I see this also purports to link to secondary regulation, but there's a reason lawyers pay huge chunks of cash to professional firms that ingest court decisions and other sources of applicable regulation. Meh, there's a reason _lawyers_ are paid huge chunks of cash to be kept on retainer and give their opinions to begin with.
It's harder to solve some of these problems than prompting an LLM to vibe a solution. I wish we'd stop.
Recently whenever I see something that's vibecoded and I see nobody taking personal responsibility for it: company entity, linkedin profile links - I leave immediately - it's not worth spending my time if the author was not willing to put their reputation at stake.
I guess this is a universal method. In the time when we can have 100 pages vibecoded in an hour by agents, how do we decide which are actually worth human time?
The agent doesn't feel a notion of cost or time, for them producing slop is free. For us humans, reading slop is at cost of cognitive overload.
I built this because tracking AI regulation by hand stopped being possible. The EU's Digital Omnibus just reshuffled the AI Act, and it's easy to confuse the headline with what's actually in force — e.g. the Article 50 transparency duties still land on 2 August 2026 even after the reshuffle.
What it is: one API covering AI law across 50 US states + DC + federal + EU + other jurisdictions, refreshed daily. Each record carries provenance and an official source URL. The interpreted layer (obligations, penalties, effective dates) is human-audited and sourced — not LLM-generated — because a hallucinated compliance deadline is worse than no answer.
There's also an MCP connector (24 tools) so you can query laws, obligations, penalties and deadlines directly inside Claude, ChatGPT or your own agent.
You can try it without a card: grab a free API key at ai-law-tracker.com/developers#get-key, or see the live Omnibus breakdown at ai-law-tracker.com/omnibus.
Two things I'd genuinely like feedback on:
1. The accuracy model — every record is checkable via a public accuracy ledger, and there's a bug bounty for wrong data. Does that go far enough to trust it under your product?
2. The MCP tool design — are 24 tools too granular, or is that the right shape for an agent to reason over regulation?
Happy to answer anything about the data pipeline or how records are verified.
Would you use this yourself? Would you trust your own project for legal advice?
I’m the resident “Claude designed this” guy but I am not even going to bring the frontend design up.
As another commenter said, you claim ~1250 laws manually verified, is there a name for the person who verified this? Will they be willing to put their reputation behind it?
Laws are the easiest thing to hallucinate due to them worded the same way an llm talks.
You can’t take people’s money and say “ This is not legal advice. Consult a qualified attorney for specific legal decisions.”
Hey I love the idea, don't let the haters get you down just because the site was vibe coded, that's trivial to improve upon.
I do think more information is needed to understand exactly where these claims are coming from. Not sure the "not legal advice" tiny text at the bottom is enough, people are going to see the claims and most won't double check.
How did you implement the tracking feature? Do you plan to narrow down in one legal sector where this could be especially useful?
What does the human check mean? The homepage says 1,287 of 1,288 laws were re-checked today...
Interesting idea, but the front end sloppiness is not filing me with confidence.
I see this also purports to link to secondary regulation, but there's a reason lawyers pay huge chunks of cash to professional firms that ingest court decisions and other sources of applicable regulation. Meh, there's a reason _lawyers_ are paid huge chunks of cash to be kept on retainer and give their opinions to begin with.
It's harder to solve some of these problems than prompting an LLM to vibe a solution. I wish we'd stop.
I guess this is a universal method. In the time when we can have 100 pages vibecoded in an hour by agents, how do we decide which are actually worth human time?
The agent doesn't feel a notion of cost or time, for them producing slop is free. For us humans, reading slop is at cost of cognitive overload.
What it is: one API covering AI law across 50 US states + DC + federal + EU + other jurisdictions, refreshed daily. Each record carries provenance and an official source URL. The interpreted layer (obligations, penalties, effective dates) is human-audited and sourced — not LLM-generated — because a hallucinated compliance deadline is worse than no answer.
There's also an MCP connector (24 tools) so you can query laws, obligations, penalties and deadlines directly inside Claude, ChatGPT or your own agent.
You can try it without a card: grab a free API key at ai-law-tracker.com/developers#get-key, or see the live Omnibus breakdown at ai-law-tracker.com/omnibus.
Two things I'd genuinely like feedback on: 1. The accuracy model — every record is checkable via a public accuracy ledger, and there's a bug bounty for wrong data. Does that go far enough to trust it under your product? 2. The MCP tool design — are 24 tools too granular, or is that the right shape for an agent to reason over regulation?
Happy to answer anything about the data pipeline or how records are verified.
I’m the resident “Claude designed this” guy but I am not even going to bring the frontend design up.
As another commenter said, you claim ~1250 laws manually verified, is there a name for the person who verified this? Will they be willing to put their reputation behind it?
Laws are the easiest thing to hallucinate due to them worded the same way an llm talks.
You can’t take people’s money and say “ This is not legal advice. Consult a qualified attorney for specific legal decisions.”
I do think more information is needed to understand exactly where these claims are coming from. Not sure the "not legal advice" tiny text at the bottom is enough, people are going to see the claims and most won't double check.