There will always be something impressive left to do
As AI improves, what counts as impressive will change—but there will always be something impressive left for humans to do.
Everything else
Tutorials, news reactions, tool notes, personal miscellany, and observations outside the main topics.
The low-value work left for humans
AI can do the entire job, except the low-value data shuffling.
How to install a Claude Code skill from GitHub
Install a Claude Code skill from GitHub as a standalone skill or through a plugin marketplace, with current Desktop and CLI steps.
My agent use cases, part 2
In part 1 I covered the straightforward agent use cases: copyediting, onboarding, expense reports, Jira management. Those are about doing existing tasks faster. The five below are different. They share a thread: the agent isn't replacing someone's work, it's gathering context I wouldn't have gathered on my own, so I can think
My agent use cases, part 1
While we're in this mode of rapidly developing agent capabilities, I want to do my part in diffusing knowledge of what agents can do. Since Claude Code IS the software, I am using it more and more for everyday office work, and rapidly discovering new things that agents can (or cannot) do. My daily driver with those is
Possible
People sometimes use the word "impossible" too lightly. When I consider whether something is possible, I consider two angles first: 1. Is it logically provably impossible? 2. Is it against the laws of physics? It's rarely either, at least in my line of work. Putting a problem in these terms makes that clear, which is encouraging.
Agent skill - Statistics Estonia
Today I published my first agent skill: using Statistics Estonia databases. Often I have some simple question and I know data exists, but I can't be bothered to figure out the clunky UIs and directory trees and subtle variants of tables. This is now automated for me. It's built for Claude Code, but it works with
AI Ranch podcast with Evalds Urtans
Mostly talking about AI, Pactum and selling to enterprises. It was recorded at the end of August, so some things are already likely stale! Find the podcast on Youtube or your favourite podcast app. Excerpts: I’m not very surprised or disappointed by GPT-5, and that’s because the trajectory is actually quite straightforward. The scaling laws tell us
My deep research use cases
Deep research is underappreciated. The feature exists in all three LLM chat apps I pay for (ChatGPT, Claude and Gemini) and is unfortunately heavily rate limited, which makes sense given the likely token cost. But the massive amount of tokens burnt on reading and analyzing hundreds of articles is the reason it can have such a big impact on some
Gemini 2.5 Pro isn't quite Claude 3.7 at coding
Gemini 2.5 Pro was just released and it could be a big deal, if its coding abilities pan out. The current positioning of Gemini has been roughly that it is a tad behind the OpenAI/Anthropic models of the same class, and far behind the coding capabilities of Claude 3.7 Sonnet which is considered unmatched for practical engineering