Some of you might have noticed that the recent (or rather: previous) version of libayatana-appindicator (v0.5.94) notified users and developers of the library being deprecated.
This short post is to notify you, that with today's libayatana-appindicator v0.6.0 release [1] this deprecation warning has now been removed again. Another new feature (added to AppIndicator without ABI breakage) is tooltip support. The new package version has just been uploaded to Debian experimental. Please test if your application (if it gets linked against libayatana-appindicator) continues to work flawlessly. Thanks!
libayatana-appindicator will receive continued support until GTK-3 becomes end-of-life (because libayatana-appindicator has a baked-in GTK-3 dependency which should not be ported to GTK-4 imho). That said, in the future, GTK-3 applications can continue using libayatana-appindicator for sending AppIndicator-like icons and menus over DBus to KStatusNotifierItem-based system tray renderers.
If you are looking for an AppIndicator implementation for GTK-4 applications (or other), I'd like to encourage you to help making libayatana-appindicator-glib [2] a new standard (can be used in GTK and Qt applications alike, implementation is using pure Glib-2.0). Currently, there is only one renderer (ayatana-indicator-application), so more work needs to be done on the renderers' side. (One of the next work items here is to get AppIndicator-Glib support working in Lomiri's desktop/windowed mode).
I backported various security fixes from 10.3 to trixie, bookworm, bullseye, buster, and stretch. For trixie, I also backported several IPQoS fixes to line up with upstream’s traffic management settings and drop a rather hacky Debian-specific patch; this needed a quick follow-up fix.
AI slop is invading the web. A recent story about disallowing LLM-generated
submissions on Lobsters triggered a lot of debate. My personal worst
offenders are LinkedIn articles with AI-generated images and uninspired
articles filled with emojis from people trying to masquerade as experts on a
subject they don’t care enough to write themselves. While I am unhappy about
this situation, I rely on LLMs for grammar, copyediting, and
translation. I don’t see this as a contradiction.
I am a native French speaker, but I blog in both English and French. When I
started writing this blog in 2011, I was composing in French and translating
to English, but I found it was better to work in the reverse order to
avoid unnatural and non-idiomatic constructions. One of my goals is to write
“good” English but I never felt it was my strong point.1 For example, verb
tenses are often an issue, even if I mostly stick with the present tense. I
learn the rules and forget them right away. I also don’t feel like hiring an
editor for something I see as a hobby.
I know that LLMs may alter the author’s voice when editing, but the
corrections in the second step are minor. The prompt asks to “apply light
stylistic edits,” with some guidance around avoiding passive voice, long
sentences, bland verbs, and filler words. It also defines the target audience:
technical with a B2 level in English.
In the following excerpt, I used “long time” instead of “long-standing.” The
former is missing a hyphen and applies to people—a long-time friend, while
the later relates to a situation—a long-standing agreement. I had a hard
time understanding the reason of the second change: the LLM prefers a
defining relative clause to provide the definition of “RIB sharding.”
As the Internet routing table contains more than 1 million routes, Akvorado
needs to scale to tens of millions of routes. This has been a long
time long-standing challenge, but I expect this issue is now
fixed by using RIB sharding, a method to split that
splits the routing database into several parts to enable concurrent
updates.
In the next modification, the LLM puts “device” instead of “equipment.” This is
correct as “equipment” is an uncountable noun. I know that, but I still fall
into this trap.
When Akvorado does not find a route from a specific device, it falls back to a
route sent by another equipment device.
I ask the LLM to use “descriptive verbs” and it complies by replacing a
multi-word predicate with a lexically rich verb:
The benchmarks demonstrate it has better performance than
outperforms other packages, both packages for
lookups, insertions, and memory usage.
It also fixes grammar errors. In the next excerpt, a “list of routes” is a
singular expression. Moreover, “stored” is a state and I should not use “into”
as it expresses a change.
The list of routes for each prefix are is not stored
directly into in the prefix tree.
As a last example, consider the following snippet. The “require” verb
accepts a noun or an object followed by a to-infinitive. I can’t use it with
just a to-infinitive.
An alternative would be to have one prefix tree for each peer but it would
require to configure configuring all routers to export
their routes.
As someone who didn’t grow up speaking English, I struggle with these grammar
rules despite reading a lot of English material.3 French is more
complex to get started but more systematic. English is full of irregularities.
On each page, I disclose in the footer whether an AI modified the content. There
are three levels:
🧠: no AI or almost no AI (e.g., grammar corrections)
✨: enhanced (e.g., copyediting)
🤖: generated (e.g., translated from another language, even if human-edited)
Hover or tap the icon to reveal the AI’s name and its role in the document.
Example of AI usage disclosure: Claude Sonnet 4.5 edited this article.
The graph below shows which tool altered each post, year by year. Recently, I
applied the grammar skill to past articles. Since 2018,
French articles have been translated with the help of DeepL first, then of
an LLM. Since 2024, English articles are copyedited.
🖼 Graph showing the AI usage over the years. Each level get its own
color.
AI usage over the years. Hover or tap a band for the details.
If you are strongly against any usage of LLMs specifically for writing, I hope
you accept my more nuanced position on the usage of these tools as a trade-off
to provide clearer and more engaging articles. Years of literature on improving
English told us it is important to choose the right word to keep the reader
engaged.
[…] Good writing consists of mastering the fundamentals (vocabulary,
grammar, the elements of style) and then filling the third level of your
toolbox with the right instruments.
― Stephen King, On Writing
Note
Unlike other recent articles, I did not use an LLM to edit this post:
an unnamed person kindly accepted to proofread it. I translated it to French
without using an LLM either.
I am quite happy with the writing tools provided by Kagi. Both the
translate tool and the dictionary are a valuable help to find
different wordings. I also lean on Kagi’s research assistant when
researching a topic. ↩
When I was ten, I played Monkey Island 2 in English without having
taken any classes. I used a dictionary to translate word by word and I found
the irregular verbs confusing—and not in the dictionary. ↩
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