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What all can I expect in an interview?
Hear it has gone to dogs after DJ took over as ED.
the website seems very different from what i have been hearing about her practise area.
Praying we're the ones that the teacher wouldn't call
We would stare at each other
'Cause we were always in trouble
And all the cool kids did their own thing
I was on the outside, always looking in
Yeah, I was there but I wasn't
They never really cared if I was in
We all need that someone
Who gets you like no one else
Right when you need it the most
We all need a soul to rely on
A shoulder to cry on
A friend through the highs and the lows
This merger will inevitably lead to reduction and rationalization at many levels. The merger is a clear indicator of a sector-wide crisis.The merger is a clear indicator of significant structural and financial turbulence across the UK higher education landscape.
https://www.businessinsider.com/anthropic-expands-legal-ai-tools-claude-cowork-2026-5
Call them what they are: TMC supporters. And their days are numbered. They will hop across to the BJP now.
https://x.com/IndiaToday/status/2054849661752779194
Now, commercialisation: it is a crapshot made using a sling owned by someone else.
The problem is that the market is flooded with AI wrappers doing the same thing, connecting the Legally India API, Claude API, or whatever cheap AI model they could find or got credits for from the company at the time. Now, if I do the same, I will be offering a subscription for โน1500-3000 a month, but then the output quality will degrade so much that it will become useless for everyone and anyone using it, no one will be using it, plus I will still be making nothing but losses as the margins are very thin at this price point. It will be the 100th AI legaltech company, claiming to revolutionize the field.
To do something truly good, Harvey AI type, I will have to incorporate a company, hire people, and regular run of the mill engineers aren't going to cut it. I am talking about top-tier talent, SDE 3 and above. These guys are in extremely high demand, so they'll charge even more to enter something this un-proven with someone who doesn't have a background in tech, if at all. At the top, for building everything, what I did was essentially make a tent. To make an enterprise product, you're looking at a building made of concrete that follows western building code. Handling 20-30k concurrent enterprise users, load balancing, cyber security at that scale is not just beyond my expertise level, but my comprehension as well. Now the building part involves a frontend and a very robust backend that isn't held together by duct tape and my hopes, and actual contracts with data providers. On top of that, I will have to make a database of my own that will have to get much bigger, deeper and nearly error-free, and would require constant updating. Think of daily updates from every High Court and District Court, making my own headnotes, summaries and stuff like that. EC2/Lambda instances to run the whole thing, and for AI models, Google Vertex or AWS Bedrock, with region/cross-region inference due to data residency requirements. This, by the way, was the least of my problems, as it is manageable.
The bigger worry is that I will have to subscribe to either the reserved tier or Provisioned Throughput tier. What both of these mean is guaranteed compute capacity no matter the load, which sounds good, but there is a very huge but: I will have to pay for the capacity even if anyone is not using it, I will be paying the same amount regardless. And you cannot use demand-based tier because those institutions who are paying good money are not going to tolerate downtime because your cloud provider ran out of compute, which happens often enough that you need to be plan for it.
I had an idea where I thought about using audio streams from virtual court meetings, converting them to text, linking them with the cause list and making a near-instantaneous court status tracker and data collector. But that would have required permissions from courts, it would have been prohibitively expensive and prone to errors as well, though it would have led to a great database.
Harvey AI is also facing similar issues in countries where they don't have a lot of customers: hardware sitting idle in data centres, still paying for it, making losses. But they charge $1,200 per seat per month with a minimum of 20 seats, so that comes to roughly $288,000 annually, and you can somehow make it work at that price point. It also needs to be taken into consideration that they raised over a billion dollars and are still burning money. Their token cost is higher as well due to the exact same reason I mentioned above: dormant compute.
For compliance, in order to sell to any decent organisation internationally you will need GDPR compliance, DPDP for India, ISO, and last but not the least, SOC Type II. SOC Type II deserves some extra focus: it is very important, costly and time consuming. To put things into perspective, this is the kind of certification American companies spend thousands of dollars on, and an entire company was set up in the US that claimed to use AI in the process to hasten it, called Delve.co . These guys are doing nothing but fraud by forging reports, and start-ups knew and were complicit. This should explain how time consuming SOC Type II is.
Now, even if I somehow secured funding and cleared all these hoops before going bankrupt, this business model is unsustainable and very short-lived at best. These companies are entirely reliant on other companies for the most important part, that is intelligence. You can make servers with enough money, but you cannot spring up a model out of thin air. I know someone will say they can use an open weight model, but the problem is not just that you are banking on Chinese companies continuing to release them it is that you only need one geopolitical event, one export control regime, or one strategic pivot for that dependency to collapse overnight. The probability is not even the point. The consequence of being wrong with no fallback is. And as of now closed models are still better.
The free cash flow of hyperscalers is coming to an end, and as that comes down, the funding for the labs will also start to dry up. But it is actually worse than that. Hyperscalers are simultaneously bleeding FCF on capex and not getting the physical capacity they are paying for on schedule. Cancellations have quadrupled, the total capacity under construction has declined for the first time since 2020, and transformers and electrical equipment sourced from China are holding up billion-dollar projects by a year or more. The compute supply that labs depend on is more constrained than the headline spending numbers suggest, and the return on that capex keeps getting pushed out. You cannot keep up the pace for very long. Then, when they get hungry for more money, because you cannot just keep making losses when your funding pipeline has dried up, the first entities they will go after are these middlemen. Not because they are small consumers, but because their entire business depends on them, and that is exactly why they have no leverage.
Think of movie distributors and how they twist the arms of cinema chains. They know PVR is sitting with around 1,750 screens that need to play something on them. They know they are desperate, so they do that, even though film distributors need them too. Customers are also not dying to go to PVR because of OTT and Telegram, the alternatives don't have to be perfect they just have to be cheap and good, so they are getting hammered from the supply and demand side. I know institutional contracts don't work like that, but I believe this analogy gets what I am trying to get through. The problem is that once these companies start to get squeezed, they can either absorb it or offload it to the customer and risk them migrating to their in-house tool, and if more customers leave, your costs increase, thus creating this deadly cycle. They aren't able to turn a profit even now; the future looks bleak.
Another problem is that you're nothing but a middleman, and if anything the internet has taught us, it is that the middleman gets crushed sooner or later. To be more precise about it the specific thing that is lethal here is the narrowing capability gap. As frontier models get better at legal reasoning out of the box, and vibe-coding the delta between using Claude directly and using a wrapper built on top of it shrinks toward zero. Right now every company is focusing on coding benchmarks and making the best IDEs and CLI tools, but the day they conquer that market they will come for this one with all their engineering experience and might. Plus, as models are getting more capable, their ability to sell simple solutions is short-lived at best. Think of what happened to CRUD developers: you cannot bank on complexity being the only thing keeping you alive.
The only thing that can save them in the long term is government protection, which in my opinion is very unlikely, as these guys aren't necessarily serving a purpose. Though I can be wrong as well. The thing that can truly save them is proprietary data and in my opinion this is the only thing that can save them. By data I mean a corpus of cases with their own headnotes, books, reports, articles and stuff like that, and not having to rely on third-party services for data. The issues are so big that you cannot just solve them. Palantir benefits from AI because of how good their management software is and how deeply it is integrated everywhere. With AI wrappers, I don't think the same can be said. I am making a very crude prediction so take it with a grain of salt they have a life of 10-15 years in my opinion.
Lastly, and this is the least important point: I feel it is very wrong to charge for plumbing that someone can do themselves with some learning. But it is not very important, as I am not really faced with the choice here, so saying how I would have acted when presented with the opportunity is rather abstract. What I can do, and will do, is share what I have built.
Even if you want to continue in that area, wouldn't it be better to go for an MBA later?
Curious though!
Is Mukul that big to be mean to a former home minister?
I think Sudhir has it right in many ways โ the batch expansion is well-intended, the plans to improve faculty quality make sense, and in all honesty, I personally enjoy the 'rigour' of NLS.
But when 'rigour' means nonsense handwritten assignments to combat AI, when batch expansion is not accompanied by concomitant infrastructural upgrades, and when faculty quality is diluted due to bloating in batch size, it is very very hard to support Sudhir.
โฎโฎโฎ folks - goss please??
(30s because more time for mentoring? thoughts?)
Looking for genuine leads please first generation lawyer here.
My mom told me that when we get older, we will regret it. ๐ข
And if you have a problem with neoliberalism why are you working with a corporate law firm, as you say you are?? Pure hypocrisy!
Background: Fresh graduate (Bo'26) from a T-2 Nlu, Average acads and co-curriculars, CV is Cap marks and Securities law oriented, did 2 callback/assessment internships at reputed firms in this practice area but was not fortunate enough to get a PPO.
Future consideration: I'm now thinking of getting into tax litigation as I have in the initial years of my law school took some experience in the same and enjoyed it.
Query: Unsure which practice area is better viz., Cap Marks or Tax in the long run. My factors of consideration are mainly: higher pay/money in the long run, exit options viz. Inhouse or consideration of experience further post MBA, International or abroad opportunity chances.
Ps - with Tax hereby I mean Direct Tax and International tax practice and I am as of now also inclined to pursue CFA or CAIA in near future, mainly to switch from law.
I will be highly grateful for any guidance on this. Thanks in advance!๐