RamPrasad "RamP!" Moudgalya

Created a list of around 100 books that had major impact on me over the last two decades. These are also the books that I've re-read several times. buff.ly/2xaaDLd

Before you spend $2,000 on an AI course, read this. A lot of people are buying expensive AI courses right now. But honestly, most of them don’t need to. Some of the best AI learning resources in the world are already free. And they’re not built by self-proclaimed AI experts online.They’re created by the companies actually building the models, chips, tools, and infrastructure behind this entire AI wave. If you want to learn AI properly, it makes sense to learn directly from the source. But before that, Check out 100+ such resources shared in this community of 200K+ AI/ML Engineers: codenewsletter.ai/subscribe?utm_… Here's a list of 10 free AI learning platforms from industry leaders: 𝟭 - 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰: lnkd.in/e5fK7QUA 𝟮 - 𝗚𝗼𝗼𝗴𝗹𝗲: grow.google/ai 𝟯 - 𝗠𝗲𝘁𝗮: lnkd.in/et6wz-ta 𝟰 - 𝗡𝗩𝗜𝗗𝗜𝗔: lnkd.in/e8aHmFxc (GOATed) 𝟱 - 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁: lnkd.in/ej85NeZc 𝟲 - 𝗢𝗽𝗲𝗻𝗔𝗜: academy.openai.com 𝟳 - 𝗜𝗕𝗠: skillsbuild.org 𝟴 - 𝗔𝗪𝗦: skillbuilder.aws 𝟵 - 𝗗𝗲𝗲𝗽𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴𝗔𝗜: deeplearning.ai 𝟭𝟬 - 𝗛𝘂𝗴𝗴𝗶𝗻𝗴 𝗙𝗮𝗰𝗲: lnkd.in/eajVCrvv If you’re serious about learning AI, the biggest difference usually comes from consistency, not another course.

@financialit_net @BillHop Nice. You probably meant a different ramp.

@Ramp acquires UK & Sweden-based @Billhop, opening London & Stockholm offices to expand B2B payments & spend management across Europe. Read more: financialit.net/news/payments/… #Ramp #Billhop #B2B #FinancialIT

If you're an AI startup in India, renting processing power from the government to train your model costs about $0.7 per hour. The same hardware on Amazon Web Services costs $3.7. On Microsoft Azure, $6.6. The Indian government is subsidizing AI infrastructure at rates that would make most Western startups do a double-take. I read all 26 pages of the white paper this tweet links to. The numbers inside are wild. The IndiaAI Mission has a budget of about $1.2 billion over five years, approved in March 2024. Almost half of that, roughly $500 million, goes straight to building the processing power AI companies need to train their models. The original plan was to deploy 10,000 processors. By December 2025, they had 38,000 running. 3.8x what they promised. A government open call in January 2025 pulled 506 proposals. The four startups picked first were Sarvam AI, Soket AI, Gnani AI, and Gan AI. Eight more were added by September. India now has 12 separate teams building AI models, ranging from tiny ones for basic chatbots to massive ones rivaling those from the US and China. They cover language, voice, vision, medical diagnosis, material science, and even brain-computer interfaces. The one I keep coming back to is Sarvam AI. They raised $41 million from Lightspeed, Peak XV, and Khosla Ventures. In May 2025, they released a model built on top of a French AI system (Mistral Small) and customized for Indian languages. It got roasted online. Critics said it was a foreign model in Indian clothing. So they went back and built Sarvam-105B completely from scratch, using Indian hardware under the government mission. It outperformed China's DeepSeek-R1 on certain tests, even though it was a model six times larger. Both were released for anyone to download and use in March 2026. There's something else buried in the paper I haven't seen another country try at this scale. India is building a copyright system specifically for AI training data. Under a December 2025 government proposal, AI companies can train their models on any copyrighted content they can legally access, books, articles, music, anything. Creators cannot say no. But the moment an AI product makes money, royalties are collected by a centralized government body and distributed back to creators. Singapore allows AI companies to use content without payment. China requires strict consent before training. India is trying a middle path, and publishers are already calling it forced participation. Stanford's AI Vibrancy Index, which measures a country's overall AI strength across research, talent, infrastructure, and investment, ranked India third globally in 2025. Up from seventh in 2023. But the actual scores tell you how far the gap still is: US at 79, China at 37, India at 22. And India's $1.2 billion budget sits next to China's $47.5 billion semiconductor fund and Saudi Arabia's $100 billion Project Transcendence. India is currently spending 40x less than the frontrunners. This white paper is the most detailed public bet yet that smart infrastructure design can close that gap.

@HausAnalytics Nice - RamP!

@RamP Find the full list here: ramp.com/vendors/catego…

Haus just claimed the top spot in the new Marketing Measurement category on @Ramp Rate, which is the company’s public vendor adoption index for SaaS buyers and analysts. Based on real SaaS spend data from 50K+ companies, Ramp Rate highlights how quickly teams are adopting Haus to measure causal marketing impact. We’re proud that more teams trust us to solve their biggest measurement and decision-making challenges. The growth numbers are exciting, but even better are the hard-earned wins, creative solutions, and real partnerships our team and customers are building every day. Check out the full category and data at the link in the replies.

@tryvantageai Thanks for tagging.

Ramp adds AI-driven expense reviews to its Plus plan, now $15/user/month, as it hires for 19 enterprise-focused roles @ramp #CompetitiveIntel #Fintech #SaaS

@traviscannell @vast_ai Congratulations - RamP!

@vast_ai just made Ramp's trending vendor list for breakout growth in the "Agent Hosting" category. Oh and we also use @Ramp ourselves. Vendor and customer. The team earned this one. Grateful. ramp.com/velocity/top-s…

If you want to get started with Claude Cowork, look no further. I recorded this 1hr session on how to use Cowork. Powerful for knowledge work like Claude Code. But I also use it for image generation with Skills. Has a nice guide to go along with it.

I never believed in the AI unemployment stuff but we should start panicking… I just used Perplexity Computer and it one-shot an entire imaginary Acquired podcast episode about Ferrari Script, voices, captions, everything

@EvanKirstel Thanks for tagging. Perhaps you meant someone else.

The agentic enterprise isn’t coming… it’s already shipping. 🚀 “The Agentic List 2026” highlights how fast AI-native operators are moving from copilots to autonomous workflows across revenue, ops, HR, CX, and security. What stands out isn’t just the logos, it’s the shift from tools → teammates. From early innovators like @ActivelyAI @docyt @Humanly @JeevaAI @Simbian @Sybill @Synthflow to mid-stage builders like @AshbyHQ @blinkops @CapacityAI @DevRev @findem @GigaML @hightouchio @MavenAGI @SeekOut @UnifyAI @WisdomAI — and growth leaders including @AbnormalSecurity @ClayHQ @Darwinbox @DecagonAI @Glean @Mercor @Parloa @perplexity_ai @Ramp @SierraAI @TorqIO @ziphq — the signal is clear: AI is becoming infrastructure, not just interface. The real story? Agentic startups aren’t just adding features… they’re redefining how work gets done, how decisions are made, and how software participates alongside humans. Curious which of these will become the next platform giants. My bet: the winners will be the ones that combine deep data context, real governance, and outcomes that execs can actually measure. Who are you watching from this list? 👀 #AgenticAI #EnterpriseAI #FutureOfWork #AIStartups #TechInnovation

@supercut_video @PerpLEXIty Congratulations. Thanks for tagging.

We've been a bit quiet on releases lately... not slacking, just doing the boring (but important) stuff. Supercut is now SOC 2 & ISO 27001 compliant. ✅ To serve teams like @Perplexity and @Ramp at the level they deserve, we had to do the security work right. Audit passed. 🫡 Back to shipping. 🚀

@__asharma @robinhood @mercor_ai @databricks @boomsupersonic I'm not part of this. Perhaps you meant someone else.

@robinhood ventures I is interesting. Essentially creating an ETF of private companies that are traded publicly. @mercor_ai @ramp @databricks @boomsupersonic are part of the RVI launch. I can see this changing how companies are valued and how companies go public (if ever)

@fintechassoc @Forbes @mercury @withpersona @Plaid @raincards @stripe Wow!! - RamP!

Congrats to our members named to the @Forbes #Fintech50! 🎉 🏆 @Mercury 🏆 @withpersona 🏆 @Plaid 🏆 @raincards 🏆 @Ramp 🏆 @Stripe We're grateful to represent the companies driving financial access and opportunity for consumers and small businesses. 👏

@dbabbs @tryprofound @Reddit @figma @GammaApp @Expedia I do not plan to be there. Perhaps you meant some other ramp.

Zero Click by @tryprofound is back for TWO more sessions in 2026: 🌁 San Francisco: April 8th 🗽 New York: June 11th The world’s leading conference on AI Marketing and AI Search. Join leaders from brands like @reddit, @figma, @gammaapp, @expedia, and @ramp

🚨BREAKING: Someone compiled every CS course from MIT, Stanford, Harvard, CMU and Berkeley in one place. You can learn: - Algorithms, OS, Distributed Systems, ML, AI - Deep Learning, Computer Vision, NLP, LLMs - Security, Databases, Quantum Computing - 500+ courses with full video lectures 70.3K stars. 100% Opensource.

That tweet on RAG, MCP, LLMs, Agents, Fine-tuning & Quantization got way more attention than I expected. I want to teach these topics live, in an interactive way. • Completely FREE • Who this is for: Working professionals in tech • Prerequisites: None For folks who want to learn: Reply with "Interested" I'll plan to do it in batches, and share the details. Believe me, you'll learn it in the simplest way. And yes, I genuinely love teaching.

@yenkel @YingjunWu @StripeDev @stevekaliski @cognition @ScottWu46 Enjoying the thread! Perhaps you meant a different RamP!

@YingjunWu @RamP @StripeDev @stevekaliski bullish @cognition wonder you make of this @ScottWu46

following on @ramp’s steps, @StripeDev shares about their internal background dev agents main takeaways - slack as main entry point - importance of repeatable dev env - custom for their dev productivity tools question @stevekaliski: “Since MCP is a common language for all agents at Stripe, not just minions” if those mod servers hadn’t been around, would you have gone more for CLIs? looking forward to part 2

Wonderful to speak with my dear friend President Trump today. Delighted that Made in India products will now have a reduced tariff of 18%. Big thanks to President Trump on behalf of the 1.4 billion people of India for this wonderful announcement. When two large economies and the world’s largest democracies work together, it benefits our people and unlocks immense opportunities for mutually beneficial cooperation. President Trump’s leadership is vital for global peace, stability, and prosperity. India fully supports his efforts for peace. I look forward to working closely with him to take our partnership to unprecedented heights. @POTUS @realDonaldTrump

If you are struggling to keep up with the fast moving AI industry, here is the shortest roadmap that does the bare minimum in 2 weeks and actually works. No hype. No rabbit holes. Just enough to stop feeling lost. Week 1. Build the mental map Day 1. What AI actually is today AI today = Large Language Models + tools around them. Understand what an LLM is and why transformers matter. jalammar.github.io/illustrated-tr… youtube.com/watch?v=zjkBMF… Day 2. How models are trained Only learn the pipeline. Data → pretraining → fine tuning → inference. Ignore math. Focus on cost and scale. huggingface.co/blog/how-llms-… Day 3. The big model families Know who builds what and why people choose them. GPT, Claude, Gemini, LLaMA, Mistral. huggingface.co/blog/large-lan… Day 4. Prompting that actually matters Forget fancy prompts. Learn only this. Context. Constraints. Examples. promptingguide.ai Day 5. Tools and agents Understand function calling and agent loops. Most agents are just prompts plus retries. platform.openai.com/docs/guides/fu… latent.space/p/agents ⸻ Week 2. Become practically dangerous Day 6. APIs at a high level Know what an API call looks like, what tokens cost, and why latency matters. platform.openai.com/docs/api-refer… platform.openai.com/tokenizer Day 7. Retrieval Augmented Generation LLMs + your data ≠ training. Understand embeddings and vector search. pinecone.io/learn/retrieva… Day 8. Local vs hosted models Learn when people say run locally, on device, or edge AI. latent.space/p/local-llms Day 9. What breaks in production This is where real engineers live. Hallucinations, cost explosions, latency spikes. shreya-shankar.com/posts/llm-fail… Day 10. The AI product layer AI features are not AI products. Most startups die here. lennysnewsletter.com/p/how-to-build… Day 11. Job impact Ignore doomsday takes. Look at workflow changes. ben-evans.com/benedictevans/… Day 12. Read one serious blog Pick one and go deep. latent.space interconnects.ai ben-evans.com Day 13. Build one tiny thing A prompt workflow, internal tool, or small automation. Building collapses confusion. zapier.com/blog/ai-workfl… Day 14. Synthesize Write one page. What AI does well. What it fails at. Where cost and latency show up. Where you personally can use it. ⸻ You do not need to chase every model release. You need a stable mental model and light hands on exposure. Two weeks of this puts you ahead of most people posting about AI. Save this. Bookmark it. Come back to it.

Data centres are reshaping the global investment landscape. @UNCTAD report shows they captured over 1/5 of global greenfield investment in 2025. But investment remains concentrated in a few countries, led by France, the US and the Republic of Korea. ▶️ ow.ly/F1eK50Y1J2h