Sun, Jun 15, 2025

Weekly Notes and Discoveries | S Anand

"Database migrations are like version control for your database." X. dbmate seems like an apt choice. #dev #database #future #markdown

PDF plumber seems a good way to extract PDF structure and internals. #document-conversion

yq is like jq but for YAML, XML, CSV, and TOML as well. dasel is similar but not updated. #ai-coding-tools #github #html #markdown

qsv is a data wrangling toolkit for CSV files. xan is similar. csvkit, of course, is the most popular. An alternative, xsv is no longer updated. #ai-coding-tools #markdown

The Singularity Reddit is apparently a good source of LLM news. #future #llm-ops

Reddit has RSS feeds for each subreddit:
- Basic: https://www.reddit.com/r/<subreddit>.rss
- All new: https://www.reddit.com/r/<subreddit>/new.rss
- Daily top: https://www.reddit.com/r/<subreddit>/top.rss?t=day (replace day with hour, week, month, or year)
- Private reddit feeds are available at https://www.reddit.com/prefs/feeds/

Almost every industry will enact some form of AI backlash. At that point, I expect model evaluation will become a powerful service and in great demand. #future

With LLMs, the limiting factor is the questions I'm smart enough to ask. But this has always been true with new technology. The real challenge is knowing "What KINDS of questions should we become smarter at asking" so that LLMs can execute them. A few learnings: #future #llm-ops
- Practice Prompt Reviews. Check if each prompt has clarity, context, and verifiability. Also, see how others would ask this. Internalize patterns

Browserbee is a Chrome extension that lets you chat with your browser. Like Cursor/Windsurf but for browsing. #web-dev

Anthropic's Claude Code internal use cases are interesting. #ai-coding-tools #code-agents #future

"We have a new prompting report: Prompting a model with Chain of Thought is a common prompt engineering technique, but we find simple Chain-of-Thought prompts generally don’t help recent frontier LLMs, including reasoning & non-reasoning models, perform any better (but do increase time & costs)" Ethan Mollick #prompt-engineering

Evals FAQ by Hamel Hussain is a thoughtful compilation of how to evaluate LLMs. Insights: #ai-coding-tools #best-practices #llm-ops #optimization
- When running RAG on docs, use hybrid searhch for retrieval. But tools work better for code and SQL works better for data.

The Illusion of Thinking paper by Apple shows that reasoning scales only up to a point. Beyond a complexity threshold, models give up. This aligns with what I saw crudely with mental math. "Think step by step" helps, but only for medium complexity problems.