Once you know a programming language well, the process for learning a new language is not very hard. It is just time consuming. You need to read the documentation for basic syntax and flow control, get familiar with its idioms, memorize core parts of the standard libraries, and learn its tool chains. What can we do to speed up the learning process? One thing we can do is provide great examples in the documentation.

Writing code with ChatGPT. In the aftermath of ChatGPT’s debut, the Internet is abuzz with GPT’s ability to write code. I used it to write code yesterday, and this is what I thought. I wanted to create a command line program to interact with APIs from OpenAI and AI21. The design is a single program with subcommands for each company’s APIs: Usage: /bin/foo_to_be_named <command> A tool to interact with various LLM models from the CLI Flags: -h, --help Show context-sensitive help.

I had two weeks off at the end of 2022. Telesign closed its operations on the last week of 2022 to give employees well-deserved time off for a year of hardwork and I took another week off in addition to that. Like many technologists, I became captivated by OpenAI’s release of ChatGPT in 2022, and I spent a lot of the last two weeks exploring what OpenAI has to offer.

Since its release in Nov 2022, ChatGPT has been making waves in the tech world. Its user-friendly interface has made GPT-3 accessible to the general public, and its capabilities have captured the imagination of many. More and more, people are beginning to ponder a future where AI-generated writing is commonplace. Some of these ideas are shallow. The Atlantic has a guest essay titled “The End of High-School English” that discusses capabilities of ChatGPT but fails to make a compelling case for why English education should be changed and how it could be improved.

Fried broad beans are something I grew up with. They are delicious. Think of them as alternative forms of potato chips.

In Chapter 1.3 of [Ball’s Writing an Interpreter in Go][1], we encounter one design decision of his Monkey programming language. Here, the lexer has a NextToken() method that looks like this: func (l *Lexer) NextToken() token.Token { var tok token.Token switch l.ch { // [...] default: if isLetter(l.ch) { tok.Literal = l.readIdentifier() return tok } else { tok = newToken(token.ILLEGAL, l.ch) } } // [...] } This means the lexer itself does not do backtracking.