In the beginning of August 2026, I started a hobby project: building a MongoDB-like database. I have 20 years of industry experience and a master's degree in computer science, so I followed a disciplined, spec-driven development model using Claude, Kiro, Qwen Coder, and Cursor.
The first version was built in about two weeks of part time work. Then I started exploring. I learned relational algebra, researched almost every kind of database, reworked the internals, built a small relational algebra layer, a query planner, and an executor, covering everything from the backend storage to the query language. I learned more in those two months than in the previous 20 years.
Did I care what code the agents wrote? No. I read zero lines of generated code. What I cared about was correctness, verified through tests, and the high-level product features. For the first time in my career, I acted as a senior product manager, steering the project along the right roadmap. Without AI, I wouldn't have been able to do that.
When you have superpowers in your hands, you don't need to worry about the laundry. For the first time in my career, I can produce code in C, C++, Java, .NET, or any other language. Sometimes it takes me longer than a senior developer in that language, but does that really matter? Absolutely not.
Writing documentation and code by hand in 2026 is like driving a horse and buggy. It doesn't matter how skilled you are with the reins; you'll never compete with a car.
My hobby db project isnt opened source yet.
"My project isn't open sourced yet" underlines the problem. There has been a massive explosion of software that works, but badly. The average user experience suffers as a result.
Call me cynical, but I dont remember interacting with well engineered software, outside of pure, mainstream opensource repos.
Most of proprietary software is just crap, and always has been. The agents are not producing worse code than typical, demotivated, i-dont-care-what-i-am-building-i-wont-try-using-it corporate development teams have over the years. I'd even bet that because now making changes and fixes is so much easier, the user perceived quality will trend upwards for popular stuff.
I would bet every single dollar I have that if the source was shared, there would be 15 "big brains" showing up to point out how it's actually "bad".
I have seen a decent amount of clearly AI generated software that's useful, would likely not have been made without AI, and is better for for being AI generated. With AI, people make improvements that they would have never have bothered spending time to do manually. If anything, having uncharacteristically good "production value" in a clearly hobby project is how I typically spot AI use in projects that aren't obvious vibe coded slop.
The code itself may or may not be spaghetti. Not that I care as a user. User experience and code quality had never a particularly strong correlation even before AI.
Okay, you're going to need to go into a lot more detail about exactly how you learned more in 2 months than you did in 20 years having read zero generated code.
Code examples are literally bread and butter when it comes to learning.
How can you learn without looking at code? That's like saying that you can learn to be an architect without looking at drawings...
I didnt know what is relational algebra is? why query plannering execution done in certain ways. What are backend storage system available in open source or commercial products. What are the traitts of each backend storage and how does that effects the replication and failover scenarios. I know all of this, I implemented a small subset of sql's relational algebra in my project and its correct and concise. I expored different backend storage systems, first tried one, then move to next and then 3rd in line, all that in span of less than a month without ever looking what code the coding agents generates.
>I didnt know what is relational algebra is? why query plannering execution done in certain ways. What are backend storage system available in open source or commercial products. What are the traitts of each backend storage and how does that effects the replication and failover scenarios. I know all of this, I implemented a small subset of sql's relational algebra in my project and its correct and concise. I expored different backend storage systems, first tried one, then move to next and then 3rd in line, all that in span of less than a month without ever looking what code the coding agents generates.
To be as frank as possible--you "understand" these topics in the same way someone who watches pop-science videos about astronomy "understands" astronomy. That is to say, you have a surface level understanding at best.
This is the sort of behavior people have been talking about over the last few years. People confuse what the AI "understands" with what they understand, and it makes them say delusional stuff like "I learned more in the last 2 months than in 20 years."
To make this concrete, it takes someone about 4 months to go through a university course.
They might take six courses at a time.
So you are saying that you learned more than 400 times as much content as a university course?
I'm sorry but this just sounds hilarious And unlikely to most people, and it comes off a bit crazy sounding... For example, do you actually think you could even pass a single university course exam on introductory relational algebra without AI I assistance at all?
I think what is more likely is that you feel confident trying to solve problems with AI's help.
That is not learning.
To learn something, it has to be in your brain, not the AI.
Learning is not the same as becoming capable.
There's an ocean of difference between those two
You need to learn the concepts not implementation detail. If you know what is relational algebra and AI teaches you this in hours then you dont need to know the implementation details any longer. If you can borrow intelligence to solve a problem, you should do that. We, the most IT industry is already working in high level languages which is not how the computer works but abstractions over abstractions that very very few people know the entire cycle of a program how it runs. So AI is not a future abstracton, it is already here and its "intelligent" as opposed to other abstractions. Writing code or documentation by hand is gone, its past. All programming languages, framworks are implementation details and AI has already mastered them, we need to now move on to high goals than learning how to write a loop.
I don't even disagree with you here. It's something I've said in the past about things like algorithms. Sometimes knowing a surface level thing allows you to utilise it without necessarily needing to know the implementation level details.
But you did not LEARN Relational Algebra. You learned OF relational algebra. And there's a pretty stark difference there.
Those with 20 years of experience are crushing it.
My worry is not about us. The worry is about the kids. I'm tech lead. I don't think the juniors at my company are learning anything from me. I'm not certain they're learning anything about _software_. Idk, I could be wrong. We barely talk because everyone has become so siloed.
I am trying. The main issue is it would be extremely annoying for the juniors, who have work to get done, and prefer to throw problems at Claude rather than ask me questions.
In general, I believe learning usually needs to be driven by the learner.
Here is one my project is opened source. Highway <a href="https://github.com/System-D-AB/highway" rel="nofollow">https://github.com/System-D-AB/highway
It is fault tolerant, distributed broker which gurantees durable queues, pub/sub and RPC all into one easy to use programming model. The application is in production and passing millions of messages every day with sub-millisecond performance, you can crash a server and replica set invokes within seconds without losing any messages.
The entire project is created in less than a month with part time working, just because of AI. Its in production and already proven.
Not that Github vanity metrics are the end-all be-all, but let's be real: this project has 0 forks and 1 star. You don't know if it properly functions because nobody is using it. Calling it "proven" production software is a joke.
Yes, you're running it in production, but to put it in perspective: PHP 5 was also proven production software at one point, running way more production instances than you.
I'm sorry, I just don't buy the hyperbole. Something with your previous approach was deeply wrong if you condensed 20 years of learning into 2 months.
Databases, programming languages, compilers, operating system internals, networks these things are pretty complicated in itself. With your day jobs you can't master any of this without spending years in your part time.
But now at least you can start something of your interest and learn on the way. Learning a new concepts, implements it, test it and reproduce cycle is so fast that it is only possible because of AI. You need to find the process which works for you. AI already knows every programming language, its best practices, entire computer science knowledge is already mastered by current state of AI. There isn't any single database internals which Ai doesnt know. If you dont believe just start implementing JavaScript or C compiler yourself without even having knowledge of compilers and in a few weeks you will where you stand. You will not only having a functional compiler but you will know the internals of compiler constructions, all the concepts.
I also don't care the exact cpu instructions my compiler emits. In fact I have no idea what the "stuff" it emits means (beyond the most elementary)... That doesnt stop me from creating very useful software that maybe even billions of people rely on (once you include the users of products that use our software)
> For the first time in my career, I acted as a senior product manager, steering the project along the right roadmap. Without AI, I wouldn't have been able to do that.
This may be Dunning–Kruger effect in action. (this is not an insult, but showing cognitive biases)
tegeek · · focus · HN ↗
The first version was built in about two weeks of part time work. Then I started exploring. I learned relational algebra, researched almost every kind of database, reworked the internals, built a small relational algebra layer, a query planner, and an executor, covering everything from the backend storage to the query language. I learned more in those two months than in the previous 20 years.
Did I care what code the agents wrote? No. I read zero lines of generated code. What I cared about was correctness, verified through tests, and the high-level product features. For the first time in my career, I acted as a senior product manager, steering the project along the right roadmap. Without AI, I wouldn't have been able to do that.
When you have superpowers in your hands, you don't need to worry about the laundry. For the first time in my career, I can produce code in C, C++, Java, .NET, or any other language. Sometimes it takes me longer than a senior developer in that language, but does that really matter? Absolutely not. Writing documentation and code by hand in 2026 is like driving a horse and buggy. It doesn't matter how skilled you are with the reins; you'll never compete with a car. My hobby db project isnt opened source yet.
alansaber · · focus · HN ↗
aenis · · focus · HN ↗
Most of proprietary software is just crap, and always has been. The agents are not producing worse code than typical, demotivated, i-dont-care-what-i-am-building-i-wont-try-using-it corporate development teams have over the years. I'd even bet that because now making changes and fixes is so much easier, the user perceived quality will trend upwards for popular stuff.
WarmWash · · focus · HN ↗
Aozora7 · · focus · HN ↗
The code itself may or may not be spaghetti. Not that I care as a user. User experience and code quality had never a particularly strong correlation even before AI.
smallpipe · · focus · HN ↗
Narciss · · focus · HN ↗
feoren · · focus · HN ↗
This is the opposite of really striving to understand what your AI is producing.
adverbly · · focus · HN ↗
Code examples are literally bread and butter when it comes to learning.
How can you learn without looking at code? That's like saying that you can learn to be an architect without looking at drawings...
tegeek · · focus · HN ↗
jplusequalt · · focus · HN ↗
To be as frank as possible--you "understand" these topics in the same way someone who watches pop-science videos about astronomy "understands" astronomy. That is to say, you have a surface level understanding at best.
This is the sort of behavior people have been talking about over the last few years. People confuse what the AI "understands" with what they understand, and it makes them say delusional stuff like "I learned more in the last 2 months than in 20 years."
adverbly · · focus · HN ↗
They might take six courses at a time.
So you are saying that you learned more than 400 times as much content as a university course?
I'm sorry but this just sounds hilarious And unlikely to most people, and it comes off a bit crazy sounding... For example, do you actually think you could even pass a single university course exam on introductory relational algebra without AI I assistance at all?
I think what is more likely is that you feel confident trying to solve problems with AI's help.
That is not learning.
To learn something, it has to be in your brain, not the AI.
Learning is not the same as becoming capable.
There's an ocean of difference between those two
tegeek · · focus · HN ↗
podgietaru · · focus · HN ↗
But you did not LEARN Relational Algebra. You learned OF relational algebra. And there's a pretty stark difference there.
adverbly · · focus · HN ↗
I apologize for being blunt, and I don't mean to sound argumentative here, I'm just trying to give you an outsider's perspective:
You should not tell people you learned more in 2 months than in 20 years.
That's all I meant.
It makes you sound crazy, and its also wrong.
Maybe you built more or you feel more capable than you have felt for 20 years, but you surely did not learn more.
I don't need to hear anything from you about how the capability of the average developer has changed. I'm well aware of that already.
lawnmowed · · focus · HN ↗
It's fairly standard for undergrad CS programs and most textbooks include at least a section on relational algebra.
andrenatalbr · · focus · HN ↗
hdgvhicv · · focus · HN ↗
NoDodgeQuestion · · focus · HN ↗
and 9/10 times project open source, project bad slop
howunfortunate · · focus · HN ↗
Those with 20 years of experience are crushing it.
My worry is not about us. The worry is about the kids. I'm tech lead. I don't think the juniors at my company are learning anything from me. I'm not certain they're learning anything about _software_. Idk, I could be wrong. We barely talk because everyone has become so siloed.
draftsman · · focus · HN ↗
howunfortunate · · focus · HN ↗
In general, I believe learning usually needs to be driven by the learner.
falserum · · focus · HN ↗
- ignore that it is annoying to some. (To certain degree, it is unavoidable and it is ok)
- reserve 1 hour meeting every month(week?) to demo/review/present.
- get buy-in and support words from manager
tegeek · · focus · HN ↗
It is fault tolerant, distributed broker which gurantees durable queues, pub/sub and RPC all into one easy to use programming model. The application is in production and passing millions of messages every day with sub-millisecond performance, you can crash a server and replica set invokes within seconds without losing any messages. The entire project is created in less than a month with part time working, just because of AI. Its in production and already proven.
mjr00 · · focus · HN ↗
Yes, you're running it in production, but to put it in perspective: PHP 5 was also proven production software at one point, running way more production instances than you.
mstaoru · · focus · HN ↗
zparky · · focus · HN ↗
~41k SLOC, ~11k lines of comments
xpct · · focus · HN ↗
tegeek · · focus · HN ↗
edg5000 · · focus · HN ↗
pjc50 · · focus · HN ↗
But why though?
n3t · · focus · HN ↗
lol
maerF0x0 · · focus · HN ↗
I also don't care the exact cpu instructions my compiler emits. In fact I have no idea what the "stuff" it emits means (beyond the most elementary)... That doesnt stop me from creating very useful software that maybe even billions of people rely on (once you include the users of products that use our software)
[deleted] · · focus · HN ↗
[deleted]
nerdyadventurer · · focus · HN ↗
This may be Dunning–Kruger effect in action. (this is not an insult, but showing cognitive biases)
1: <a href="https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect" rel="nofollow">https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect