Today, I asked a simple question to Microsoft Copilot in Excel:

Copilot then reasoned for 42 seconds and then proclaimed:

Only, nothing changed in the Excel sheet.

So, I replied:

It got me, it thought:

After some thinking, it came up with a brilliant solution:

I thought: let’s make it easy for it:

Reply:

Only, everything was empty.

Hallucinations, anyone?

Option A! It “reasoned” (I have to use scary quotes now) for 5 seconds and then:

I’m starting to get annoyed, because there’s no summary in the file:

It starts to understand me, now.

So, of course I reuploaded the file and then Copilot “reasoned” again for 9 seconds

All these emojis make me helpful! But there’s still no Summary in the sheet

At this point, the model was puzzled, and it reasoned again for 11 seconds.

No shit I’m right. Anyway, the Excel still didn’t have the Summary tab. I uploaded it to Claude and it got it right the first time.

What a horrible experience.

Icing on the Cake

OK, let’s share the prompt then! Let’s click on the 3 small dots at the end of the conversation:

A dialog opens up

OK, then link has been created and copied! Only, nothing has been copied.

No worries, there’s a Manage Access button:

🤦🏻

🐹 Deep clean and optimize your Mac.

I just stumbled upon Mole, a utility to clean and optimize Macs. What stood out to me is fact that it packs a bunch of GUI utilities (DaisyDisk, iStat, etc.) into a neat TUI.

The developer has received quite some scrutiny being Chinese but that didn’t stop a thriving community (+30 contributors) and user base (+28k ⭐️, +80 👀) to start using it.

Its core features are:

• 🪥 Deep Cleaning, removing logs, caches, and browser leftovers
• 📲 Smart Uninstaller, including launch agents, preferences, and hidden scraps
• 🔎 Disk Insights, visualizing usage and allowing managing large files
• 📊 Live Monitoring, for CPU, GPU, memory, dis, and network

While designed for macOS, there’s a Windows branch in the making.

 __  __       _
|  \/  | ___ | | ___
| |\/| |/ _ \| |/ _ \
| |  | | (_) | |  __/  https://github.com/tw93/mole
|_|  |_|\___/|_|\___|  Deep clean and optimize your Mac.

➤ 1. Clean        Free up disk space
  2. Uninstall    Remove apps completely
  3. Optimize     Check and maintain system
  4. Analyze      Explore disk usage
  5. Status       Monitor system health

↑↓  |  Enter  |  M More  |  U Update  |  Q Quit

Patient-First: the Future of AI in Healthcare

It’s been millennia since humankind realized that, if you follow the advice of medicine, you can live a better and longer life (that, and avoiding carbs, apparently). The craft has been perfected ever since, and each major technological advancement has contributed to furthering this craft. 

Good opening!

The AWS GenAI summit was not about agentic systems, but targeted tools solving actual problems:

• Either creating silent, scalable efficiencies within healthcare systems, or

• Designing human-centric solutions, enhancing diagnostic.

The future of AI in healthcare is then about leveraging human-out-of-the-loop AI for backend gains while creating human-in-the-loop systems, empowering professionals to do more and reach more people. 

To achieve this, specialized models are key to earning trust and making an impact to, ultimately, put the patient where they belong: at the center.

We still see few specialized models out there, but they truly are key for speed and cost (and privacy, it you’re going to self-host).

I recently started using Marked 2 again with some of my markdown files.

The app works great and it can strip YAML from the front matter of the files.

However, I recently started another blog with TOML front matter, and Marked didn’t handle those.

Luckily, it has a preference where you can set a custom preprocessor for your files:

I fired up Claude and whipped up the tiniest utility to do just that.

If you want to use it, it’s pretty easy to compile following the README.md or by heading to the releases page.

AI Zealotry

This post is so great, I want to frame it

If you’re an engineer opposed to AI coding—or if you haven’t started yet—read it.

I feel both that I can move faster and operate in areas that were previously inaccessible to me (like frontend). Experienced developers should all be doing this. We’re good enough to avoid AI Slop, and there’s so much we can accomplish today.

I like this quote from this blog

I get it, you’re too good to vibe code. You’re a senior developer who has been doing this for 20 years and knows the system like the back of your hand.

[…]

No, you’re not too good to vibe code. In fact, you’re the only person who should be vibe coding.

The folks at Astral have released ty, which they define as:

An extremely fast Python type checker and language server, written in Rust.

You can read more in the blog post announcing it.

Today, I set it up with helix. To make it work, we first have to install it. Using uv, it’s as easy as typing:

uv tool install ty@latest

Then, edit your ~/.config/helix/languages.toml and add the following:

[language-server.ty]
command = "ty"
args = ["server"]

[[language]]
name = "python"
scope = "source.python"
injection-regex = "python"
file-types = ["py","pyi","py3","pyw",".pythonstartup",".pythonrc"]
shebangs = ["python"]
roots = [".", "pyproject.toml"]
comment-token = "#"
language-servers = ["ty"]
indent = { tab-width = 4, unit = "    " }
auto-format = true

At this point, you can start using it, but there are a few handy things to know:

• By default, ty will search for first-party modules in the project’s root directory or the src directory, if present.
• If they are located elsewhere, you need to update your pyproject.toml like so:

[tool.ty.environment]
root = ["./app"]

• Third-party modules are searched for within a virtual environment, determined by:
  1. An environment variable called VIRTUAL_ENV.
  2. A .venv directory in the project root or working directory.
  3. The --python or --venv flag when invoking it.
  4. A configuration in pyproject.toml:

[tool.ty.environment]
python = "./custom-venv-location/.venv"

That’s it. Now, when editing files with hx, you should get all of ty’s goodness!

Since posting about how I use llm to check my grammar, Dr. Drang took inspiration from my setup and wrote about how he implemented a system that shows differences side-by-side, instead of highlighting them as I do. On top of that, his system includes a short rationale for the changes.

I have always liked the idea of a diff-based check, but because I write in Mailmate, helix, and the browser, I couldn’t come up with a system that worked everywhere.

That was until I remembered about Meld, a diffing app.

Before starting, it’s important to have Meld installed and available at the command line (to do so, install it via brew install meld and follow these instructions).

Once that is done (and you have llm installed—see my previous post), I use this macro that I invoke after copying the text:

The script does all the heavy lifting and is self-explanatory:

#!/opt/homebrew/bin/fish

pbpaste > /tmp/original.md
pbpaste | llm -m gemini-3-flash-preview -s "
Given the following text, improve grammar and punctuations. Note that there might be markdown syntax that needs to be preserved

Output the text and add commentary only at the end, after a clear break line (use dashes)" > /tmp/corrected.md
cat /tmp/corrected.md | pbcopy
meld /tmp/original.md /tmp/corrected.md

Once invoked, Meld opens, allowing me to review the changes and copy the text back:

If you write long lines of text without hard wraps, don’t forget to check the Enable text wrapping box in the preferences pane!

Netnewswire is moving to Discourse

We’re moving from Slack to here. This way we can use an open source app that’s part of the open web — and we can have conversations that don’t get deleted, that are findable, that people can benefit from long after the conversation actually happened.

👏🏼 I would love if more communities were to move to Discourse.

We briefly had it for the GoDataDriven Academy, but it never took off with students. I guess they were not so idealistic?

Just before Christmas, I got an email from Bitbucket saying that inactive workspaces will be deleted.

Almost 20 years ago, I created a Bitbucket workspace to host my university stuff (mostly for my research thesis and various papers).

And while I have the final PDFs, I did not want all that LaTeX to go to waste, so I decided to migrate everything to GitHub (which, since 20 years ago, added private repositories to their free offering).

Creating these scripts is a use case where LLMs really shine—although I had to doctor it a bit, as the way it concocted to create repositories on GitHub didn’t work.

The final script is in this gist, and to use it you need the GitHub CLI utility gh installed (see the instructions if you don’t have it) and ready to go.

Once that is done, it’s a matter of writing the names of your repositories in a file called, f.e., repos.txt and then calling the script:

BB_WORKSPACE=your_bitbucket_workspace \
GH_OWNER=your_github_username \
./migrate-bitbucket.sh repos.txt

After a while, depending on the number of repositories, you should see

🎉 All migrations complete.

Notes:

• Repositories are created private by default.
• The script assumes repositories with clashing names do not exist on GitHub.
• You need to have access to Bitbucket and GitHub through SSH.

When starting this blog, I didn’t think about adding tags. As time passed, I wondered about adding them, but back-filling them was a chore.

But with LLMs, this can be done relatively quickly and easily:

• Pass the LLM some text, and it will happily tell you which tags you might use.
• And, while you’re at it, it can create the script to call the LLM on all the posts and the code to visualize tags (which were previously hidden).

So I did just that! In a 10-minute session, Copilot created the add_tags.py script, which you can find in this gist!

There are two commits where the tags were added: one for the theme and the other for adding the actual tags to the posts.