Speaking as a Brit, our national trait is generally too understate things. So even saying what you mean, directly, comes off as a bit immodest and hyping it up in sales pitches sounds shady.
Americans generally say what they mean a bit more, so I think their mid point is just different.
There was a quote somewhere about Mercurial having a mental model small enough you can fit in your head - and that was the big win for me.
It was also fast and had very clean, easy to contribute to code. I remember submitting a patch and getting a bit of Python education from Matt, which was very useful.
Git is fine but it's inconsistent enough in the interface department, even after all this time, that I still get regularly frustrated. On the other hand, you can't just break a workflow that already exists and I very much appreciate it scales to work far beyond mine.
I do like that the git people are doing the difficult work of improving the UI over time - it's hard to change the engines while the plane is flying!
I've recently been thinking how AI agents could affect this.
If you're lucky enough to be able to code significant amounts with a modern agent (someone's paying, your task is amenable to it, etc) then you may experience development shifting (further) from "type in the code" to "express the concepts". Maybe you still write some code - but not as much.
What does this look like for debugging / understanding? There's a potential outcome of "AI just solves all the bugs" but I think it's reasonable to imagine that AI will be a (preferably helpful!) partner to a human developer who needs to debug.
My best guess is:
* The entities you manage are "investigations" (mapping onto agents)
* You interact primarily through some kind of rich chat (includes sensibly formatted code, data, etc)
* The primary artefact(s) of this workflow are not code but something more like "clues" / "evidence".
Managing all the theories and snippets of evidence is already core to debugging the old fashioned way. I think having agents in the loop gives us an opportunity to make that explicit part of the process (and then be able to assign agents to follow up gaps in the evidence, or investigate them yourself or get someone else to...).
Very excited to see this come out - though coding agents are impressive their UIs are a bit of a mixed bag.
Textual offers incredibly impressive terminal experiences so I'm very much looking forward to this.
I wonder how much agentic magic it'll be able to include though - Claude Code often seems like a lot of its intelligence comes from the scaffolding, not just the LLM. I'm excited to see!
I love the Patagonian Welsh. BBC Wales, which often has great comedy, has a sitcom based around the original emigration to Patagonia: https://www.bbc.co.uk/programmes/b060cd20
The whole thing feels very much like a Star Trek plot to me with a culture leaving on a ship to an unknown world to preserve their way of life - which later the crew would happen upon in some episode.
In Cambridge we've got a clock called the Chronophage which is intended to be a sinister "eater of time" - the designer has done a good job of making it feel uncomfortable to look at. There's some detail here: https://www.corpus.cam.ac.uk/articles/secrets-corpus-clock
My memories of what I've heard over time:
* The grasshopper escapement actually is the demonic insect that sits on the top, "walking" around the serrated ring.
* Although it's backlit electronically it's actually a fully mechanical design - including all of the weird things it does.
* The Chronophage itself blinks its eyes unnervingly.
* It sometimes pauses or ticks slightly backwards, then runs faster to catch up again.
* On certain special dates it does extra weird stuff.
* The "chime" is a metal chain dropping into a box.
There were three made in the series, this was the first one. I've always found it slightly unappealing aesthetically but also compelling - there's no arguing with the fact that there's always a crowd of fascinated observers looking at it.
Amp (ampcode.com) uses Sonnet as its main model and has GPT o3 as a special purpose tool / subagent. It can call into that when it needs particularly advanced reasoning.
Interestingly I found that prompting it to ask the o3 submodel (which they call The Oracle) to check Sonnet's working on a debugging solution was helpful. Extra interesting to me was the fact that Sonnet appeared to do a better job once I'd prompted that (like chain of thought prompting, perhaps asking it to put forward an explanation to be checked actually triggered more effective thinking).
I think the key thing with OSM is that the data is open.
It would be nice if this app had more open code and it's nice if people contribute back to the data set too.
But the database is the open source artifact here, not the software - as long as they're respecting that then it feels ok, even if more would be desirable.
Americans generally say what they mean a bit more, so I think their mid point is just different.