1️⃣ Python is being phased out for performance‑critical and AI work
“I was so into Python for 10 years… moving them to faster languages in a post‑AI codebot world. Mostly moving to Go these days.” — brianwawok
“All of our services we were are significantly faster and more reliable. We used Rust, it wasn’t hard to do.” — mountainriver
“Google models still fail it … I wonder if the lack of typing in a lot of the training data makes Python harder to reason about?” — prodigycorp
2️⃣ Core language / ecosystem complaints (typing, GIL, lazy imports, version churn)
“Python is such a weird language. Lazy imports are a bandaid for AI code base monstrosities … Type decoration … too slowly iterated … GIL … boxed it into a long‑term pit of sadness.” — zabzonk
“The quality issue doesn’t seem unique to Python … library version changes … type‑hinting … degrade.” — stuaxo
“Training data is often Python‑2 or low‑quality, making static‑typing benchmarks fail.” — prodigycorp
3️⃣ Ambivalent outlook – Python still dominates beginners and niche domains, but its growth is questioned
“Python’s REPL, beginner simplicity and massive training data keep it alive, yet ‘it’s horrifically slow (50‑200× slower than C++, Rust…)’ and unlikely to improve.” — IshKebab
“I’m happy to see it go. It didn’t win because it was the best language.” — zabzonk
These three themes capture the dominant viewpoints: a move away from Python toward faster languages; critical assessment of Python’s design and tooling; and a split between its lingering utility and the push for alternatives.