Have you watched any TV shows recently you want to discuss? Any shows you want to recommend or are hyped about? Feel free to discuss anything here.

Please just try to provide fair warning of spoilers if you can.

Here is the schedule for the upcoming year

Last week in August - Cats Cradle by Kurt Vonnegut,

Last week in September - Stories of Your Life and Others by Ted Chiang

Last week in October - The Poisoners Handbook: Murder and the Birth of Forensic Medicine by Deborah Blum,

Last week in November - We are Legion (We are Bob) by Dennis Taylor,

December break for the holidays.

Last week in January - Fire on the Mountain by Terry Bissen,

Last week in February - The Truth by Terry Pratchett

Last week in March - The Metamorphosis by Kafka,

Last week in April - The Tea Girl of Hummingbird Lane by Lisa See,

Last week in May - Pnin by Nabokov,

Last week in June - How to Become the Dark Lord and Die Trying by Wexler,

Last week in July - A Psalm for the Wild Built by Becky Chambers,

Last week in August - Light From Uncommon Stars by Ryka Aoki

Last week in September - Dr. No by Ian Fleming

Welcome all to our weekly (ish) gardening group discussion!

Feel free to discuss anything related to gardening, beginner or advanced, challenge or success.

‘Seed’ questions?

Has the weather been working out for you?
What is your favourite gardening tool, or are you looking to get a new one?
What is your biggest error this year?

I've been thinking a lot about LLM assisted development, and in particular why I keep dropping the available tools after a few attempts at using them.

I realized recently that it's taking away the part of software development I enjoy: the creative problem solving that comes with writing code. What's left is code review tasks, testing, security checks, etc. Important tasks, but they all primarily involve heavy concentration, and much less creativity.

Why aren't agents focused on handling the mundane tasks instead? Tell me if I've just introduced a security vulnerability or a runtime bug. Generate realistic test data and give me info on what the likely output would be. Tell me that the algorithm I just wrote is O(n^2).

Those tasks are so much more applicable to matching against existing data, something LLMs should be extremely good at, rather than trying to get them to write something novel, which so far they've been mostly bad at, at least in my experience.