Ex-Googler, Perl hacker, graph theory junkie, Ducatisti, Hadoop wrangler, general generalist and data science geek. Formerly at Factual, Bitfuture, Fullscreen, and Duckly.
Currently running Forgetmenaut, the next generation of privacy and compliance automation.
I once did an application of Benford's Law to USDT transactions between crypto exchanges, which seemed to indicate some exchanges had mostly "organic" transactions and a handful of exchanges seemed to have heavy transaction volume of seemingly-random but not really random amounts, indicating some level of wash trading on those exchanges.
To be fair, the reason the CA laws are much more expansive on all uses of data is because companies have tried a number of arrangements to get around the definition of "sale". This was Sephora's defense back in the first CCPA case, that their data sharing relationship in exchange for targeted marketing services was not "selling" data:
I'll second this observation, as well as add that apart from AI slop most people around here associate the data center push with the sudden proliferation of Flock cameras at every major intersection and along every highway. Provo defeated a major data center project that was going into an empty industrial park, arguably the kind of place that would fit that sort of development. The actual cost-benefit calculation for most people is heavily weighted towards the negative and this should not continue to surprise people. The perceived downside with no upside is just going to get worse if the government gatekeeps the most useful models.
You're probably on to something with the value of disagreement. I think it's one reason why chatting with current models doesn't create the same stimulation as rubber-ducking used to bring. The models are typically too quick to agree and amplify what you think rather than truly break it down and push back.
And thanks for saying it should have worked, I agree. My chagrin has increased over the years as I have realized the magnitude of my ill-timing.
In 2017 LLMs weren't powerful enough to generate working code on their own, but my goal was to at least create a chatbot that could help you rubber-duck-debug your way to a solution. Unfortunately the tech wasn't quite strong enough for that, and not enough engineers even knew what rubber-duck-debugging was. RIP Duckly.
Trying to train an LLM on two 1080ti's on the StackOverflow corpus in my living room was a vibe though. Good times.
Well, CT and VT passed their own version of the California DROP system last week and there are 5 other states in play for the current 2026 legislative sessions. I think it will be a slow patchwork for more states to take similar action, but it is coming.
I will note that many "data brokers" will just honor non-California residents' requests as if they were California residents and subject to the CCPA, simply because they would rather remove a potentially litigious consumer from their databases. Given the relatively low potential revenue for a single consumer's data it just doesn't make sense to hold on to information for the kind of person who currently goes out of their way to make that kind of request.
At the same time, many data brokers do go out of their way to deny as many privacy requests as possible. Given that the CPPA/CalPrivacy is starting audits very soon I don't see this as a winning strategy for them in the long run.
I built a half-baked CRM that has a lot of custom fields and visuals for statistics that are relevant to my potential customers. I'm selling primarily to registered data brokers, so being able to pull up their self-published compliance stats (gleaned from their own privacy pages or public filings) and contextualize them in terms of the rest of the industry ("your deletion request volume has been in the 95th percentile year over year") has been extremely helpful when starting conversations. I also gamified it a bit by giving myself targets for cold outreach and gathering hard numbers on my cadence for outbound calls and emails per lead.
I also built this site for educating potential customers and other privacy professionals about the increasing tempo of CCPA enforcement actions driving compliance: https://ccpa.world/enforcement
I could have probably coded this from scratch quicker considering that it took me two weeks to remove all of the hallucinated imaginary enforcement actions against real companies and also the citations to non-existent California law that the models kept injecting into my enforcement summaries.
The real impact of this case is that it's the first time we've seen a serious data minimization case in the US. California's investigation showed that they will prosecute if legitimately collected data is repurposed and resold after the fact.
My wife used to think that I had terrible sleep apnea because I'd repeatedly quit breathing for a minute or two at a time and then gasp for air, but it turned out I was just dreaming about freediving for lobsters.
I don't think it is killing SaaS. I have definitely had to extend my sales cycle when a potential customer vibe-coded a quick fix for a pain point that might have triggered a sale a few weeks earlier, but eventually the benefit delivered by someone else caring about the software as their entire mission really wins out over a feature here and there.
If you are selling SaaS consider that a vibe-coding customer is validating your feature roadmap with their own time and sweat. It's actually a very positive signal because it demonstrates how badly that product is needed. If they could vibe code a "good enough" version of something to get themselves unstuck for a week, you should be able to iterate on those features and build something even better in short order, except deployed securely and professionally.
Everyone's going to talk about how cool their custom vibe-coded CRM is until they get stuck in a failed migration.
My friend Dave Taylor (programmer on Doom / Doom 2 / Quake / Abuse) was famous for marathon gaming sessions when he was at id. He told me it almost killed him after a session because he was driving and saw what he thought was a Quake rocket ammo box and he instinctively swerved the car at speed to "pick it up", but it was in fact a concrete pylon securing a guardrail by a drop-off. He narrowly swerved back into the road.
On a lighter note, I played far too much GTA: Vice City on PS2 in college, to the point that when driving in real life I forgot to check my side and back mirrors at stop signs, and instead realized I was squeezing my middle fingers on the steering wheel instead of turning my head to look.
I saw that post, neat stuff. We made an attempt to develop something similar 4 years ago and take it to YC, it simply wasn't good enough often enough because our training data (Stack Overflow posts) was garbage and models were weaker back then. I figured it would take about 5 years for it to really be useful given the technology trajectory, and here we are.
I'll note that we weren't trying to build "code auto-complete" but instead a automated "rubber duck debugger" which would function enough like another contextually-ignorant but intelligent programmer that you could explain your issues to and illuminate the solution yourself. But we did a poor job of cleaning the data and we found that English questions started returning Python code blocks, sometimes contextually relevant. It was neat. This GitHub/OpenAI project is neater.
I would be curious what the cost of developing and running this model is though.
If you can not only survive at Google but slack along well enough to get promoted once on "10% of your mental capacity" I'd stay right where you are. You aren't going to find a better place to earn money for equivalent effort and it sounds like you've already adapted to the ecosystem. Sounds like you need an interesting side project or just a meaningful hobby.
Don't go looking for the missing sense of fulfillment you have at work, either for Google or any other company. Crack some classic literature and take some long walks, figure out what you haven't been doing.
Currently running Forgetmenaut, the next generation of privacy and compliance automation.
[email protected] [email protected] ccpa.world/enforcement