Yashraj Shukla
5K posts

Yashraj Shukla
@whynesspower
quit my job to build fulltime | prev @observeAI (YC’18), @hexoai & 4x other YC startups | Built & launched 6 times last year • Fundraising

@SCR4India My college resume: docs.google.com/document/d/1qs… I try to be the very best at whatever I do and I enjoy working with people who feel the same. You can complain about the world or just create something of your own.










I’m incredibly excited to share this: MiniMax has just closed a new $2B funding round. 🚀 At the same time, our CEO, IO, shared three long-term commitments with the team: • No salary until we achieve AGI. • Over the next four years, he will dedicate shares equivalent to 4% of the company’s total equity from his personal holdings to reward employees who are building MiniMax for the long term. • Another 1% will be committed to supporting the open-source community. The funding is exciting. But what excites me even more is what it represents: a long-term commitment to AGI, to our people, and to the open-source ecosystem. We’re living through one of the most exciting moments in the history of AI, and we’re just getting started. If you’re passionate about frontier AI, open source, and building the future, we’d love to build with you. Intelligence with Everyone. 🚀








Does parity on dataset questions mean ForecastBench is “solved”? No. On market questions that require judgment about novel, one-off events, LLMs are still behind. Even on dataset questions, the 64.9% achieved by Google DeepMind is unlikely to be the ceiling of what’s possible. ForecastBench doesn’t stop being useful at human parity. It will continue tracking LLM progress even if they surpass expert human forecasters.



My conversation with @ScottWu46, founder and CEO of @Cognition, the company behind Devin, the first AI software engineer. 0:00 Scott Wu's Obsession With Winning 2:06 Competitive Programming, Games And Finding His People 4:24 Family, Go, And The Roots Of Scott's Competitiveness 8:35 Why Losing Hurts More Than Winning Feels Good 9:38 What Winning With Devin Looks Like 12:55 Devin Today: The AI Software Engineer 13:52 Software As The Human-Computer Interface 18:45 Why AI Progress Is Hard To Intuit 20:39 Thinking About AI From First Principles 22:57 What Happens When Agents Can Work For Months 30:18 The Original Thesis Behind Cognition 31:12 Launching Devin And Handling Criticism 37:17 Finding Product-Market Fit In The Enterprise 42:41 How Cognition Deploys Devin Inside Large Companies 48:34 Measuring ROI Instead Of Token Spend 50:01 Why Cognition Wants To Be Model-Neutral 52:18 Why Focus Lets Startups Beat Giants 57:14 Independence, Acquisitions, And Building A Generational Company 1:00:27 Why Money Is Not The Goal 1:03:42 One Life: Going For It All Includes paid partnerships.


Introducing LongCat-2.0 🐱 1.6T parameters · MoE with ~48B active · 1M context The full model behind Owl Alpha on @OpenRouter — now available. Built for agentic coding from the ground up: ◆ LongCat Sparse Attention (LSA) — scales efficiently for 1M-context tokens ◆ Zero-Compute Experts — dynamic activation 33B–56B per token, zero wasted compute ◆ MOPD — three specialized expert groups (Agent / Reasoning / Interaction), gate-routed per task How it stacks up: → Terminal-Bench 2.1: 70.8 → SWE-bench Pro: 59.5 (GPT-5.5: 58.6) → SWE-bench Multilingual: 77.3 → FORTE: 73.2 · RWSearch: 78.8 · BrowseComp: 79.9 📖 Tech Blog: longcat.chat/blog/longcat-2… Try it across different scenarios 🧵👇








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