I think Anthropic and OpenAI have found product-market fit

Re:I think Anthropic and OpenAI have found product-market fit by scribble0242 on Wednesday May 27, 2026 @10:39PM (#48303721)

This worked for me with qwen3.6-36b-a3b even at a q4 quant. I ran pi in a docker container and it had to figure out how to install python as well. I used the same initial prompt you had without any additional. You talked about Qwen 3.6, but then said you tried Qwen 3.5 in lmstudio. Not sure if you meant Qwen 3.6. I ran with llama.cpp llama-server with the recommended settings from unsloth.

I'm not an expert in SQLLite so I can't say if this is 100% correct, but it seemed directionally similar to the conclusion from claude.

  ### TL;DR
  
  - Authorizer + EXPLAIN:  No — authorizer only sees SQLITE_INSERT, not VDBE opcodes
  - EXPLAIN opcode analysis alone:  Yes — Delete opcode at position 10 is the unique signature of INSERT OR REPLACE / REPLACE

I can't help but think the not-so-distant future will see language models expected on commodity personal computing devices.

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Re:I think Anthropic and OpenAI have found product-market fit by simonw on Wednesday May 27, 2026 @10:55PM (#48303856)

OK that's a very good answer! Do you mind sharing the transcript?

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Re:I think Anthropic and OpenAI have found product-market fit by scribble0242 on Thursday May 28, 2026 @11:40AM (#48310572)

Sure I cleaned up the jsonl session file a little here: https://pastebin.com/PL9EPn9Y

I tried it a second time, and it spent a lot of time trying to figure out some authorization issue, so definitely not a slam dunk. I might run it a few more times for science. But while this is a new model it's also quite lightweight, and as hardware adapts and improves it seems inevitable that for many use-cases a packaged language model running locally will do the trick.

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Re:I think Anthropic and OpenAI have found product-market fit by Balinares on Thursday May 28, 2026 @07:45AM (#48307578)

So one of the prominent LLM advocates known for testing every model shared a prompt intended to exhibit Opus 4.7 capabilities, and Qwen 3.6 sorted it out okay? Interesting.

Not saying they're equivalent, local models still decohere much quicker as the context grows in my experience. But... Interesting.

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