Raj Chandra

This #CockroachJantaParty's Instagram account should be withheld in Indian, effective immediately because of foreign interference.

@heyshreyaaa They are misleading, only 9% Indians follow 😅

Honestly, India's youth has become way too easy to manipulate. No research, no critical thinking, no real understanding of politics, governance, or even basic civic sense.. just viral reels, edits, and blind hype. A random guy sitting comfortably in the USA creates a "youth party, says a few motivational lines online, and suddenly thousands start treating him like some revolutionary leader. Most of these people can't stay disciplined in their own lives, dont want to study properly, dont want to work hard, complain about everything, yet somehow think they fully understand how to change an entire country. Nobody asks the important questions: Who is the founder? What has this founder actually achieved? What's the real agenda? What experience does he have? What's the actual plan beyond social media marketing? But of course, asking questions requires intelligence. Blindly following trends is easier. This generation doesnt follow facts anymore. it follows whatever looks cool on Instagram..

Follower demographics reveal >40% Pakistani accounts and 90%+ overseas engagement—patterns consistent with coordinated influence campaigns designed to exacerbate domestic fault lines and erode institutional trust among youth demographics. Classic information warfare playbook.

Exploiting emotional narratives for political gain isn't new, but this operation exhibits characteristics worth examining.

@abhijeet_dipke The ACTUAL stats!! BTW, I see a very scary future ahead of you, pretty much like your paymasters! :)

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why. First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it. Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands. Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition. I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively. THE 100X ORGANIZATION The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago. Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken. The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems. These roles will evolve. But waiting for that to happen naturally means falling behind now. The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working. THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS — THE BUILDERS: 10X ENGINEERS I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality. Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment. AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down. Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed. So who do you want orchestrating and reviewing code? And how do you want your best engineers to spend their time? If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code. The new world is about enabling your 10x engineers to become 100x. The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated. I call this the great reckoning of AI coding, and every company will face this soon if not already. More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well. — THE BUILDERS: 10X PRODUCT MANAGERS Product management and design roles are merging. Designers that have customer focus, become more like product managers. And product managers that have intuition for UX become more like designers. The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results. The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy. Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on. To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production. Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck. That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time. — THE SYSTEM MANAGERS Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp. The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world. You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is. — THE FRONT-LINERS In a world that will become saturated with AI communication, the human touch will matter more than anything to customers. This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings. One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers. REWARDING 100X IMPACT In a world where companies are able to do so much more with less, where does that excess money go? In our case, much of the savings in this new operating model will flow directly back to those that enabled it. We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them. You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace. Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems. THE FUTURE Nearly every company will make changes like these. The ones that do it proactively will define what comes next. The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago. ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

LEAKED AUDIO FROM META ALL-HANDS AHEAD OF LAYOFFS TOMORROW Mark Zuckerberg, in his own words, told Meta employees their devices are being tracked to train AI models. His reasoning? Meta employees are smarter than the contract workers the rest of the industry uses for data labeling. So instead of hiring outside help, Meta is turning its own workforce into training data. "The average intelligence of the people who are at this company is significantly higher than the average set of people that you can get to do tasks if you're working through these contractors." He wants the AI to learn how "really smart people use computers" by watching employees work. He says the content is "stripped out" and none of it is used for surveillance or performance tracking. Then he admitted the rollout was botched but said Meta intentionally kept employees in the dark because leaking competitive AI strategy would help rivals. "It is not strategically in your interest for us to communicate everything in all the detail that we normally would on this." Translation: We're watching you, we told you as little as possible, and we did it on purpose. AI is replacing the contractor. Then the employee trains the AI. Then the AI replaces the employee. This story and this company keeps getting weirder.

I have uninstalled cursor, been over 3 weeks now. Replaced by @claudeai .

Scary 😱

True

How to Set Up OpenClaw in 30 Minutes (Step-by-Step): 00:00 Intro 00:51 VPS vs local 02:05 Installation: VPS 08:40 Installation: Local setup 13:00 5 top files 15:40 soul.md 18:32 Choosing models 20:27 Telegram Topics 22:28 Prompting 23:06 Skills 24:36 Subagents 26:18 Recap

INSTEAD OF WATCHING NETFLIX TONIGHT. Spend 30 minutes with this. How to Set Up OpenClaw for free (Step-by-Step). The people who watch this tonight will wake up tomorrow with a skill that most people will not have in 2 years. Watch it and Bookmark it now

When will @GeminiApp get folders on Android 👀

That's cool ⚡

LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So: Data ingest: I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them. IDE: I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides). Q&A: Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale. Output: Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base. Linting: I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into. Extra tools: I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries. Further explorations: As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows. TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

NotebookLM video overview on Andrej post.

@aiandchai @emergentlabs @RaghavChamadiya Congratulations 👏🏼👏🏼 Nice username lol 😅

Made it to the top 300 out of 10,000+ applications. Moving to the finale. Participating in a hackathon after so long. Going in with repowise and @RaghavChamadiya. See you at VibeCon and YC Startup School. @emergentlabs

@saumya_karan @claudeai @todoist How is it going, are you facing any problem with todoist MCP?

connected @claudeai to @todoist via MCP in about 30 seconds, workflow improved 10x

How do you add api key into @claudeai cowork, without leaking it for tools that don't have MCP 😅

Hung out with a Lovable super-user, who also happens to be a big creator of culture for my generation. It was great to catch up with you, @iamwill.