Some carriers offer blocking all unknown calls from specified area codes. On Verizon that is "Neighborhood Filter", part of their "Call Filter" toolkit:
The way it's meant to be used is that the subscriber would block their own area code, and perhaps co-located overlays or neighbouring area codes. The limit for now is ten area codes.
Known or explicitly approved numbers are passed through.
The additional hack is that it's possible to request a number in any arbitrary area code, and spam and robocall rates vary tremendously across area codes. They're generally worst across the Deep South / Southeast (TX, OK, AR, AL, MS, TN, GA, SC, NC), and lowest in Alaska, Utah, Massachussetts, Washington, and North Dakota.
Pick a low-spam, low-population state, request a number from one of its area codes (if not its one area code ;-), and then block all but known numbers from that area code.
Ha, for a brief moment I thought VM=virtual machine and not voice mail and was scratching my head how you set that up and what the VM is doing with the call
I love and hate this feature. I use it all the time with Claude, and find it super useful. At the same time I wish it didn’t exist so I was unable to continue to do work away from my computer. Kinda like the days before mobile phone and when you left the office work mostly ended.
I think they are releasing the native app so they can have the omni-present ask bar that some people I assume like. Also I assume their CLI will be eventually integrated into this app.
As a builder/developer, marketing often isn't considered "fun". But you need to do it, else the build was for your personal entertainment/learning exp (which is sometimes a good thing).
What I do is stop building and focus 100% on marketing - well, 90% because I can't help myself. Even if this isn't as "fun", you need to switch modes and stop building.
As for my approach, I start with Google Ads + SEO/AEO. Google ads can get results in a few weeks (Google does have a learning phase) and SEO and AEO is a much longer process, which can be months before you see results. I use AHREF to check my SEO/AEO progress. While AHREF isn't a direct measurement of Google, I've found their DR to be correlated with my organic traffic.
The 90% is relatable, I physically cannot stop building even when I know I should be doing something else. The mode switching is the hardest part, not the marketing itself.
Good reminder that ads can show results fast while SEO compounds slowly, running both makes sense.
> “ The model, code-named Avocado, outperformed Meta’s previous A.I. model and did better than Google’s Gemini 2.5 model from March, two of the people said. But it has not performed as strongly as Gemini 3.0 from November, they said.”
So in two months they will make it better than 3.1? But by then there will probably be even newer models. It would be great if we get another competing model, but it isn’t going to be easy for Meta.
I remember everyone wondering how they got faster inference speeds, and everyone was so focused on the memory throughput, but after simmering on it for a bit, I am left wondering if the SSD speed plays a part in that speed up they noticed. Then again could also be the specific model as well.
- "The agent mapped the attack surface and found the API documentation publicly exposed — over 200 endpoints, fully documented. Most required authentication. Twenty-two didn't."
I’m tired of every AI capability at SaaS companies charging usage fees. I get it: they both have their own token costs and want to make a profit on the feature. But it makes a $50 a month product potentially hundreds if I’m not careful. For example our customer chat tool with AI on is going to be hundreds a month instead of the $39/mo we pay. We turned off the AI capability.
> I’m tired of every AI capability at SaaS companies charging usage fees. I get it: they both have their own token costs and want to make a profit on the feature. But it makes a $50 a month product potentially hundreds if I’m not careful.
Well, I understand how, as a user, yoou’d prefer your $50 subscription to include hundreds of dollars of subsidies for the costs of consuming third-party AI resources, but other than a startup spending VC to buy a userbase and force the traditional unsubsidized competition out of business before milking their new monopoly hard to payback investors, how do you expect a firm to justify that?
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