I needed to start an application each time I unlocked my Mac. But there didn’t seem to be an obvious way to run something every unlock in macOS.

For example, I found that launchd has an on-wake event. Great! But that doesn’t quite work because it also fires on power nap, which is a kind of mini-wake-up in macOS terms. I didn’t want to run the app each time power nap happened, or actually even when a normal wake up happened. I only wanted it when I was actually sitting at and unlocking the machine.

It turns out that Hammerspoon, which I’ve used for a long time to automate various slightly esoteric things¹, has a module tucked away for this. hs.caffeinate.watcher had what I needed. I’ll include the code snippet in the lede, and add a bit more detail below.

function runOnUnlock(eventType)
    if (eventType == hs.caffeinate.watcher.screensDidUnlock) then
        -- Carry out your unlock event here, eg:
        hs.execute("/path/to/shell/script.sh", true)
    end
end

local lockWatcher = hs.caffeinate.watcher.new(runOnUnlock)
lockWatcher:start()

I have been writing support for SSH’s ProxyCommand into a product at work over the past month or so. I find protocols fascinating, particularly those as old as / with the pedigree of SSH.

ProxyCommand is an interesting corner in the set of (defacto) SSH standards. It is used to establish a secure connection to a destination host, where that destination host cannot be directly accessed by the local machine. It is mostly used when you want to tunnel through a bastion host. It specifies a command that your SSH client executes to create a proxied connection — hence the name — to the destination host through the bastion.

I’m writing about it because my experience over the last few months suggests that ProxyCommand can be slightly mind-bending. Certainly it took me a little while to wrap my head around what is going on.

So let’s take a look at how it works.

Gradually, then Suddenly: Upon the Threshold is a good piece to contrast with my previous link to a post that considered the evidence that LLMs may be plateauing

We know AI is a general purpose technology - it will have wide-ranging effects across many industries and areas of our lives. But it is also flawed and prone to errors in some tasks, while being very good at others. Combine this jagged frontier of LLM abilities with their widespread utility and the concept of capability thresholds and you start to see the development of LLMs very differently. It isn’t a steady curve but a series of thresholds that, when crossed, suddenly and irrevocably change aspects of our lives.

In Evidence that LLMs are reaching a point of diminishing returns - and what that might mean, Gary Marcus shows evidence that the widespread view which holds that AI capability is increasing exponentially may be ill-founded:

And here’s the thing – we all know that GPT-3 was vastly better than GPT-2. And we all know that GPT-4 (released thirteen months ago) was vastly better than GPT-3. But what has happened since?

I could be persuaded that on some measures there was a doubling of capabilities for some set of months in 2020-2023, but I don’t see that case at all for the last 13 months.

Instead, I see numerous signs that we have reached a period of diminishing returns.

For the opposing viewpoint, get a coffee (or perhaps several) and read the much longer Situational awareness.

A few quick-fire notes which might be of interest to others now, and myself in the future.

After I started to use it a year ago, I wasn’t sure how long I’d continue to use the Helix editor. And yet here I am writing this post in Helix, and still using it at work. It’s crashed four or five times — in a year — but has overall proven very stable and capable. I think it’s dev progress is a bit slower than I’d like, but really, I’m very happy with the editor. It starts instantly, LSP+tree-sitter still proves a winning combination, and the improvements that have arrived are solid.

One thing I’ve been searching for is a fast formatter for web languages, specifically the ones used in Hugo and Jekyll sites. Markdown, templated HTML and CSS in the main. Tools like Prettier tend to be noticably slow in kicking in to format if one isn’t willing to pay the price of a constantly running server. I’ve been using deno fmt for a while for Markdown, but it doesn’t do CSS or HTML. So now I’m trying dprint, which has inbuilt formatting for all three languages I wanted. It turns out that deno fmt actually uses some dprint formatters under-the-hood, specifically Markdown. I like finally having a CSS formatter, although since I moved to Tailwind this has been less important. (I still really like Tailwind).

In August 2023’s journal, I mentioned using ClickHouse in a PoC. That PoC became production recently, and we now have over 100TB of data stored in ClickHouse after our pre-production ramp up. We ingest more than a billion rows a day. Throughout our build out, ClickHouse has continued to impress me, coping with each bump in data volume smoothly. Querying has remained efficient. We may need to bump our hardware a bit as we start using it more in earnest, but the simple, vertically-scaled, replicated architecture we are using seems solid 🤞

We went for a walk in a small piece of woodland near Bristol today, Leigh Woods. I loved the shapes within the branches of this tree: