The LLM can only generate text. The harness can do more than just generate text. By joining the two you're allowing the LLM (through text) to carry out whatever actions the harness can take.
My brain can only generate electrical signals. My hand responds to electrical signals and can interact with the real world. The two together can do more than just what my brain alone can do.
If you don't trust a particular brain, don't put a gun in the hand which is connected to it. If you don't trust a LLM, don't connect it to a harness which has access to your production database and only recent backups (https://www.theregister.com/2026/04/27/cursoropus_agent_snuf...).
Humans make mistakes too. In many cases, more often than LLMs. Humans are still useful for doing work.
I use AI extensively in my legal work. But I check every citation myself, manually. That means that I read the entirety of every case that I plan to cite in my output, and I check on Westlaw that it hasn't been overridden by a later decision. If you're just producing the AI's output verbatim, then you have only yourself to blame when things go wrong in the courtroom.
Maybe you check every citation, but there have been several news stories recently of lawyers using LLMs and using completely fabricated cases without verifying they exist
Legal professional here. This is NOT a replacement for proper legal AI assistants (e.g. Westlaw, in my jurisdiction). As far as I can tell, this is just a wrapper around regular LLMs i.e. nothing that you couldn't achieve yourself with the right prompting.
What legal professionals actually pay for, and that is virtually impossible to replicate unfortunately, is to give the AI access to a legal database of case law. Without case law, you can't do accurate legal research, and you are inviting disaster if you're doing things like drafting statements of case or skeleton arguments.
There's a reason why companies like Thomson Reuters have an oligopoly on these types of products, and can get away with charging thousands a year. They are the only ones with access to a comprehensive set of case law, and they've entrenched their position by having exclusive contracts with the law reporting companies. Without that, your model is just relying on publicly available cases that it can find on Google etc., and that's just a fraction of the full set.
With that said, these types of competitor products can be useful if you're just doing simple tasks like drafting letters or reviewing contracts and you accept that you need to do the legal research separately. But again, you can get that with just ChatGPT + a good prompt.
> There's a reason why companies like Thomson Reuters have an oligopoly on these types of products, and can get away with charging thousands a year. They are the only ones with access to a comprehensive set of case law, and they've entrenched their position by having exclusive contracts with the law reporting companies.
I'm not in the legal field, but can someone explain that further? I would have expected that all case law is public access. Not necessarily easy access, but when a judge writes an opinion, why on Earth would that opinion be gated behind a corporation? What am I missing?
Yes, it sounds crazy and against the principle of open justice, but unfortunately this is the reality. Certainly in the UK which is my jurisdiction - and I believe in the US too although I don't know for sure.
In theory, any member of the public can obtain a judgment by applying for one at the court and paying a fee. That's fine if you just need a one-off judgment, don't mind paying the fee, and you're not in a hurry. It also assumes that you know which case you need.
For realistic legal research, you might need to wade through dozens of cases just to even know if any of them are relevant, you might have a deadline of tomorrow to get it done, and you might not want to pay that fee for a bunch of cases that you aren't going to end up needing. Only a company which already has a comprehensive copy of virtually every important case can help you here.
A typical workflow for a complex piece of legal research might look like this:
1. You need to research a legal topic.
2. Do some Googling, or chat to your LLM, to get a rough overview and some pointers for further research (but don't completely rely on what you find).
3. Read some professional content (e.g. Practical Law articles relevant to the topic, or a legal textbook).
4. Read the relevant legislation.
5. Use a legal database to download all the cases you found from steps 2 and 3 which seem like they might be relevant.
6. Use a legal database to download all the cases which cite the relevant legislative provisions you found in step 4 and seem like they might be relevant.
7. Use the legal database to confirm that those cases are still good law (not overridden or criticised by a later case).
8. Skim read them, discard those that turned out to obviously not be relevant.
9. Read the remaining ones more closely.
10. Note any useful-looking cases which are cited in the ones from step 9, and recursively work your way through those cases as well.
Relying on court-provided copies of judgments won't realistically help you with most of these steps.
Related question, then - what do judges use when they have to write opinions in the first place? Do they have to follow the same process and use Thomson Reuters?
It's obviously even more important for judges (compared to lawyers) to be able to easily search all of the relevant case law to see which cases are controlling and would have precedence. Seems bizarre to me that this critical function would be gated behind a corporation.
The other answer (staff who use Westlaw) is right, but critically this is the point of adversarial litigation. The justice system doesn't hang on that judge finding the precedent; it assumes that the highly motivated lawyers on either side will find the relevant precedent that helps their case and highlight it for the judge.
those steps are what a RAG LLM agent setup excels at.
If tech companies invested 10% of what they have in AI assisted coding tools into AI assisted legal tools, they would be able to do those steps easily.
You can have as much RAG as you like, but if you're missing the data itself (the legal judgments), it's useless. The fundamental problem here isn't technical, it's that a very small number of corporations have complete control over the source material.
To be fair, there's sufficient of it publicly available (e.g. on https://www.bailii.org/) that you can easily disprove the conspiracy theory that laws and interpretations are "blatently inconsistent". In fact most judgments are very well thought through and carefully written and cited, because those that aren't tend to be appealed if they are establishing an important principle and getting it wrong. There just isn't enough publicly available to base a full legal AI assistant on.
Do not know about the US, but some countries publish some type of high profile cases but _only_ after anonimization for obvious privacy reasons.
To access the DB through the modern archive (well modern as new rules) you'd have to be an accredited professional passing through a few legal hardles and digital chancellor's office for each copy. It's like going to a bureaucracy^bureaucracy office.
Some early companies given their initial foothold were not required these checks so they were able to get hold of bigger archives (it's also important to remember often legislation or conformity is done through consulting or lobbying done by these entrenched players).
They can also build on the Data professionals themselves submit.
> Do not know about the US, but some countries publish some type of high profile cases but _only_ after anonimization for obvious privacy reasons.
It doesn't work that way in the US. Legal judgements are documents of public record, and they are normally published in full - it's not uncommon to search for someone's name and see legal cases pop up that they have been involved in.
There are specific instances where a judge can seal a judicial record (and records for minors are sealed automatically), someone may petition for their own records to be expunged, and parties may ask for some information to be redacted, but these are normally (except in the case of minors) not done automatically. As I understand it, the US has much more lax rules around the publicity of legal proceedings than other jurisdictions. For example, even though someone is deemed "innocent until proven guilty", arrest records and mugshots are reported all the time in the media even though this would be illegal in many other areas of the world.
Theoretically speaking if someone scraped all of it and added it to something like this open source Mike project would that then be a much better tool for lawyers?
Better than before, yes. Good for general legal work that doesn't require robust legal research, yes. Sufficient for full legal research, no.
The problem is that "a lot of case law" isn't enough case law. You need close to everything. Otherwise this can happen: Canlii case X -> Legal principle Y. Westlaw case Z not on Canlii -> X overriden, Y no longer good law. Or you might simply not find a case which cogently supports your argument, when one does in fact exist. Or, conversely, you are unaware of a detrimental case which your opponent knows about because they have Westlaw.
> Legal professional here. This is NOT a replacement for proper legal AI assistants (e.g. Westlaw, in my jurisdiction). As far as I can tell, this is just a wrapper around regular LLMs i.e. nothing that you couldn't achieve yourself with the right prompting.
I'd not use generative AI for anything but a cursory check anyway⁰. Even if it is trained on clean up-to-date data rather than all the wrong information that is out there, it could still give a wrong answer and I have no leg to stand on if I rely upon it. At least if I pay a human and they trust the LLM too much, I'll hopefully have some call to pursue them for giving bad advice when it bites me.
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[0] Or at all… But even if I wasn't someone actively avoiding LLMs, the point would still stand
There is enough controlling law publicly available to ascertain whether grounds for a suit exist, and for drafting sophisticated legal arguments for most actions in US federal court. I have not found the same for US state courts where law and especially legal procedure is deliberately not transparent (to the federal court system's credit, it is transparent). In my experience litigating pro se (by myself), I have found LLMs can assist effectively up to settlement for a a legal claim up to the low seven digits.
To be clear, the value of services like Legora and Harvey was not as a replacement for legal-specific services like Westlaw. LLMs are absolutely abysmal at legal research and analysis, and every week we are seeing reports of some lawyer being called out publicly for submitting a brief to a court with hallucinated case citations. This has happened to lawyers at all levels, including lawyers at big law firms. If you ask an LLM questions about very basic principles of law, it will do a decent job, but anything requiring nuance or specialization, they will spit out things that sound plausible, but are not correct.
And this is not likely to change in the future, as the legal market is so small and niche that the leading makers of LLMs have put legal analysis near the bottom of their list of priorities in terms of improving model performance. There is very little if any effort by the major LLM companies to curate sources of additional high-quality legal training data or fine-tune their models to improve performance on legal tasks. Law is also a field with very low tolerance for error, where tiny mistakes can have big consequences, and getting the models to perform well under these constraints would require a lot of investment without a sufficient payoff.
The true reason big firms are buying Harvey and Legora subscriptions is simply to use an LLM for LLM-type tasks, like document review, spotting issues in user-provided documents, and other things that LLMs do well. True, services like Harvey and Legora have lots of cool templates and features for legal work, but you will find that most of the people who use these services in these firms use them much the same way they'd use ChatGPT, Claude, or any other AI chatbot.
The reason law firms can't just use ChatGPT or Claude is that they can't allow confidential or privileged client data (such as documents provided through the prompts) to be stored and hosted on a third party service like ChatGPT or Claude, as these companies may have to turn over client data in response to subpoenas, and depending on the type of LLM account you have, these companies could use your user prompts to train future models thus risking leakage of client data to third parties and potential privilege waiver.
Services like Harvey and Legora solve this problem by accessing the LLMs through APIs, and all client data, prompts/responses, etc., are stored encrypted on Harvey or Legora servers and protected by keys held by the customer. For many law firms, this is 95% of what they're paying for.
The big challenge "Mike" presents to services like Harvey and Legora is that it exposes how little additional value they offer over ChatGPT or Claude, for the vast majority of law firms. A system like "Mike" can provide the same security benefit at basically $0 cost, and can be hosted on the law firm's own internal servers. This is going to put a lot of pricing pressure on services like Harvey and Legora; law firms are notoriously cheap when it comes to IT and software spend and will switch quickly if cheaper alternatives arise. This confirms that Harvey and Legora are going to have to sell their services based on the value they add to lawyer productivity, and not just on being a protected wrapper around GPT or Claude.
I've been looking into Harvey/Legora's competitive moat for a paper I'm writing. The claim that 95% of what firms are paying for is the data security offered by Harvey/Legora's API buffer is one that I see often, but now that foundation-model providers (Anthropic, OpenAI, etc.) offer zero-retention enterprise tiers and configurable data-residency options that allow firm-side systems to mediate document access without exposing privileged material to the model provider, is there really still any meaningful security benefit offered by Harvey/Legora?
VPN. Simple as that. Most companies aren't bothering to check anyway, most that do aren't detecting VPNs, and for the few that do that, there are ways to circumvent detection if you are really determined.
Not if you set the VPN up on your router. You can also buy small portable routers designed specifically to sit between your machine and your wifi / ethernet.
This is a common misconception. Namely, that increasing lifespan just means extending the part where your health degrades continuously. That's actually a very unrealistic outcome for life extension technology. In general, the things that cause your health to degrade as you age are interlinked with the things that cause you to die. If you find a way to increase lifespan, chances are you've also found a way to increase healthspan. In fact, all of the best methods we currently have to live longer do exactly that (e.g. exercise, eat healthily, avoid smoking, etc.).
You seem to be implying that at after a certain number of years (e.g. 79) you wake up one day and say "I'm fulfilled and have nothing left I'd like to achieve".
As someone who occasionally works with terminal patients, I've never seen that in practice. In reality most people desperately wish that they could carry on living, and have plenty of unfinished business that they'd like to see through. The only exception I've seen is when someone is in so much pain that they just want to end the suffering.
If we turn your argument on its head, a person who dies at 20 is just as fulfilled as a person who dies at 79. So why should anyone bother trying to live a long and healthy life?
You want it, but then you closed by explaining exactly why you shouldn't want it. Plus, the new baseline isn't neutral (as in, everyone is the same again). If humans can now do 10x the work as before, the employer doesn't need the same number of humans to carry out its work. So the new baseline is actually "let's keep 1 employee and fire the other 9", unless the business can find a way to suddenly expand 10x so that it needs 10x as much work done.
> So the new baseline is actually "let's keep 1 employee and fire the other 9", unless the business can find a way to suddenly expand 10x so that it needs 10x as much work done.
If they have any surplus of money (or loans) they'll try, so those 9 employees may end up becoming team leads or middle management, trying to start new initiatives to get the 10x expansion (and 100x improvement).
The market isn't anywhere near efficient enough to directly translate productivity improvements into labor reductions. Thankfully, because everything that's nice and hopeful and human lives within the market inefficiency; a fully efficient market would be a hell worse than any writer or preacher ever imagined.
lol that has nothing to do with market efficiency.
I’ve seen a number of your posts where you talk about topics you clearly are not all that well versed in, with such confidence when you’re plain wrong.
Of course it does have to do with market efficiency, of which the inertia and surplus within companies (especially large ones) is a part.
> I’ve seen a number of your posts where you talk about topics you clearly are not all that well versed in, with such confidence when you’re plain wrong.
I'm sure it's true. However, since you brought it up, can you be more specific and name three?
Yes, but in the long run, the market expects growth and innovation, not just doing the same thing with fewer workers. Especially when every other company can just buy the exact same advantage for the same price.
I don't think it's that unusual. It seems to me just to be a narrower version of panpsychism:
https://en.wikipedia.org/wiki/Panpsychism