Introducing Code Llama, a state-of-the-art large language model for coding
CodeMonkey @ CodeMonkey @programming.dev Posts 0Comments 47Joined 2 yr. ago
The immediate use for this that jumps out at me is batch processing: you take n inputs and return n outputs, where output[i]
is the result of processing input[i]
. You cannot throw since you still have to process all of the valid input.
This style also works for an actor model: loosely coupled operations which take an input message and emit an output message for the next actor in the chain. If you want to be able to throw an exception or terminate prematurely, you would have to configure an error sink shared by all of the actors and to get the result of an operation, you so have to watch for messages on both the final actor and the error sink.
I knew basic CLI commands (such as cd
and ls
) for a while, but did not do learn much more. Some things have helped me grow my skills:
- Necessity: Some times I need to do something on a VM or container that does not have a graphical interface installed. Some utilities only have a command line interface and not a graphical client. My only option is to Google how to do it. The more I do it, the less I have to Google and the more focused my searches become (instead of searching for "How to do x", I search for "How to do x in utility").
- Learning from others: For many tasks, I follow internal or external guides, which typically use CLI commands. Often I look at how my coworkers accomplish tasks and pay attention to what commands they use. Then, when I have time, I look up any new commands I saw and decide if they will be useful for me too. Lately, I have been doing code reviews that involve shell scripts. Those are especially nice, because I can take my time, going line by line, and understand what each command does.
- Keep notes: Every time I find a command that I think I will need again, I copy it into a text file (and I have many such text files). It also makes it easier when I need to run the command with slightly different arguments (a different commit id or something), I can just edit the command in my editor (with searching and undo) and paste it in to my terminal with all the flags and arguments correct.
GUIs are easier to learn, but they are not always available. Many services only have a CLI client. If you are connecting to a remote server or, especially, a container to debug it, it may not have a window manager installed. If you know how to do something via the CLI, you can automate it with a shell script.
I also exclusively use the git CLI. I have tried to use a graphical client and could never figure out what it was doing and what was going on. I probably picked it up so easily because when I learned git, I was already used to using a CLI version control client. At the time, I was working at a company that heavily used Perforce and had a custom wrapper around the p4
cli that injected a bunch of custom configuration.
My favorite YOLO-Driven Development practice (from a former employer) was Customers as QA. We would write code, build the code, and ship it to the customer, then the customer would run the code, file bugs for what broke, and we would have a new build ready next week.
It provides many benefits:
- No need to hire QA engineers.
- Focuses developer debugging time on features actually used by customers instead of corner cases that no customer is hitting.
- Developers deliver features faster instead of wasting time writing automated tests.
- Builds are faster because "test" stages are no-op.
One time a developer was caught writing automated tests (was not sure in the correctness of his code, a sign of a poor developer). Our manager took 15 minutes out of his busy day to yell at him about wasting company resources and putting release timelines in jeopardy.
Yes, you should use third party tools (just don't take credit for them, maybe even credit the tools used in the footer). In a real job, you would leverage third party libraries to work more efficiently, so you should do the same when showing off your skills.
Also, when you find a script try to understand what commands they are using and with what flags.
We tried to ask our interview question of ChatGPT. After some manual syntax fixes, it performed about as well as a mediocre junior developer, i.e. writing mutithreaded code without any synchronization.
Don't misunderstand, it is an amazing technical achievement that it could output (mostly) correct code to solve a problem, but it is nowhere good enough for me to use. I would have to carefully analyze any code generated for errors, rewrite bits to improve readability (rename variables to match our terminology, add comments, etc), and who knows what else. I am not sure it will save me much time and I am sure it will not be as good as my own code. I could see using an AI to generate sophisticated boiler plate code (code that is long, but logically trivial).