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Their AI is just bad. Figma solved real-time human collaboration, but completely missed the boat on human-AI collaboration. If the canvas doesn't evolve into an active, generative workspace that understands production code systems, teams will simply design where the code is born.

Been thinking about this for the last couple of days and put together a small prototype — Public Record. We discuss taxes, poor public services, cash demands in real estate, lack of support after layoffs etc. But how do we take a shared concern forward once the conversation dies down? The idea is: Issue → proposal → community ballot → collective submission → response A place where Indian taxpayers and citizens can find others facing the same problem, gather evidence, discuss a specific demand and decide whether to raise it together. The part I’m most interested in building is the automation behind that: Identifying which authority actually handles the problem. Finding the right route — grievance, RTI for information, or policy representation. Helping prepare collective submissions, or individual submissions where appropriate. Tracking responses and follow-ups. People would review and consent before anything is submitted. Also thinking of referendum-style community ballots on proposals. Informal and non-binding, showing what participating members support. For now, it’s just a frontend prototype. Sample content, browser-local posts/votes, no shared backend or automated filing yet. Sharing early to understand whether the idea is useful before building further. Two versions, both open without login: Version 1 — main product structure public-record-india.dineshdi… Version 2 — simpler UI public-record-india.dineshdi… Small background — NIT grad, around 2 years of experience, exploring this as a personal side project. Would appreciate honest opinions, especially from legal folks and devs. What could realistically work here, what am I missing, and what’s one issue worth starting with?

Every leap in human progress needed two things: intelligence to imagine what’s possible, and energy to make it real. AI is making intelligence more abundant. But data centres already use about 415 TWh of electricity a year. By 2030, that could more than double. Energy is becoming the defining final frontier of the AI age. Today, we’re officially announcing Energy AI Labs to build energy superintelligence. Compute has CUDA. Knowledge has LLMs. Energy still lacks an intelligence layer. We’re here to help build one and to advance the technologies that will power intelligence at scale. Our work spans two frontiers that belong together: >> AI for Energy: intelligence that helps batteries, grids, vehicles, storage and buildings sense, predict and act as part of a smarter system. Applied at scale, AI could unlock up to 175 GW of capacity on existing transmission lines and help save around 300 TWh of electricity a year. >> Energy for AI: the materials, methods, power systems and controls needed to keep AI running reliably as it grows. The scale is changing fast: NVIDIA is targeting 1 MW AI racks from 2027. And grid constraints could delay about one in five planned data-centre projects. Few years ago, we started with battery intelligence by building EV DOCTOR™ for batteries, one of the most complex, consequential nodes in the energy system. Global EV battery deployment is expected to rise from about 1.2 TWh in 2025 to almost 3 TWh by 2030. India is at optimal point, where these frontiers meet at extraordinary scale: a record 271 GW peak demand, with 300 GW on the horizon. We’re building this from India for the world, with a simple ambition: that no dream, idea or human possibility is held back by energy. Not for hype cycles, but for a real impact in our lives. The best part, this is JUST day one. @Ajayv93 @energyailabs

Hey people in my network also part of POINTONE Engineers We are holding our first space today. See you there 😉 Set a reminder for my upcoming Space! x.com/i/spaces/1oKMvNzqmRNGQ