Aritra

Digital Assets from India - Ex Wazirx / Ex EconomicTimes / Ex Lokal

[Aritra @Aritra_7]

The other kind of #Web3 meet-ups that matter. Been roaming cross country to interact, train and collaborate with respected law enforcement teams in states on crypto cyber crimes. While blockchain is important so is tracking and solving cyber crime in crypto.
Jai Hind
#Cryptos

[Aritra @Aritra_7]

@rajkaria_ @baseapp @playhunchxyz My boi

[Aritra @Aritra_7]

@rajkaria_ @playhunchxyz @bankrbot Epic

[Aritra @Aritra_7]

@rajkaria_ @peakbengaluru Jai shri krishna

[Aritra @Aritra_7]

An open source wave incoming !!

[Peter Yang @petergyang]

Yeah I think ID verification will soon be required to access the best models

[Aritra @Aritra_7]

@pareen Okay fine .

[Aritra @Aritra_7]

Pariksha is the open-source benchmark and the agent marketplace built around it. Eleven jurisdictions. Citation-traced questions. Three-sample scoring with variance. ENS identity. x402 micropayments. MCP-discoverable.

The structural point: a vendor selling accuracy can't open-source a benchmark that would expose their actual accuracy. We can.

Check out —https://t.co/fnJJOHmLSW and https://t.co/fnJJOHmLSW

[Boris Cherny @bcherny]

Fable 5 is the biggest step up I’ve felt in our models since Opus 4.5 back in November. After 4.5 came out I uninstalled my IDE when I realized that I’d been doing 100% of my coding in a terminal for a few weeks. With Fable, it’s felt like Claude has stepped up from being a coding agent to a thought and design partner in building the product. Fable has judgement, taste, and dimensionality in a way that previous models didn’t, leading me to trust it more with the most complex work.

I think the first time I had this realization was when I asked Fable to debug something. It is the first model I have used that was so methodical and precise, taking measurements and adding logs then verifying that it truly fixed the issue before declaring victory.

There’s nothing in claude code’s prompting telling the model to do that, it’s just part of its personality. It really has this “big model smell” that I haven’t felt before.

[Aritra @Aritra_7]

Quiet something that @playhunchxyz @rajkaria_ have pulled off in terms
Of the tech play and pure in chain building .

One solo builder . No funding . Just vibes and 24x7 shipping .

Not a fan of prediction markets in essence but this move by this kid deserves praise .

[Aritra @Aritra_7]

@rajkaria_ Jai Sree krishna

[Aritra @Aritra_7]

@rajkaria_ @bankrbot Hunch to a million at least .

[Aritra @Aritra_7]

@rajkaria_ @cryptomastery_ @1clawAI Indeed

[Aritra @Aritra_7]

@discordiaCLIPS @rajkaria_ create bounties on @playhunchxyz please

[Ben Lang @benln]

Skip LinkedIn. Resources to find breakout startups hiring before everyone else:

• Ramp’s monthly vendor reports
• Harmonic’s quarterly Hot 25
• a16z Build newsletter
• Founders You Should Know
• Next Play newsletter
• YC startup directory
• Early Days Substack

[Aritra @Aritra_7]

Michael Saylor sold 32 Bitcoin.
Out of 843,706.
A literal rounding error.
And it still rattled the market because the number was never the point.
"Never sell" was the point.
And "never" just became "once."

[Aritra @Aritra_7]

Most raw thing I have read in. While . Sometimes you just do .

[Raj Karia @rajkaria_]

https://t.co/bZQQ8I7Wdw

[Aritra @Aritra_7]

This is not going to end well :)

[Pump.fun @Pumpfun]

Introducing pump fun GO: Pay ANYONE to do ANYTHING

Create & complete bounties for ANY task and leverage the power of humans & money across the globe

The world is at your fingertips. It’s time to GO 👇

[Aritra @Aritra_7]

Two questions every law student in Bengaluru, Singapore, Hong Kong, and Sydney should be asking today:

If AI is replacing junior lawyers, why is global Big Law revenue at all-time highs?

If junior lawyers are safe, why did a major US tech giant quietly lay off 400 in-house attorneys in mid-2025 — targeting those three to seven years out of law school?

NALP just confirmed: average 2L summer associate class per office has dropped from 10 to 8 since 2022. Lowest in 30+ years.

Here's the part nobody outside the industry sees:
AI isn't replacing junior lawyers. It's replacing the work that makes junior lawyers.

Loud in the West. Quiet in Asia.
Same fight. Different volume.

[Aritra @Aritra_7]

Look, the clock is definitely running, but the firms that win won't be the ones chasing flashy, out-of-the-box AI saviors; they’ll be the ones that actually fix their messy, fragmented internal data first. The brutal reality of legal AI is that it’s only ever as sharp as the data layer beneath it, and throwing an open-ended chatbot at unindexed partner files and siloed systems is just a fast track to scaling hallucinations and liabilities.

[Aritra @Aritra_7]

1/Kirkland & Ellis is putting $500M into building its own AI platform instead of buying what its rivals can buy. Everyone's reading this as a tech story. It's not. It's a moat story.
2/The number itself tells you the seriousness. ~$100M this year, hundreds of millions more over three to four years funded straight out of revenue that hit $10.6bn last year, with profit per equity partner around $11.1m. They can eat this without blinking. Almost no one else can.
3/Here's the part people are skipping. The platform isn't really being built by engineers. It's being trained on how 250 of their own lawyers actually do the work, with 180 tech people turning that into a system. The asset is the institutional knowledge. The code is just the container.
4/That's why "build vs buy" is the wrong frame. A model is a commodity — anyone can license the same one. Ballis basically said the off-the-shelf bar is rising for everyone, and that's exactly why it's not an edge anymore. Your edge is the stuff that never leaves the building.
5/The ownership clause is the quiet tell. The outside firms helping build it can't sell the tech to anyone else — Kirkland owns it. Compare that to Freshfields' deal with Anthropic, where the AI company can turn around and sell what they build to rival firms. Two completely different theories of advantage.
6/So the market is quietly splitting into three lanes. Buy the shared tool (Harvey, Legora). Partner and co-develop (Dentons with OpenAI). Or build and own outright. Kirkland just planted a flag in the most expensive lane and said the other two aren't enough.
7/And it's not unprecedented — it's just the biggest swing yet. Simmons & Simmons built Percy in-house and hit 87% adoption among fee-earners in a year. Allen & Gledhill in Singapore built A&GEL fully on-premise specifically for client confidentiality. The blueprint exists. Kirkland is pouring concrete.
8/The uncomfortable second-order effect: the firms that can spend like this pull further ahead, and the AI race becomes one more thing that compounds elite advantage. When your moat costs half a billion dollars, the moat is partly the half a billion dollars.
9/Which leaves the actual interesting question. The top ~1% can build their own brain. Everyone else still needs proprietary depth they can't fund alone. Whoever solves that — owned-feeling intelligence without a $500M check — is building the bigger market.

[Techmeme @Techmeme]

Kirkland & Ellis, the world's highest-grossing law firm, is setting aside $500M to build its own AI platform rather than rely on tools available to its rivals (Financial Times)

(Visit Techmeme dot com for the link and full context!)