Manas Ranjan Kar

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Manas Ranjan Kar

Manas Ranjan Kar

@manasrnkar

Building compound LLM systems for my soul and healthcare

Boston, MA Katılım Ekim 2012
2.4K Takip Edilen852 Takipçiler
Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
Saw @HumorouslyVipul at my Cult today. Thought to go up and say Hi But my mind wanted to say “Vipul yahan soda lene aaye ho kya?”. Was funny in my head, chuckled and left minding my own business 😂
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Alfie Carter
Alfie Carter@AlfieJCarter·
I put the entire Claude Code GTM Engineering Playbook into ONE Notion doc. 8 sections. No fluff. - How to get set up correctly from day one: Pro plan, terminal install across Mac, Linux, and Windows, GUI install via Antigravity or VS Code, and bypass permissions mode - What to put in your project brain file, what to leave out, and how to get Claude to update it automatically when it keeps making the same mistake - How to run plan mode step by step and when to skip it for simple tasks - How to build a skill file from scratch, fix one that keeps failing, and install 5 GTM skills worth building first: lead scraping, email labeling, proposal generation, outbound sequence writing, and client onboarding - MCP install process, token cost checks after every install, the best MCPs for GTM work, and how to cut token usage by 50 to 100x by converting MCPs into skills - Sub-agents and agent teams: the 3 cases where they earn their cost, reliability math for parallel runs, and how to enable parallel variant exploration - What is eating your context before you type anything, how to use /compact and /clear correctly, and model selection for parent vs sub-agents - Modal deployment: any skill as a live URL in under 2 minutes, form interface setup, and connection to n8n, Make, or Zapier This is the setup I would have KILLED for before spending months piecing together how to actually get productive in Claude Code from documentation, YouTube tutorials, and scattered GitHub threads. Like + comment "CODE" and I'll send it over (must be connected for priority access)
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Jen Abel
Jen Abel@jjen_abel·
best thing i’ve read on X … f**k ‘storytelling is the ultimate compression algorithm for human attention. everything else, data, logic, tech feeds into it, but if you can’t wrap it in a compelling narrative, nobody will give a shit. people think they make decisions based on facts, but they’re mostly responding to the shape of a story, whether it’s a personal arc, a company vision, or a product pitch. if you want to accomplish anything meaningful, the story is the interface between it & the world. get that wrong & nobody will give af. get it right & you bend steel with your bare hands.’ @signulll
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mark pincus
mark pincus@markpinc·
I'm excited to share that my book, Life at the Speed of Play, will be out in June. I've spent the last 5 years writing so I can share my lessons and stories around building products and scaling companies.
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Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
My biggest fear is this - labs will increase (they need to) prices to a degree where salary of a human will be lesser than token costs. At that point, cos who bet on self deployed AI will win Contra view, but self deployed open source models may be the best bet for AI native businesses
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Garry Tan
Garry Tan@garrytan·
We're going to fight against this outcome, but it's a compelling and scary idea to be hyper-aware of as we go into new and uncertain times
goodalexander@goodalexander

The Big Rug Gooning is well covered in the Doom thesis. Elon's "Imagine" is digital crack cocaine being given out for free. So that's in progress. But, GPT5 shows us that enterprise / tool calls is where companies are converging This mirrors the rest of the economy. Consumer apps have to use ads or extractive loops (gambling/ porn/ DLC video games) to monetize at scale. Or you do Enterprise. Anthropic's CEO has indicated that companies pay up to 10x as much for better reasoning. And that training a model is positive unit economics t+12 months Which is the first time anyone is talking about unit economics. Which means the GPU costs of ppl just chatting away were getting gnarly. So today I'll write a bit about the Enterprise part of the Doom Thesis - which I call "The Big Rug" The core idea of the Big Rug is that everything you do in Claude Code, all the Vibe Coding you do, and even the work you do with AI that is covered by Terms of Service will end up getting completely stolen and monetized by AI research labs in order to justify their enormous valuations. The US economic system is not sustainable. There is a single chart below that shows this. US labor productivity is growing at 1.2% while Microsoft and other AI companies are reporting token consumption growth above 400%. Salesforce indicated that 30-40% of its code is written by AI but its cash flow from operations is up single digits along with its headcount. So -- if 100% of code was written by AI ... what would everyone do again? At the same time, AI very clearly is a thing. And there's huge demand. But the vast majority of companies are not using AI correctly. We can - in part, deduce this from basic common sense. VSCode and Copilot are terrible / borderline unusable if you use Claude Code/ Cursor. but they are in hyper growth nonetheless People are likely drastically increasing their technical debt. Because AI isn't good enough on default settings to really use to automate huge amounts of work. At least right now. Managers are saying "use AI". And employees are doing it. And doing it poorly. Because AI valuations are so high it's vibe coding and vaporware across corporate America. "We need an AI strategy" The most cynical VC I know just joined Cognition, selling 10s of thousands of seats to financial institutions. GPT5 isn't the Death Star. Productivity is growing at 1.5%. In boom times that can be 5-7%. We are definitively not in a productivity boom despite the hype. But then -- certainly this is not sustainable? If aggregate productivity is going 1.5% -- how is enterprise usage going to go sustainably at triple digits? Like -- the ROI is not going to be there. And then demand will go off an absolute cliff unless there is a fundamental non linear change in the cost of inference Indeed. Everyone knows this. Let's spell it out more specifically. 1. You are an enterprise agent company (whether that's openAI or Claude Code) 2. You see the slop generated by Vibe Coding 3. You see the same aggregate productivity statistics as everyone else namely that A. Margins are not expanding a ton B. Aggregate productivity is also not expanding 4. You know at some point an economic downturn results in massive cuts to token usage 5. Which makes your momo Q2 2025 into a hard comp and people start talking about a tech crash 6. But you just raised billions of dollars at a nosebleed valuation 7. You need to justify this valuation somehow or you're cooked Enter The Big Rug AI usage is a bit magical because you can't point to any single person or workflow that is responsible for training data. The training process, of compression, is a big jumble. We've already seen the implications of this in IP theft. Copyrighted material is fully known by ChatGPT. We don't know exactly how it ended up in the training dat,a bc the model weights aren't really intelligible. So it's hard to prove anyone did anything wrong. Even though the copyrights are there So if copyrights arent' enforceable. Trade secrets, methodologies, and non copyrighted user interfaces are *really not enforceable" This is an important point because many of the actions of closed source models explicitly break copyright and other laws, but they have such enormous financial legal firepower -- and the technical details are so hard to prove - that if you ask for Grok to render images from movies, it will. Or if you ask Chatgpt for the full plots of books - it will happily provide it. So there's already precedent for large scale non compliance with rules in the name of growth. And this non-enforceability is the nature of the big rug. Your employees don't really care about your enterprise IP and are more than happy to use closed source AI tools to help them be more efficient cogs. And then all this information and know how finds its way into the training data of AI research labs And then - when agents come out. It won't be enterprises tailoring agents to their use cases. It will be agents, essentially assembling apps that are FAR BETTER than anything those enterprises could do. With proprietary models that aren't for sale And because AI is completely portable, these agents could be spun off in offshore compliant jurisdictions likely with even less transparency. Or run through subsidiaries. Or even through crypto rails which are now getting supercharged by stablecoins So not only did you *not get an efficiency boost* because the Vibe coded apps were slop. But you also lost all your trade secrets, IP, and know how. And will be competing with an AI equivalent that will destroy your margins Welcome to the New Economy. It's essentially the largest vampire attack in corporate history. Everyone using closed sourced API models thinks they're going to be safe due to enterprise SLAs, or simply don't care (bc they're employees told to use Cursor or get fired). But they won't be safe. Once it's in the model. It's gone. So that's the Big Rug. And here's the funny thing. The Big Rug is actually necessary for this productivity chart to start going up. So before you get a massive acceleration in agentic workflows, the entirety of the people who formed the basis for those agentic workflows being created. Will be made completely obsolete / financially ruined. After the Big Rug - is when unemployment starts ticking up. Token growth will indeed go off a cliff but it won't matter bc we will be past the facade that for some reason AGI was going to be made accessible via API And if I were wrong, then these AI research labs wouldn't be worth what they are. And there wouldn't be animal spirits secondary demand for SPVs getting access to them at insane valuations. The writing is on the wall. You think you're vibe coding, but really you're contributing to the Agent that will drink your milkshake. The reason I haven't written about the Big Rug is that it's fairly far away. It will be a bit (maybe 12 months) before the research labs go mask off and launch agents directly instead of providing their models through APIs. Because as soon as this starts happening suddenly every company is going to lock down the usage of its coding tools. And presumably by then the ROI calculations won't make any sense Smart companies will adapt early on by using self-hosted API layers, and open source models even though they are worse. China will likely keep funding heavy open source development because it's a way to subtly promote the Chinese worldview -- so I guess the downside will be getting brainwashed by the CCP if you want to avoid the Big Rug. Once the Big Rug really kicks off, the enterprise software sector and any cloud player that hasn't hedged with their own AI research equity exposure will get completely shrekt. I've been a long time hater of Accenture and AI consulting plays, as they're basically in a 1-2 year white space of hope before the hammer drops pricing long term growth. Of course, the majority of cloud players have piled into the Labs for exactly this reason. If GPT5 were incredible -- I think we'd have a bit more time before this narrative kicks into gear. But now that the disappointment is there, the enterprise focus is there, the abrupt 'focus on unit economics' is appearing - the 2nd part of the doom thesis - the de-rating of everything non AI - should begin percolating. In crypto I am long Ambient to express this view - but it's a private holding with a minable test-net coming soon. My own network we're working to design to be more robust to the Big Rug (I think Google Docs, and Microsoft Word, and Github Gists are all basically going in the training data - so we are migrating to Proton Docs and using more encryption). In stonks it's genuinely terrible for the whole IT service sector (or anything in a software index that isn't heavily long OpenAI, Anthropic, or Deepmind). The white collar unemployment kick from the Big Rug should result in lower interest rates due to higher unemployment. The breach of trust/ economic shock should result in lower equity multiples. Other financial implications I'm still thinking through but just wanted to put this out here

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Prompter
Prompter@PromptLLM·
your relationship with uncertainty dictates your success
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Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
@NewsArenaIndia BJP will lose 2029 - Pradhan, Gadkari, NS will be biggest contributors to that. Paradoxically, GenZ will contribute most to loss of vote share
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News Arena India
News Arena India@NewsArenaIndia·
"Will urge scientific community to consider if Mahakaal Standard Time can replace GMT." - Union Minister Dharmendra Pradhan in Ujjain
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Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
@khurpenchh @DeepikaBhardwaj We need a group of lawyers willing to go pro bono to protect citizens raising their voice. This will keep the authorities in check - the only reason they behave this way is they feel it’s an individual and won’t have any recourse if we harass them enough
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खुरपेंच
खुरपेंच@khurpenchh·
First, we warned them, Then, we warned them again and gave them a hint, After that, we exposed them with complete documentation, we only shared the documents that were part of the internal committee report of FSSAI. Instead of taking action against the defaulters, they are targeting the person who is bringing these issues into the public domain. In the past, we have exposed many officials. Let them take us to court, they will expose themselves in the proceedings. Mark my words.
Gabbar@GabbbarSingh

While the govt has gone after FSSAI whistleblowers, has it shown any action against the allegations? At least re-assure the people that the allegations are false?

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Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
BJP’s chances of winning in Odisha are zero now. You don’t get to insult one of the Odia icons, probably the biggest one and get away with it Thank you @nishikant_dubey - we need you leeches out of there
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Jeongho Nam
Jeongho Nam@SamchonGithub·
I was invited by the Qwen team (@Alibaba_Qwen) to give a presentation at a Meetup. It is the story of the Function Calling Harness, which turns a 6.75% success rate into 100%. autobe.dev/blog/function-…
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Harry Stebbings
Harry Stebbings@HarryStebbings·
Most podcasts are BS because they are fluffy and lack substance. This is the densest, most insightful episode you will listen to this year. @gokulr breaks down the 8 defensible moats you need for your company to be successful in a world of AI. 1. Data (Proprietary and inaccessible) 2. Workflow (Deeply embedded operations) 3. Regulatory (Licenses and contracts) 4. Distribution (Exclusive proprietary channels) 5. Ecosystem (Third-party platform reliance) 6. Network (Marketplace liquidity density) 7. Physical (Infrastructure and atoms) 8. Scale (Low cost through volume) (Links below)
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Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
@anandc @ponnappa Biggest shift - a product or services company doesn’t mean the same thing anymore. Services need to offer a product and products need to have a key niche lest they be vibecoded away
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Manas Ranjan Kar
Manas Ranjan Kar@manasrnkar·
@mike_revenue Creativity and grit are the currency now, not code anymore. Great essay, really enjoyed reading this with my morning coffee 😃 We can’t build for companies anymore - need to build for agents
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Michael Davidson
Michael Davidson@mike_revenue·
@manasrnkar i’m seeing this internally and via friends and clients no one is looking for a “dev” anymore they’re looking for a vibe coder that can get things to market as fast as humanly possible really interesting to see how things are progressing
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Michael Davidson
Michael Davidson@mike_revenue·
If you run a business and want to stay ahead of the curve over the next 6-12 months you need to read this 35 pages. Free. If you understand what's in here and act on it, the upside for you is seven figures minimum. Not theory, insights and direction from doing this for 5 yrs docs.google.com/document/d/1mw…
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