Alex Hamilton

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Alex Hamilton

Alex Hamilton

@AlexHamiltonRad

CEO and co-founder of Radiant Law, curious about what happens if lawyers stop being so... lawyerly

Cape Town / London انضم Ağustos 2010
1.1K يتبع4K المتابعون
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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
It was never going to be one-and-done: thinking evolved, CLMs and GenAI blew up, and the team kept figuring things out. The second edition is being published on 24 June, with fresh content on purpose, ideal behaviours, and why relationships matter most (plus AI!).
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Jeff Carr
Jeff Carr@CarrNext·
@Levenger — best writing & travel stuff out there — sure it’s old school but also truly useful & practical. What do you think @AlexHamiltonRad, @ElevateNic, @LambZFTG, @liamjmbrown?
Levenger@Levenger

✈️☀️ Summer is calling — and so is your next adventure! Enter to win our #WellTraveledGiveaway, a curated collection of Levenger travel favorites valued at over $300. ⁠ Follow @Levenger, like, and tag 2 friends. Bonus: repost & tag us! Ends 6/13/25 @ 9:00 AM EST⁠.⁠

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The Jالی Contrarian
The Jالی Contrarian@ContrarianJolly·
@lawheroezV2 Isn't the problem that ai makes “anything that can easily be coded with ai” essentially free and therefore valueless?
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Nir Golan
Nir Golan@lawheroezV2·
You can AI code and Vibe code all you want but if you are solving the wrong problem or not solving a real problem, it doesn’t matter. *What to build* is still the most difficult, important, and valuable question for anyone building #legaltech
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James Landale
James Landale@BBCJLandale·
If you want a measure of the scale of the transatlantic rift, consider this: I am told yesterday was the 1st time since 1945 the US voted with Russia & against Europe at the UN on an issue of European security. Just let that sink in. 1/4
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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
@alexgsmith @CarrNext @ContrarianJolly @DCaseyF @damienriehl @lawheroez @ronfriedmann @jborstein @AdamsDrafting @smuckwell @pcarayiannis @Legal_Ev @wihender @jaesunum @DanLinna @inspiredcat @mmdestefano @MikeRoster @radiantlaw Too early folks, too early. We aren't particularly chasing AI right now (skunkworks aside) because we can see far greater gains using other paths. However we could easily pass this test using AI. If I win it's because it's generally safe to bet against lawyer adoption.
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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
I think I'm going to hang out at the other place now
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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
@jborstein That's quite possible. Under my hypothesis, though, they will probably be trying to solve for a different problem that just happens to need a legal solution on the way through, rather than coming at it as a legal problem.
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Joe Borstein
Joe Borstein@jborstein·
@AlexHamiltonRad I don’t expect a compete overlap, but do suspect it’ll be a lot of the same folks. I’m certainly in and doing my research.
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Joe Borstein
Joe Borstein@jborstein·
I’m not the only one who thinks the TAM of #legaltech is exploding. It will soon be able to “practice law” from a consumer point of view (though my legal ethics professor will certainly disagree, and will have valid criticism). Once the jump from, “assisting lawyers” to “solving legal problems” happens, the sector is going to go thermo-nuclear.
Aaron Levie@levie

One of the biggest open questions with AI is its impact on software business models over time. What seems to be under-appreciated about AI is how it can enable significant TAM expansion for a large number of categories over time when software can deliver outcomes, and not just enable existing work. Right now the dominant business model in SaaS is a per seat model, which inevitably means that the total number of seats you can sell is limited to the number of employees in the organization that are relevant for your particular software. Legal software is roughly capped by the size of the legal team, audit software is capped by the size of the audit team, and so on. The implication of this is that the customer generally *already* has to have not only a need for your solution, but also the existing headcount in the organization to become users of your software. Incidentally, this is often why so many SaaS products tend to go after horizontal productivity categories, because this maximizes the number of potential users you have access to in an organization. AI flips this on its head, especially with the power of AI Agents, and you get a new form of “outcome-as-a-service”. When AI is actually doing the work within the software itself, you're no longer constrained by the number of employees inside the organization to use the actual software. The software is quite literally bringing along the work with it and delivering a particular business outcome. It's clear the full potential of this playing out is not fully understood, as this represents a massive transformation of software as an industry.  When you are no longer constrained by the size of a team or department to use your software, markets are no longer arbitrarily capped in size. In this new era, software that powers a legal workflow actually brings the equivalent of legal knowledge work along with it, and software for audits brings the equivalent of audit work with it. All of a sudden small businesses, under-resourced teams in large enterprises, and all new geographies begin to open to up as markets. AI will enable otherwise niche categories of software to become much larger, and already large categories of software to become even bigger. This transformation is similar to what we've seen in other markets where a new innovation has unlocked the size of a market well beyond its original demand. For instance, most investors and economists would have thought the size of Uber or Lyft's market was the size of the existing Taxi market, when in fact the market size was orders of magnitude larger once the shape of the product changed to make the offering easier to consume. We’ve seen this effect time and time again in areas like SaaS, cloud computing, a variety of mobile categories, and more. We’re only in the earliest of stages of figuring out what this all means for the future of the software business model. Clearly all new variables of monetization will need to emerge when you start to pay software vendors for outcomes as opposed to just the software itself. But inevitably, when you remove the existing dominant constraint of enterprise software, TAM expansion will follow.

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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
@jborstein I'm not sure it will necessarily be the same people. Suspect the people who will have the biggest impact are going to be solving a different problem and just accidentally law on the way.
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Joe Borstein
Joe Borstein@jborstein·
@AlexHamiltonRad Ok, but that’s semantic. It’ll be the same group of people, solving the same problems, just making even more $$$. Way more $$. Also, doing a lot more good for the consumer of legal services.
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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
It was never going to be one-and-done: thinking evolved, CLMs and GenAI blew up, and the team kept figuring things out. The second edition is being published on 24 June, with fresh content on purpose, ideal behaviours, and why relationships matter most (plus AI!).
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Alex Hamilton
Alex Hamilton@AlexHamiltonRad·
And of course @DCaseyF, who is always good for a beer (whoever is buying).
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The Jالی Contrarian
The Jالی Contrarian@ContrarianJolly·
@AlexHamiltonRad Yeah, pretty much: it just doesn’t pick up minor stuff (at character level), and it can’t do tables. It works okay if you edit inline with track changes on but that isn’t always practical. If you could be bothered writing a macro to strip out formatting changes it would be better
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The Jالی Contrarian
The Jالی Contrarian@ContrarianJolly·
legaltech chat: Litera is the flagship comparison app. Text comparison is hardly a challenge in 2024. But Litera blows. Surely there are better, cheaper alternatives?
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