Unrelated to this (and sorry for highjacking this topic), but just want to say a big big thank you to ladyada for founding Adafruit.

When we decided to go fully open source hardware at AirGradient, I looked at the ‘business’ models of two companies: Adafruit and Arduino.

Seeing that both worked sustainably, made our decision much easier and it was probably one of the best decisions of our life. I just talked at the Open Hardware summit in Berlin about “50 devices later: The open source hardware advantage” [1].

[1] https://2026.oshwa.org/talks/100-achim-haug/

Is it only me or are you guys also being disappointed when a very interesting article is heavily AI written?

I feel like not wanting to read it in depth, even though the topic is unique and something I like to learn more.

It’s a shame because there was probably quite some work that went into it: coming up with the topic, doing the research, polish it up etc.

I have also been using AI a lot for article writing but the last two posts I wrote I went back into handwriting. They are much less “perfect”, but they are me and 100% what I want to say and convey.

Even the imperfections matter.

Maybe like a piece of handmade furniture vs something from IKEA.

It’s actually a nice article if it wouldn’t be so obviously AI written.

In my opinion this really devalues the reputation I am having for a publication and is a pity especially in this particular case as home assistant is such a great community.

I guess for a lot of the Show HN posts, people could accuse of being Ads.

This was an honest account of my experience coding this. If you do a bit of research on our company, you might come to a different judgement. But obviously everybody is free to have their own opinions.

Mostly codex, and initially claude. I'm planning a follow up post on more details of our process.

Different strategies.

- sometimes when it’s lost, just roll back. Commit very often. Sometimes it’s getting lost on simple and easy features - very unexpectedly.

- prompt regularly to review the architecture and clean up the code, check for specific things like code repetitions, error handling etc.

- keep an eye on the code yourself. At least on the general architectural side, and review complex code areas by hand

- ask always for larger features to make a plan first. Review the plan carefully. Only when the plan is ok, ask it to start coding.

I actually think this could be the completely wrong approach.

By focusing on only one persona, you might focus on one that for reasons NOT covered in this questionnaire does not work out.

Practical example from us at AirGradient. Initially, we had a strong focus on selling air quality monitoring to schools.

Our strategy would have ticked all boxes in this article but selling to schools turned out to be extremely difficult. In our case, the problem was that decision makers are often not the people benefiting from the solution. Another reason for that persona being very difficult was that air quality is not a core competency of a school.

So I actually think that you should have a relatively broad approach because often the customer that you will be successful with you actually might not know when you start.

100% agree. It is super important to know the composition of the particles.

Unfortunately currently only super expensive instruments can measure this in real-time.

This is why I believe contextual information will become much more important in future.

Detect an indoor short PM2.5 spike around lunch time, probably a cooking event.

Detect medium elevated levels outdoor in a city in the morning and late afternoons, probably traffic related smoke.

I actually made a small tool to simulate different events that contain a quiz. Give it a try here [1].

[1] https://www.airgradient.com/air-quality-monitoring-toolkit/p...

The quiz hides the chart. Makes it hard to answer

Achim from AirGradient here. Great to see this posted.

When we first heard about this new sensor, we were quite pessimistic about its performance but have been pleasantly surprised by its performance. It is something we consider now for potential future products.

We are also currently testing the energy consumption because we believe the fanless design should make it quite efficient; but not sure how much the laser needs. So we will keep the article updated as learn more.

With a powerful enough laser, the sensor could also improve air quality.

You can use an air purifier. The Hepa filters are effective in eliminating PM. Gases like NO2 and VOCs can be reduced with carbon filters. Make sure that your carbon filter is large and different get saturated too quickly.