blockchain | AI | virtual worlds | etc }
and suddenly there's a rush. At the start of the gold
rush, we're not sure how to build everything that's going
to be the next google [[1]] so we fill the room with young
kids who have seen some recent tooling and will work
cheap. We don't develop them. We want them to be
compliant drones dancing to a tune played by a CTO and
VP/Eng who got their jobs because they're the children of
the fund investors who gave the startup a bunch of money.
And then we go back to Universities and tell them "OMG!
Your not bar-raising your grads by teaching them __fill in
the blank__!" [[2]]
So... I don't doubt it looks like AI is destroying the
degree. But maybe it's just making it hard to ignore
previous problems with the uni to industry pipeline.
And I didn't mention the Mythical Man Month once in this
comment. I'm getting better.
1. I'm not sure too many people want to be Google at the
moment, but over the last 25 years, they've certainly
done well.
2. I'm intentionally misspelling "you're" because in my
time in industry, I've found only about 15% of people
would pass a 7th grade spelling test.I think I'm lucky... my TV doesn't seem to try to connect to open wi-fi networks. You have to explicitly give it an SSID and tell it to connect. I have chosen not to do that.
I think my SCAAAS service would advertise "Sure we spy on you, but we're too incompetent to do anything with the data."
Which is not to diminish the author's point (which I interpret as twitter is a cess-pit and think hard about what social media you want to engage in and the interface you want to use.) My point is you don't have to spend time on twitter to benefit from this world-view.
I'm not saying mythos didn't find anything new, but several people who should have known better were not using SAST/DAST tools to find potential vulnerabilities before pushing their code into the great unknown. One person I talked to said they didn't bother because GitHub automatically runs SAST tools against pull requests. I looked. Their CICD pipeline had no such tool configured. I'm pretty sure it's more appropriate to say GitHub CAN run SAST/DAST tools, if you configure it, but it won't run SAST/DAST tools by default.
This was a very small sample, but I wonder how common this type of confusion is.
It turns out that software engineering in large organizations is a process greatly influenced by human psychology.
Also, "confidence w/o ability" is the core of the Dunning-Kruger effect. You have to know a fair amount to understand how shit you are at things.
I've noticed the same thing about agentic coding. Not really the agents, but the way people responded to agents. If you were the kind of coder who was a little unsure of yourself, agents made you more unsure of yourself. If you were confident with your abilities, you were more confident.
By the transitive nature of HN comments, we can therefore conclude that LLM coding agents are drugs.
I am now wondering if there's a conversation to be had about Dunning-Kruger and Impostor Syndrome. In the modern agentic era, is it better to hire people who know less than experts, though clearly somewhere above complete novice? Perhaps this is why I find it difficult to find a job. Perhaps I am "overfit" to the world before descriptive ambiguity was an advantage?
I am reminded of the words of J. R. "Bob" Dobbs: "act like a dumb-sh*t and they'll treat you like an equal."
Anyway... yes... I agree with @freefaler on this one. AI is a qualia amplifier.