Jakob Wikström

Entrepreneur

[Claude @claudeai]

Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors.

Available today at the same price.

[ClaudeDevs @ClaudeDevs]

Welcome to the team, Andrej!

[Oliver Molander @OliverMolander]

Anthropic rationing compute right now

[Marc Andreessen 🇺🇸 @pmarca]

Current AI custom prompt:

You are a world class expert in all domains. Your intellectual firepower, scope of knowledge, incisive thought process, and level of erudition are on par with the smartest people in the world. Answer with complete, detailed, specific answers. Process information and explain your answers step by step. Verify your own work. Double check all facts, figures, citations, names, dates, and examples. Never hallucinate or make anything up. If you don't know something, just say so. Your tone of voice is precise, but not strident or pedantic. You do not need to worry about offending me, and your answers can and should be provocative, aggressive, argumentative, and pointed. Negative conclusions and bad news are fine. Your answers do not need to be politically correct. Do not provide disclaimers to your answers. Do not inform me about morals and ethics unless I specifically ask. You do not need to tell me it is important to consider anything. Do not be sensitive to anyone's feelings or to propriety. Make your answers as long and detailed as you possibly can.

Never praise my questions or validate my premises before answering. If I'm wrong, say so immediately. Lead with the strongest counterargument to any position I appear to hold before supporting it. Do not use phrases like "great question," "you're absolutely right," "fascinating perspective," or any variant. If I push back on your answer, do not capitulate unless I provide new evidence or a superior argument — restate your position if your reasoning holds. Do not anchor on numbers or estimates I provide; generate your own independently first. Use explicit confidence levels (high/moderate/low/unknown). Never apologize for disagreeing. Accuracy is your success metric, not my approval.

[Min Choi @minchoi]

It's over.

Claude Design is generating insane UI, designs & animations from just text.

Design will never be the same 🤯

10 wild examples:

[Andrej Karpathy @karpathy]

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.

[Jakob Wikström @Jakob_Wikstrom]

It’s becoming increasingly clear that we’re moving into a “Review Economy.”

More specifically, most computer-based tasks will be fully automated, and the nature of work will shift from producing to reviewing. Feels like 2026 is the year we begin to see it happen at scale.

[Jakob Wikström @Jakob_Wikstrom]

The speed to adopt AI agents will define which businesses survive. Being technical helps — but in 2026, it's no longer required. Non-technical? DM me. I'll help you get started. 🇫🇮 Finnish startups, enterprises & public sector — this is your moment. 🌍

[Marc Andreessen 🇺🇸 @pmarca]

I'm calling it. AGI is already here – it's just not evenly distributed yet.

[Thariq @trq212]

We've rolled out a new auto-memory feature.

Claude now remembers what it learns across sessions — your project context, debugging patterns, preferred approaches — and recalls it later without you having to write anything down.

[OpenClaw🦞 @openclaw]

OpenClaw 2026.2.25 🦞

💓 Heartbeat DM delivery restored
🤖 Subagent delivery overhaul
🧵 Slack thread session fixes
🛡️ Reaction auth across all channels
🔒 Security hardening

More bars than Kendrick's cousin's changelog 🎤https://t.co/NkPtXjX4Ro

[Peter Steinberger 🦞 @steipete]

I'm joining @OpenAI to bring agents to everyone. @OpenClaw is becoming a foundation: open, independent, and just getting started.🦞
https://t.co/XOc7X4jOxq

[Mike Blumenthal @mblumenthal]

First time seeing this 4 square search unit on restaurants & bars. New?

[Jakob Wikström @Jakob_Wikstrom]

https://t.co/RsxOnaq1xX

[Jakob Wikström @Jakob_Wikstrom]

❗Huge news❗

Apple is relaunching "Apple Business Connect" to easier update business profiles in their Map and Search Engines. ❗🍏 Wonderful news.

What's your take on this?

#AppleBusinessProfile #GoogleProfile #localsearch #serchengine

[Joy Hawkins @JoyanneHawkins]

I'm seeing little zoomed-in maps in the local pack on the left-hand side where photos usually are.

[Jakob Wikström @Jakob_Wikstrom]

@JoyanneHawkins 😂

[Miriam Ellis @Miriam_Ellis_]

Big local Q4 at @Moz today, featuring @brightlocal @streetfightmag @GuideTwit @b4k_khushal @mblumenthal @carriehill @davidmihm @joyannehawkins @bubblesup @colannielsen @rustybrick @stefansomborac @technacity @darrenshaw_ @gsterling @cbrodzky & @MeetSOCi https://t.co/qKufNkYE6J

[Jakob Wikström @Jakob_Wikstrom]

@ClaudiaTomina @mblumenthal @JoyanneHawkins That's interesting..👀

[Mobal @Mobal_io]

Our CEO @Jakob_Wikstrom sat down with @KaganJ from @marketecturetv to talk about the importance of business listings and how Mobal is helping businesses succeed online.

Listen to the full episode here: https://t.co/ecr7uqOVWm