I don't know if I love this more for the sheer usefulness, or for the delightful over-the-top "Proper English Butler" diction.
But what really has my attention is: Why is this something I'm reading about on this smart engineer's blog rather than an Apple or Google product release? The fact that even this small set of features is beyond the abilities of either of those two companies to ship -- even with caveats like "Must also use our walled garden ecosystem for email, calendars, phones, etc" -- is an embarrassment, only obscured by the two companies' shared lack of ambition to apply "AI" technology to the 'solved problem' areas that amount to various kinds of summarization and question-answering.
If ever there was a chance to threaten either half of this lumbering, anticompetitive duopoly, certainly it's related to AI.
There’s actually a good answer to this, namely that narrowly targeting the needs of exactly one family allows you to develop software about 1000x faster. This is an argument in favor of personal software.
The Apple walled garden argues against you here. There are at least 20 million families in America where this holds true:
• Everyone in household uses an iPhone
• Main adult family members use iCloud Mail or at least use Apple Mail to read other mail
• Family members use iCloud contacts and calendars
• USPS Informed Delivery could be used (available to most/all US addresses)
• It can be ascertained what ZIP code you're in, for weather.
I think that's the full list of 'requirements' this thing would require. Just what's standing in their way?
Not every one of those families would find the same set of features helpful, so you have to make calls about what's worth developing and what isn't. Making those calls is very difficult because it's tricky to gather data about what will be used and appreciated.
Well, it's a good thing we've settled on... genmoji. Yeah.
> it's tricky to gather data about what will be used and appreciated
I'm not sure it's so tricky for Apple, and for sure not for Google.
And whatever they are doing is clearly working well. /s
The thing that is standing in their way is probably that nobody is willing to pay for this what it costs to run.
Doesn't look very expensive to me. An LLM capable of this level of summarization can run in ~12GB of GPU-connected RAM, and only needs that while it's running a prompt.
The cheapest small LLMs (GPT-4.1 Nano, Google Gemini 1.5 Flash 8B) cost less than 1/100th of a cent per prompt because they are cheap to run.
Yes! And also, Apple loves selling expensive hardware and has zero shyness asking people to pay a few thousand bucks to buy into part of their ecosystem.
They could easily offer an on-prem family 'AI' product that you plop in your house and plug into your router, and does all AI processing for the whole family, and uses a secure VPN to connect to any of your devices outside the LAN.
If such a product delivered JUST what this guy's cool hack provides, and made Siri not a stupid piece of sh*t for my family, I'd buy it for $1999 even if I knew it cost Apple $700 to make.
Isn’t that how good product development should look like for Apple/Gooogle though?
Find something useful for one family, see if more families find it useful as well. If so, scale to platform level.
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yes which vibe coding enables.
True, I always thought something like Hypercard was needed to bring personal programming to the masses, but it appears that it might require LLM coding instead. ("I wish an app that did simple task XYZ existed."; "Can you ask ChatGPT to make that for you?")
This is literally in the first chapter of Mythical Man-Month:
> One occasionally reads newspaper accounts of how two programmers in a remodeled garage have built an important program that surpasses the best efforts of large teams. And every programmer is prepared to believe such tales, for he knows that he could build any program much faster than the 1000 statements/year reported for industrial teams.
> Why then have not all industrial programming teams been replaced by dedicated garage duos? One must look at what is being produced.
One reason might be that personal data going into a database handled by a highly experimental software might be a non-issue for this dev, but it is a serious risk for Google, Apple, etc.
The reason Google and Apple stopped innovating is simply because they make too much money from their current products and see every innovation primarily as a risk to their existing business. This is something that happens all the time to market leaders.
Take a look at Home Assistant - I would argue their implementation is currently better than both Siri & Gemini assistants.
HA team is releasing actually useful updates every month - eg ability for assistant to proactively ask you something.
In my opinion both Google & Apple have huge issues with cooperation between product teams, while cooperation with external companies is next to impossible.
Because how would you monetize this? Because would google or apple make a product that talks to telegram? Or anything with an open ecosystem?
All the big guys are trying to do is suck the eggs out of their geese faster.
As some of the other commenters have directly and indirectly pointed out, I believe this is the crux of the AI Agent problem. Each user has a customized workflow they’re trying to achieve. This doesn’t lend well to a “product” or “SaaS”. It leads to thousands of bespoke implementations.
I’m not sure how you get over this hurdle. My email agent is inevitably different than everyone else’s email agent.
It’s because this story hints at the concept of “Unmetered AI”. It can be easily hosted locally and run with a self-hosted LLM.
Wonder if Edison mentioned Nikola Tesla much in his writings?