I went down that rabbit hole with Cursor and it's pretty good. Then I tried tools like Cline with Sonnet 4 and Claude Code. The Anthropic models have huge conte

I went down that rabbit hole with Cursor and it's pretty good. Then I tried tools like Cline with Sonnet 4 and Claude Code. The Anthropic models have huge context and it shows. I'm no expert, but it feels like you reach a point where the model is good enough and then the gains are coming from the context size. When I'm doing something complex, I'm filling up the 200k context window and getting solutions that I just can't get from Cursor or ChatGPT. I had a data wrangling task where I determine the value of a column in a dataframe based on values in several other columns. I implemented some rules to do the matching and it worked for most of the records, but there are some data quality issues. I asked Claude Code to implement a hybrid approach with rules and ML. We discussed some features and weighting. Then, it reviewed my whole project, built the model and integrated it into what I already had. The finished process uses my rules to classify records, trains the model on those and then uses the model to classify the rest of them. Someone had been doing this work manually before and the automated version produces a 99.3% match. AI spent a few minutes implementing this at a cost of a couple dollars and the program runs in about a minute compared to like 4 hours for the manual process it's replacing.