Last night I re-watched Tron from 1982. And just now I glanced at Claude's thinking where it reasoned about what "the user" wants, that is me. This struck me as very similar to how the "programs" in Tron talk about the mythical "users", which they are not even sure exists and whose wishes need to be guessed. Very prescient of the film-makers!
Claude Opus 4.5 is really good as coding agent, and I'm having a blast with it.
It's even more fun in "YOLO-mode", a.k.a. --dangerously-skip-permissions.
This way one does not need to approve anything; Claude gets to do whatever it
sees fit to get the job done. This enables longer tasks because it can do trial and error
on its own, and also requires less attention from us users.
Is it safe though? When will Claude mess up and delete important data? After all, unrestricted access to the command line is as powerful a tool as they come. I have no good answer here, so I recently looked into various ways to prevent the agent from doing damage. As far as I know, these are the common approaches:
uv self update resolved it.
Still annoying.docker sandbox run claude. Ultimately though, I don't like the friction this introduces.
Suddenly one has to maintain the Dockerfile and what to install there, mounting directories or copy
data back and forth, etc.For now, I take the risk and run yolo-Claude on my laptop without a container or separate user. All code is under version control and pushed to remote. And I make sure to have frequent backups, just in case.
What I dont't do however, is run Claude with root-access on a remote server. It would most likely be fine for a while, until it would not. Claude makes a great sysadmin sidekick though: earlier today, the maintenance interface (iDRAC) of one of our servers hung itself and in this session Claude showed showed me how to reset it remotely, which I did not know before was possible.
Our small farm has some forest attached, and we have a tractor from the 80s with an old winch/crane to get logs out. Earlier this year, I cleaned out an old barn and put in a Woodmizer sawmill. Autumn and winter are the right time for forest work, so I took most of yesterday to do just that.
I had felled a tree that was killed by bark beetles last summer, meaning that it has had time to dry while standing already and the lunber can be used right away. I managed to pull out a double length (~9.5m) log to the saw, just 200m away, and cut it in two there.
Then I rolled in onto the saw which turned it into 2-by-8s (50x200mm). Below are a few pictures of the process, click to enlarge. And if you happen to be local to the Östhammar region, we're open for business: info (in Swedish) at https://www.bestbo.se/sag/.
Only a month ago I made my own vibe-coded hack to convert Claude Code sessions to HTML. Now Simon Willison has one-upped the game: Simply run
uvx claude-code-transcripts
and enjoy! Here's an example of how I just asked Claude to tweak the CSS of this site.
A comment on HackerNews that made me smile:
Frameworks abide by the Hollywood Principle and the Greyhound Principle: Don't call us, we'll call you. Leave the driving to us.
It's true! When using a framework one's code gets called by the framework and it usually takes care of how things are run. This is from the discussion about Avoid Mini-Frameworks, an insightful article on unnecessary mid-level abstraction layers.
How uv got so fast has quite a few hallmarks of being (co-)written by AI, but I found it a good read nonetheless. I continue to be impressed by uv and now use nothing else for running Python.
Here's another example for the kind of task that I no longer do myself but rather hand off to the AI, because it does it so well. I asked like this:
Let's implement a new option --fib_eff that gets a single value or a range, like 0.9 or 0.7-0.9 , in order to set the fiber efficiencies in the simulation. see fiber_efficiency.md how to do that. set the eff after loading the HDF file, dont modify it. Ranges like 0.7-0.9 are to be interpreted as a random value within that range, uniformly distributed. ask if this was unclear, othweise get crackin and iterate. example command: uv run andes-sim flat-field --band H --subslit slitA --wl-min 1600 --wl-max 1602 --fib_eff 0.5-0.95
As expected, Claude had no problem figuring this out. This the resulting commit. The image above is the ouput of that example command.
I did not have to to type anything else than the prompt above. And in doing that, I needed to get clear for myself what I actually wanted, which is always a good thing to do first. The rest is just typing.
The whole project, a CLI to make simulated spectra, was "vibe-coded" this way, me caring little about the actual code that Claude produced, only taking the occasional glance at it. It is therefore probably not great for a long-term maintained code-base, but it already does what I need it to and I have no intention to take this much further.
She has not gotten a Nobel prize herself, local celebrity nanotech professor Maria Strømme. But she as been part of the Nobel prize presentations, so let's apply the moniker Nobel disease loosely. It means the
the embrace of strange or scientifically unsound ideas by some Nobel Prize winners, usually later in life.
What qualifies Strømme is that she recently did the classic crank thing and wrote about the mixture of consciousness and quantum woo. I just leave these links here, in case you are interested
Running a small farm implies a constant stream of things to fix. The image shows an example of when the fruit grinder (to the right) in our juicery broke down. The motor fried itself towards the end of the season and I was hesitant to make the investment of a new one for just two remaining days.
Thus, one of the old motors that one naturally accumulates had to drive it externally with a belt. At first I did not gut the old motor which made it melt a second time thanks to induction -- lesson learned. The receiving axle is not perpendicular to the floor, so I made the angle of the other one adjustable together with the belt tension, by using one of the most important tools of all, a ratchet strap.
I notice it in myself, and in the vibes on the interwebs: this dissonance between on the one hand loving how useful AI is for oneself, and at the same time being annoyed when others use it "on you", or force you to use a bad one.
The examples are aplenty. Slop bug reports, all the companies that try to use chatbots for support questions, and the general feeling that companies push AI a bit too hard down our throats.
But when used right and with taste, it can be fantastic. This is not a contradiction; both the good and the bad exist, and the gap between them will probably only get larger.
A good rule-of-thumb for oneself may be to not make anyone read or interact with AI slop against their will. That means having read and understood AI-generated things to a degree that one feels comfortable standing for it, before sharing. Alternatively being very clear about when this is not the case, so that everyone can choose they level of attention accordingly.
ChatGPT is a mere three years old by now -- it sure feels longer. By now, many seem to either have dismissed LLMs as useless (or evil) or have quickly taken them for granted. But I continue to be amazed and find I get more and more value from Claude et al.
What I probably like the most is that LLMs remove friction. What often slows us down is not the lack of ideas or things to do and try, but the sum of the small hurdles and hoops one has to jump though before getting anywhere.
Well, no more. Config problems with your web-app? Data needs to be converted to or from an obscure custom format? Need to understand why your code does not do what you think it should? Or understand someone else's code quickly? LLMs got you covered. It's like rubberducking but the duck talks back and can solve the entire problem for you!
Yes, they make mistakes and one may need to verify the results. But in may cases this is trivial, or not really necessary, for example when discussing different tools or solutions to a problem. Skimming through the alternatives quickly lets one choose a path forward that is very likely better than it would have been without asking the model.
This is an import aspect: having some taste and quick judgement helps a lot, in other words knowing what you want. If you really do, you probably are able to explain it well enough to an LLM and get it to execute for you. If not, then LLMs can help you too, but one needs to have enough clarity of mind to recognize this as a different mode of operation, where non-leading questions and iterations on the problem can improve one's thinking very much like a discussion with a collegue or expert would have done.
To quote TheZvi:
AI is the best tool ever invented for learning. AI is the best tool ever invented for not learning. You can choose which way you use AI. #1 is available but requires intention.
