Anthropic raises $13B, triples valuation to $183B, focuses on enterprise AI.

Indian startups KOGO, Sarvam AI, and thriwin.io are redefining the nation's AI ecosystem with impactful innovations across enterprise and consumer sectors. Bengaluru-based KOGO, in partnership with Qualcomm, has launched a secure private AI platform designed for regulated industries such as banking and healthcare. Recognized by Accenture Ventures, KOGO's on-premises AI agent deployment is setting new benchmarks for edge AI adoption. The platform focuses on data privacy, compliance, and low-latency operations, marking a major shift toward trusted enterprise AI in India. Sarvam AI, founded by Vivek Raghavan and Pratyush Kumar, is creating sovereign large language models supporting over ten Indian languages. Meanwhile, Thriwin.io, founded by Vamshi Mangu and Arnav Neil Mukherjee, is transforming lead generation and sales automation for startups and SMEs.

Garry Tan (Y Combinator CEO) told me that before AI, the average YC startup grew 2-4% 𝘄𝗲𝗲𝗸𝗹𝘆. Now, it’s 10% weekly growth (some even hit 20%). Here are 3 reasons why: 1. Buyers stopped dragging their feet Before AI, founders would pitch their software to a company and hear: “We already have something that works. Maybe next quarter.” Buying better software was a “nice-to-have.” He said event enterprise customers might stick with spreadsheets instead of trying new software. AI made software an 𝘂𝗿𝗴𝗲𝗻𝘁 need. Take CaseText, one of YC’s breakout legal AI startups. Before AI, their sales cycle took a full year. After they built AI into their product, it dropped to one month. Lawyers saw how much billable time it saved and bought it on the spot. 2. Founders can ship in weeks, not months/years. YC companies used to take months to build and iterate. Now, Garry says startups with 10-20 people are hitting $10–20M in revenue within 20 months. “That’s literally never happened before in software.” AI coding tools are doing the heavy lifting: - Claude Code writes 95% of its own code - Cursor makes engineers 20% more efficient - Replit lets founders deploy products overnight A team that once needed 200 engineers can now move just as fast with 20. That means faster shipping, faster feedback, and faster growth. 3. They’re solving boring, trillion-dollar problems The fastest-growing YC startups aren’t chasing ChatGPT clones. They’re applying AI to overlooked, high-friction industries: HVAC, compliance, logistics, and accounting. “You can’t just take ChatGPT and have it do that type of work yet,” Garry said. “So founders are building perfect-fit tools for real people.” Those markets are massive, fragmented, and starving for better software. → 𝗟𝗲𝘁 𝗺𝗲 𝗸𝗻𝗼𝘄 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀 𝗶𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝗮 𝗿𝗲𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝗼𝗳 𝗺𝘆 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗚𝗮𝗿𝗿𝘆 𝗼𝗿 𝗶𝗳 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗼𝗳 𝗼𝘁𝗵𝗲𝗿 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗴𝗿𝗼𝘄𝗶𝗻𝗴 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝗮𝗶.

Since the launch of OpenAI’s artificial intelligence (AI)-powered chatbot ChatGPT in late 2022, 100 startups have reached unicorn status, reflecting the sector’s rapid growth and heightened interest from the technology and investor community.

The Rise of Vertical AI Startups Horizontal AI tools (like ChatGPT) created awareness. But the next trillion-dollar opportunity lies in vertical AI — focused, trusted, domain-specific products. Think: → AI legal assistant for contracts → AI tutor for NEET aspirants → AI financial analyst for startups Each of these verticals already has user demand — they just need specialized execution, UX, and trust. We’re moving from general intelligence to contextual intelligence. And whoever owns context, wins. #AI #VerticalAI #Startups #Innovation #FutureTech

💸 The Harsh Truth About GenAI Startups Nobody Wants to Talk About Everyone’s building a GenAI SaaS startup these days — text tools, slide generators, code copilots, design assistants, you name it. But here’s the uncomfortable reality 👇 🧮 Every new user costs money. Running an LLM call (even a short one) isn’t cheap — compute, GPUs, inference servers, API costs — all add up fast. 💰 And conversion rates? Most users try once, leave, and never pay. The “freemium funnel” that works for traditional SaaS doesn’t work here — because the cost to serve a free user is way higher. So you end up with a brutal equation: High acquisition cost + High compute cost + Low conversion = Negative unit economics That’s why even the biggest GenAI players are still burning cash. Every “free” query eats into margins. Every “try our AI tool” campaign deepens the loss. And few users stick around long enough to justify the expense. 🚨 The takeaway? If you’re building an AI startup today, don’t just build a wrapper around GPT. Think deeply about: Your differentiation moat (data, UX, or workflow integration). Your unit economics (how you’ll make money before scale). Your retention strategy (how to keep users coming back). Because “AI + subscription” is not a business model — it’s a cost center with a landing page until proven otherwise. 📊 Market dominance does not equal profitable unit economics ChatGPT is reported to hold ~62.5% share of the B2C AI subscription (paid AI tools) market.  It also commands ~79–80% of the chatbot / AI assistant market share in many rankings.  But — here’s the kicker — only ~10 million users of ChatGPT are paying subscribers (Plus, Pro, etc.).  That means out of hundreds of millions of users (weekly active users reportedly ~800 million) , a tiny fraction is generating real revenue. So while ChatGPT’s reach is massive, its monetization funnel is narrow. 🔥 Curious: Do you think GenAI SaaS startups are doomed by economics, or will falling compute costs and better models fix this in a year or two?

If you’re building an AI startup today, your roadmap just became obsolete. Sam Altman has quietly killed 100s of startups overnight. By turning ChatGPT into an operating system for intelligence, OpenAI is collapsing the layers between apps, APIs, and users. This isn’t another product release. It’s a reset button for the software ecosystem. 𝗪𝗵𝗮𝘁’𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗰𝗵𝗮𝗻𝗴𝗲𝗱: ChatGPT is no longer just a chatbot. It’s becoming the execution layer for digital work. Third-party apps now live inside it — meaning you don’t need to “open” software anymore, you just ask for outcomes. OpenAI is turning conversation into computation. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 For Enterprises:   • Seamless cross-platform orchestration could finally become real.   • AI-native workflows will redefine productivity and decision-making.  • But vendor dependency and data control will become new strategic concerns. For Small Businesses:  • Lower barriers to automation — plug into the AI OS and operate at enterprise scale.  • However, differentiation will be tough when every competitor uses the same core AI brain. For AI Startups:  • This is the big disruption.  • Most “AI apps” just got reduced to features within a larger ecosystem.  • Infrastructure, orchestration, and general-purpose agents are now commodities. To survive, startups will need:  • Deep domain specialization  • Proprietary data and user context  • Defensible trust and transparency models  • The moat isn’t the model anymore — it’s the context and credibility you own. 𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝗿 𝗽𝗶𝗰𝘁𝘂𝗿𝗲 Software is being rewritten — not line by line, but layer by layer. Building apps is no longer the destination; it’s the baseline. This moment is both thrilling and unsettling — a reminder that in tech, the ground never stops shifting. If OpenAI succeeds in making ChatGPT the operating system of the AI era, the real question is — who builds on top of it, and who gets built over?   #OpenAI #AI #Startups #EnterpriseAI #FutureOfSoftware #SamAltman

AI Unicorn Boom Post-ChatGPT Since ChatGPT’s launch in late 2022, 100 new AI startups have reached unicorn status – and investors are all in. A CB Insights report reveals: • 36% of AI unicorns are backed by tech giants like Nvidia, Google, and Microsoft • Nvidia leads with stakes in 24 unicorns, including robotics firm Skild AI • LLM giants like xAI and Anthropic dominate in funding and valuation • Humanoid robots are gaining momentum, with projections of a $5T+ market by 2050 On the exit front: • CoreWeave went public, raising $1.5B • Windsurf and BioCatch were acquired • Next in line? UK-based Beamery and Huma The AI wave is far from over. https://lnkd.in/epypTeMK

With so many startups emerging in the GenAI/Agentic wave, what is their moat? I just finished another great podcast episode from Y Combinator discussing the Seven Powers framework from Hamilton Helmer which can be equally applicable for AI startups too. ◾ Process Power: Building complicated systems that become hard to replicate, such as finely-honed AI agents serving regulated industries (e.g., KYC for banks), where reliability and depth make clones impractical. ◾ Cornered Resources: Gaining access to unique and covetable assets, such as proprietary data, regulatory approvals, or specialized talent—like how AI companies integrate with government or create specialized datasets for model training. ◾ Switching Costs: Making it painful for customers to leave by deeply integrating AI agents into their workflows and operations, similar to legacy enterprise SaaS like Oracle or Salesforce—often enabled by long pilots and custom integrations. ◾ Counter Positioning: Adopting a disruptive approach incumbents cannot copy without undermining their own business; for example, shifting from per-seat to task-based pricing as AI automates away traditional roles. ◾ Brand Power: Building consumer trust and mindshare, as illustrated by OpenAI's ChatGPT overtaking Google's product despite Google's massive user base, because ChatGPT became the recognized 'AI brand'. ◾ Network Economies: Growing a product's value as more people use it, often manifesting as valuable proprietary datasets that improve AI models with scale, or facilitating data-driven product improvement flywheels. ◾ Scale Economies: Reducing per-unit cost by operating at larger scale—most apparent at the AI model level, as hyper scalers use enormous amounts of capital to train powerful LLMs, making it hard for smaller players to compete directly on cost or capability. It's interesting how one can approach competition counterintuitively against existing moats. The biggest issue large enterprises may face is speed. Due to their rigid processes and operational aspects, they often cannot ship features quickly enough. Take Cursor as an example, which was shipping new features almost daily. Another aspect is that if an existing software's moat is switching cost, startups may use AI to accelerate migration and reduce switching costs. While the Seven Powers framework originated for web-era companies, its principles remain relevant and actionable for AI startups seeking sustained competitive advantage in today's fast-moving market. In the end, you are not going to go wrong with speed, specialization, and data!!

🚀 ChatGPT Will Be 10x More Powerful in Under 18 Months! 🚀 In a recent interview with Vinod Khosla, founder of Khosla Ventures, OpenAI CEO Sam Altman shared groundbreaking insights on AGI, the future of work, and venture trends. One standout takeaway: GPT-6 is expected to be at least 10x more capable than GPT-5! Here’s a summary of the key points: 🧠 GPT’s Next Leap 🔹 From 0 to 1: Altman compares the journey from GPT-1 to ChatGPT as the "0 to 1" revolution in AI. 🔹 From 1 to 100: We are now moving from "1 to 10," and in the next 18 months, GPT is set to leap from "10 to 100." 🔹 10x Power: GPT-6 is predicted to be ten times more powerful than GPT-5—though public perception of this shift may be muted as AI becomes more normalized. 💼 Impact on Industries & Work 🔹 Software Revolution: AI will generate custom software on demand, reducing the need for traditional SaaS. This shift could disrupt legacy business models. 🔹 The Human Touch: While AI may handle many knowledge tasks, jobs requiring genuine empathy—like teaching—will remain human-driven. Students need inspiration, not just information. 🔹 Accelerated Innovation: Whether through AI assistance or collaboration, research and creativity are speeding up dramatically. 💡 Advice for Entrepreneurs & Investors 🔹 Don’t try to build “another OpenAI.” 🔹 The real opportunity lies in new services and sectors emerging after AGI becomes widespread. The next trillion-dollar company will likely be built on top of AI, not within AI itself. 🎯 The Vision Behind OpenAI & ChatGPT 🔹 From Research to Product: OpenAI shifted toward product development due to scaling needs, starting with the GPT API. 🔹 The Chat Interface: ChatGPT almost didn’t launch due to low early user retention—but persistent engagement convinced the team to move forward. 🔹 The Ultimate Goal: A personal AGI assistant that doesn’t just chat but works, creates, learns, and acts on your behalf across platforms. 🌍 Ensuring AI Serves Everyone 🔹 Altman advocates for affordable and accessible AI tools to prevent monopolization. 🔹 Major innovators should profit, but the benefits of AI must be shared broadly and affordably. 🔹 Computational resources should be democratized—AI should reduce inequality, not deepen it. In summary: Technological evolution continually reshapes industries. Companies that fail to adapt don’t just lose to competitors—they fall behind the pace of change. Let’s learn from the past, embrace AI empowerment, and move forward—together! #AI #GPT6 #AGI #OpenAI #FutureOfWork #TechTrends #Innovation #AIForAll #DActionConsultancy

🚀 Imagine a 22‑year‑old founder hiring ChatGPT as her CTO and then raising AU$2 million for her AI startup, Lucent. Alisa Wu’s story isn’t just a headline – it’s a snapshot of today’s AI reality. 🔍 What does this mean? - **AI is becoming a core team member**: Companies are treating language models as co‑founders, not just tools. - **Funding is flowing into open‑source‑friendly ventures**: Investors see the value in building on accessible AI, not just proprietary giants. - **Youth and innovation are reshaping the landscape**: Fresh perspectives can accelerate adoption of AI in ways that older, more cautious firms may miss. 💡 The takeaway? If you’re watching AI evolve, you need to understand how these models are being integrated into business strategy—beyond the hype. The line between “tool” and “partner” is blurring, and it’s happening now. 👀 Want to stay ahead of this shift? Click on my profile photo and follow me for real‑world insights, practical guides, and the latest updates from the open‑source AI community. 🔗 DM me for more details about joining the Open Source AI Builders Club.