Luc P

Introducing Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision.

LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So: Data ingest: I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them. IDE: I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides). Q&A: Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale. Output: Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base. Linting: I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into. Extra tools: I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries. Further explorations: As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows. TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

this feels like ages ago

JUST IN: Replit CEO suggests being “brainrotted” & “terminally online” is an advantage in the AI age.

As he said, a lot of it sucks and a lot of it is super good haha Kinda hit or miss, but knowing someone who's local always helps One of the best times of my life I had in a beach villa in a party city... So highly recommended if you like these types of vibes or just want to escape the european winter xD

@levelsio @ItsLucP worth it or not?

🇧🇷 Waking up in Brazil near the ocean South Brazil has lots of great villas available although definitely not at the price point of South East Asia, I'd say 3-5x more expensive and whether that's worth it for you is debatable Build quality of villas in Brazil honestly really varies, a lot of it sucks and is cheap, but a lot of it is built with love and great materials too, kinda hit and miss, it depends if the owner is rich and built it for themselves or not Brazil is also a great place to build a villa, lots of land for sale, approval is fast, and there's no shortage of workers to build it (like in Europe) Brazil also has lots of great architects and interior designers, and they just make beautiful stuff This villa I love because it has that Bali white glossy stone (I think it's boho chic) and it's just great to walk down on barefeet, also I love the rotating stairs and this little jungle inside the living room Then you go outside and you hear the sea! I love living near the sea and I think the salty air really is healthy for you Only bad thing which is common here: no AC in living rooms, only in bedrooms. Why? People like to get the natural wind to cool although at peak summer (like February) it gets boiling hot Oh last thing many villas in Brazil come with a chef included (kinda like Bali and I think there's a colonial connection here as in Bali you sometimes get a "babu" and in Brazil it's called "babá") They cook for you what you want and get groceries etc Nice!

This is Claude Sonnet 4.6: our most capable Sonnet model yet. It’s a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It also features a 1M token context window in beta.

Introducing Claude Opus 4.6. Our smartest model got an upgrade. Opus 4.6 plans more carefully, sustains agentic tasks for longer, operates reliably in massive codebases, and catches its own mistakes. It’s also our first Opus-class model with 1M token context in beta.

I'm Boris and I created Claude Code. I wanted to quickly share a few tips for using Claude Code, sourced directly from the Claude Code team. The way the team uses Claude is different than how I use it. Remember: there is no one right way to use Claude Code -- everyones' setup is different. You should experiment to see what works for you!

There's probably a lot of alpha here... I just couldn't quite fit this into my workflow yet, but I know this kind of setup can make Claude Code even more autonomous

@RCM7 To be fair, its identical to tmux, except the user experience is better (you dont have to memorize so many hotkeys haha)

@ItsLucP Didn't know zellij! Seems interesting 🧐 I've been using tmux but good to have other options!

People using mono repos: have you found a way to use multiple agents working on different tasks? Do we need multiple clones of the repo now so we can be in different branches? Asking for a friend

More on our experiments here: cursor.com/blog/scaling-a…

Reposting just cause I think there is still a lot of alpha regarding this

@justalexoki Claude rn

i don't think you're ready for this

next year we’ll be laughing at how bad opus 4.5 was. scary thought.

Best ROI I've had was with learning how to properly use git worktrees and tmux. I also use bash scripts instead of agents. Easier to call from any folder and are predictable. Bash scripts for everything + worktrees and tmux feels like a superpower.

LLMs killed critical thinking.