Why do you need a CI at all? You can use a queue like Oban on your own server to kick off jobs. And with AI you can add new jobs, so long as they are well defined, in a few minutes and schedule them however you like. I only recommend this because I use a similar system. If you are planning on GitHub's recent instability to be improved in the future, I would not get your hopes up, they have a long history of instability.
Programming languages are most interesting area in CS for the next 10 years. AI need criteria for correctness that can't be faked so the boundary between proof verification and programs will become fuzzier and fuzzier. The runtimes also need support for massively parallel development in a way that is totally unnecessary for humans.
“Another parable put he forth unto them, saying, The kingdom of heaven is like to a grain of mustard seed, which a man took, and sowed in his field: Which indeed is the least of all seeds: but when it is grown, it is the greatest among herbs, and becometh a tree, so that the birds of the air come and lodge in the branches thereof.”
Yes, these are the central mysteries of Christianity. We have to reckon with imperfect people writing about a perfect person. And there is never any absolute proof or disproof. We make the justification by faith alone.
You have to move up or down to survive. In 10 years we'll either be managers (either of humans or agents), or we'll be electrical engineers. Programming is done! I for one am glad.
* AI can replace knowledge workers - most of existing software engineers, managers of all levels will loose their job and have to re-qualify.
* AI requires human in the loop.
In the first scenario, I see no reason to waste time and should start building plan B now (remaining job markets will be saturated at that point).
In the second scenario, tech-debt and zettabytes of slop will harm companies which relied on it heavily. In the age of failing giants and crumbling infrastructure, engineers and startups that can replace gigawatt burning data center with a few kilowatt rack, by manually coding a shell script that replaces Hadoop, will flourish.
Most probably it will be a spectrum - some roles can be replaced, some not.
One thing that slop often lacks is framing. I want to know why a particular person designed it this way. What were the constraints of the original team? What were their goals at the time? How did these change over time? Just knowing "TikTok aims for 99.99% uptime and low latency" without any story, well I don't find it very useful. I'd rather get an interview of one of the first architects!
2 things have not changed since the advent of AI, and never will change. The first is the calculus of computation. The second is the engineering of computation. All coding is just some interesting combination of these two forms of logic.
You can learn both of these quickly to a deep level with only 2 books. For the calculus of computation, read "Structure and Interpretation of Computer Programs" (SICP) by Abelman and Sussman. It is available for free.[0] If you understand all of this book, you understand all of the fundamentals of computer science. Every program you write from now on will be understandable to you, with enough persistence. But most importantly you will be able to think in computer programs by second nature, and communicate in this language. And when you talk to AIs in this language, they become exceedingly precise and powerful, because you lost the ambiguity in how you are conceptualizing the program.
For the engineering of computation, read "The Elements of Computing Systems" by Nisan and Schocken.[1] An abridged version of this book is available for free in the form of the Nand2Tetris course. In this course you will start with an imminently simple digital construct, and use it to build step by step a full working computer that can run Tetris. You could even write a Lisp from SICP on this computer, and pretty easily too as you'll see in SICP itself! Once you have completed both books you'll have met in the middle between abstract computer science and concrete computer science: coding.
Just like in your math class, you can see that one side of a right triangle is always longer than the others, but you cannot understand how or why or explain it or work with it until you can comprehend some simple theorems and functions, you cannot truly compose computer programs until you can speak the language of computer science. It used to be that you could make a career by copying code you saw online, patching bits and piece together to create basically working code. But that era is over. AI reads and writes and searches millions of times faster than you. But still only humans are capable of new compositions. But in order to create these new compositions you have to be able to speak a mutual language that you and the AI can understand. That language is computer science, and it hasn't changed since time began and it won't change in 10, 100 or 1,000 years from now when AI is capable of doing anything and everything better than we can. So if you want to stop struggling and start creating new and exciting things with computers, read these 2 books!
I highly recommend John Ventimiglia's audiobook reading of the Original Scroll. It's my favorite reading of any audiobook. He perfectly captures all of the tone and characters and rhythm.
On the Road is the American Odyssey. A lost man separated from his wife and returning from war takes a long and twisted path over many years to find his way home, despite countless setbacks and moral failings, at the mercy of the divine all along the way.
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