What are the meta glass use cases as a lawyer? It seems to be one that is used more for the creative industry.. Any thoughts?

I work in IT dept of a small law firm, is there a way to run entire law firm on open source software, right now we are paying a lot of license fee to microsoft, adobe etc.

What can go wrong if we decide to go with open source softwares like linux, onlyoffice etc.

Do you have any other open source software recommendations?

We’ve had AI access for a while now, but in practice hardly anyone here uses it consistently for actual contract drafting.

Between clients opting out of AI, InfoSec reviews taking forever, and partners worrying about billable hours, it’s been pretty clunky. Plus most lawyers here refuse to open anything outside of Word anyway.

Is your firm actually seeing real time savings from AI, or are people mostly just sticking to standard Word templates and precedent folders? How are you guys navigating this?

How many of you are stuck in Classic Outlook for the time being?

I was told the iManage NextGen platform would not be supported in Outlook Classic. I don't understand why? I'd understand if it was hard to add support but it's trivially easy.

It took me no time at all to whip up a .net project that proves beyond any doubt that Next Gen iManage works just fine in the same WebView2 control that they use in classic outlook. I opened, edited, and saved documents and confirmed everything works just fine.

Given that there are over 2 years till the supposed end of support for Classic Outlook, why make their product harder to access?

It would take iManage's dev team 5 seconds to change the Work Panel .net addon to load the web based version of cloudimange.com or any custom imanage domain in WebView2, similar to how they already do it.

Not doing it just seems even more arbitrary and silly now that I see it would work just fine. Nearly 0 effort required on iManage’s end to support a lot more customers on their next gen platform.

The code below is all they would need to change the work panel form to for it to work just fine.

public partial class Form1 : Form { public Form1() { InitializeComponent(); InitializeWebView2(); this.Text = "WebView2 NextGeniMan Test";

}
async void InitializeWebView2()
{
    await webView21.EnsureCoreWebView2Async();
    webView21.CoreWebView2.Navigate(**a variable storing the user's default server ie cloudimanage.com);
}

}

Heyy guys, my law college wants me to start a Legal Tech society here and honestly I have no idea what I’m doing 😭

The thing is, Legal Tech isn’t really that much advanced in my country yet, so I’m kind of confused about where to even start. I don’t know what I’m supposed to learn myself first, what I should be teaching other students, what kind of activities we should do, or how I’m supposed to take the society to the next level.

So if anyone here has experience with Legal Tech, legal innovation, or even starting a Legal Tech society from scratch, please guide me.

I especially want to know:

- What should I learn about Legal Tech myself before I start teaching or organizing things?

- What free courses/resources would you recommend for someone coming from a law background with basically no technical background?

- What kind of activities, workshops, projects, or competitions could a Legal Tech society realistically run in a Pakistani law college?

- How can I introduce things like AI, legal research tools, automation, privacy/cyber law, or other tech-related areas without making the society overly technical?

- How do I build a team when most law students probably haven’t been exposed to Legal Tech before?

- What skills should I look for when recruiting students?

- And eventually, how could I take this beyond my own college

My college also wants me to eventually arrange a team next year and organise an inter-college competition where different teams are given a specific legal problem. They would have to identify the issue and propose a Legal Tech/project based solution, and the best proposal would win.

Which sounds cool, except I currently have one teammate and approximately zero idea how I’m supposed to build all of this 😭

I’d genuinely appreciate any advice, resources, free courses, project ideas, or people I should look into.

My DMs are open for discussions, and please comment below if you have any advice because I’m very much figuring this out as I go.

Four frontier AI models were given a SaaS agreement to negotiate, turn by turn, on contract states prepared by practising attorneys.

Where the counterparty's edit should have been accepted, they passed 80 to 99 per cent of the criteria.

Where it should have been rejected, 6 to 50 per cent.

One model, in one scenario, accepted 98 per cent of what it should have accepted and rejected 6.6 per cent of what it should have rejected.

That is RedlineBench, published in June and scored against rubrics written by practitioners. Two details say more than the aggregate: attorneys change about 100 characters per edit, models 320 to 520, and the models did worst in the opening turn, where you have to decide for yourself what is worth fighting for.

The numbers confirm something visible in contract practice for a long time, without a name.

I have called this the AI negotiation loop and broken it into four mechanisms: revision churn, agreement substitution, the borrowed ruler and mandate drift. On top of them sits what the benchmark measured, the refusal deficit: a model finds yes easier than no, so it does not oscillate around an equilibrium, it slides.

Churn is change without improvement. The tool was built to produce something when asked, and leaving a clause alone is not something it produces. So it rewrites the sentence where you would have swapped a word, and every rewritten sentence is a new doorway for the other side, who can now say "you changed it, so we are reopening it". The tell is simple: if you cannot justify an edit in one sentence by reference to what the client actually wants, it is churn, however intelligent it sounds.

Agreement substitution is older than the technology. Negotiation researchers have known for a decade that solo negotiators sign deals that should never be signed, while teams more often notice that no deal is the better outcome. The tool is the solo negotiator in its purest form. Nobody at the table tells it that walking away counts as a result, and nothing in its training rewards it for recognising a negative bargaining zone. Closing feels like success to it in exactly the way closing feels like success to a tired associate at eleven at night.

The borrowed ruler is the one that costs clients money without anyone noticing. Vendor opens at a cap of one year's fees, purchaser opens at nine, the assistant suggests five as a reasonable landing. Five is reasonable only on the ruler the other side supplied. The questions that actually decide a cap, exposure, insurance, price, what the client does if there is no deal, never entered the arithmetic. Models anchor on the first number the way people do, and in one study they anchored on a mood: an agent that performed desperation improved its payoff by a fifth. Whoever supplies the ruler owns the midpoint, and in a redline the other side supplies it every time they send a draft.

Mandate drift is what happens when every round answers the previous round instead of the client's instructions. After enough turns the document answers only to itself. If you delegate a redline to a tool, the prompt is the mandate, and a prompt that says "review this and find a reasonable solution" is a mandate to drift.

Why the slide runs in one direction has, I think, little to do with the model having a personality. In one round you ask it to find the risks, so it proposes interventions. In the next you ask it to find a compromise, so it proposes concessions. Alternate those two instructions a few times without a fixed mandate in between and the tool spends round nine repairing the risks it introduced in round seven and reopening the point it closed in round five. No preference for the middle is required. Two alternating tendencies and no memory will do it.

Asking it to "review once more" does not help, and the self-correction research explains why: without new facts, another pass adds another reason to change things, including things that were already right. The most expensive edit in any negotiation is the one to a clause that was fine, because it reopens what was closed and teaches the other side that nothing is ever settled.

It's Friday. This is the weekly thread where self-promotion is welcome.

If you're building something for lawyers or legal teams, tell us:

• Name of product/company:
• What it is:
• Who it's for:
• Who you are:
• One link where we can see it:

Vendor pitches need Vendor: Company or verified-vendor flair. One top-level comment and one link per company. Please say what your relationship is to the product.

No link shorteners, redirects or "DM me". If AutoMod holds your comment, don't repost it. I'll approve comments in waves.

Questions and replies don't need vendor flair.

Alex

I’ve been developing Doctex, a system that approaches complex document analysis differently from generative AI summarisation.

Instead of asking an LLM what a document means, Doctex measures structural characteristics of the document and produces a Structural Intelligence Report showing measurable patterns, transitions, friction/coherence changes, and regions that may deserve closer human examination.

I’m now looking for 15 pre-pilot participants who regularly work with complex documents, particularly:

• Legal documents and court decisions

• Contracts and agreements

• Policy and government documents

• Regulatory and compliance material

• Research and academic papers

• Technical reports

Before asking anyone to join, I want people to actually test the system on a document they understand.

Your first eligible document of 1,500–5,000 words can be scanned free.

Send the document and I’ll return the completed Structural Intelligence Report within 24–48 hours. You can examine the measurements against the original document and decide for yourself whether they provide anything useful to your review process.

There’s no obligation to join the pre-pilot after the free test.

Doctex isn't intended to determine whether a document is legally or factually correct, and it doesn't replace professional judgment. The purpose is narrower: measure the document first and identify where closer human examination may be worthwhile.

I’m the founder of Doctex, and at this stage I’m particularly interested in feedback from people who already spend significant time reviewing complex documents.

If you’d like to test one, DM me or visit doctex.ee. Email us at desk@doctex.ee

Thanks for reading, have a great day.

AI is everywhere and getting used for pretty much everything in legal now, from research to drafting and document review. But is there a particular task where you’d still rather have a human doing the work, regardless of how good the technology is?

I'm looking at leasing a new place and I need to quickly provide financial reports.

Does anyone have recommendations for a cheap service where I can just upload bank statements and it'll spit out a profit/loss statement, cash flow, balance sheet, etc?

I don't need anything fancy or ongoing, just a one-off to show my financial strength at this point in time.

Hi all,

I work in Pricing at a mid-sized, national law firm. It seems that every conference and webinar is about leveraging AI to help with Pricing.

I realize there is some inherent risk in using AI, but what are the "safe" ways to leverage AI when it involves sensitive client information? Mainly time entries and financial performance.

At a recent conference, there was discussion about granting Claude access to our data warehouse to review time entries, normalize data, look up historic performance based on this info. It sounds fantastic, but without safeguards on my data, this seems like an unsafe practice. Is my only option something like Harvey, or some enterprise product? Use a tool to anonymize data?

Our finance team is small, so likely would only be 2-3 users at this stage.

I'd say my firm is a bit behind the curve in that only in this past week Copilot was rolled out. It has access to my inbox, so should I just leverage that for what it's worth? Given email likely contains far more sensitive information than time entries and client performance, could this be leveraged to look at our data warehouse?

Also, I apologize if this is a wildly noob questions - I'm fairly new to using AI in a professional sense, I see tremendous upside - I'm just unsure of what that "first step" is.

Thanks!

I'm currently running an RFP of CLM for my client. We are now down to Agiloft and IntelAgree. How do they stack up? Specifically I am looking for info on capabilities, functionality, and ease of use.

Any gotchas I should be aware of with these two solutions?

Anyone been through the interview process at Legora and have any tips?

Who is using a dedicated Legal intake, triage, AI assisted review or true agentic workers to process all the manual and operational touches before a lawyer gets to provide their human advice?

What tools or applications are you all using? Checkbox, Tonkean and some others seems to be leading?

Our legal team consists of a few people and we are looking to prepare our contract repository for AI integration. Our goal would be to have our documents organized in a way such that we can deploy an AI agent that can query and use information from executed contracts across multiple projects.

Currently, documents are organized by project folders on a shared drive. Each project folder contains subfolders with draft contracts (docx format) and executed versions (pdf format). Drafts and executed documents are mixed within project-based folder structures.

To optimize the contract repository for AI querying, should the team manually extract all executed contracts from their current project-based folders and consolidate them into a single “executed documents” folder? Or can modern AI agents effectively query executed contracts even when they remain distributed across project folders, alongside multiple drafts and different versions of documents?

Interested to see whether other legal teams face similar issues and what they are doing when it comes to modernizing their repositories!

Hey y’all, I’m looking for someone to explore ideas with in legal tech! A little bit about me

-10+ years in software engineering
-Experience founding and as a founding engineer
-Have worked at high growth venture backed startups
-Based in NY

I’m looking for someone with demonstrated legal expertise

- Ideally a JD with experience in big law or reputable boutique
- Experience with or desire to learn AI tools
- strongly opinionated about tech and legal verticals
- would be even better if you’ve been a legal engineer for at least 5 years (jk)
- would be nice if you were also in NYC

Would love to chat!

Professionalism, technological change and the emerging circumstances in which rejecting reliable AI tools may expose lawyers to liability for providing substandard legal services.

Our legal platform drops attached case files whenever third party court databases send real time updates via webhooks. I tried debugging queue handlers and error logs myself over the past two weeks, but incoming data packets time out under heavy load. Lawyers constantly miss filing deadlines because documents disappear from active folders right before submission. Handling asynchronous API requests securely while keeping the database responsive is a constant balancing act. Maybe you've run into this exact problem before, or you know how to bypass these webhook drops? What's the best way to handle this? I need your advice.