Niraj (@nirajshah) header
Niraj (@nirajshah) profile picture

Co-Founder & CTO Twins AI @twinsainet - AI Voice Assistant - Close deals faster with AI Agents.

New York
Joined March 2007
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some may call it pandering . maybe lol. but the nepali vote is on somebody’s radar now and I’m pretty happy about it. Happy Tihar!
Tihar ko hardik shubhakamana to our Nepali neighbors! Tihar reminds us to honor every bond that sustains us, from the animals who share our lives to the siblings who protect us. May it bring you happiness, prosperity, and peace.
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This looks pretty awesome. Very Apple like! Great job!
BREAKING: Trump launches <America.gov> as a “single entry point” for federal services, using Gemini and Grok to turn roughly 29,000 government websites into one AI powered interface.
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It’s 2026. Voice AI can negotiate, sell, troubleshoot and hold a natural conversation.Then you call @Verizon and get trapped in one of the worst automated support systems imaginable. @VerizonSupport how does a company this big still ship an experience this bad?
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Apparently everyone on X is sending or receiving money. Just wanted to report that I have successfully received $0. My account remains financially independent.
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Is there a muse grokbot like product from google ?
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AI coding is going to create a generation of startups that can build everything and explain nothing.
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Surprise win !
BREAKING: Exit polls show that Putin’s United Russia party has won the Russian “election” United Russia: 52.8% The Communist Party: 14.8% LDPR (national-chauvinists): 9.9% New People (liberal spoiling party): 8.6% A Just Russia (Democratic Socialists) 5.5% The Yabloko party was barred from the election by Russia’s Supreme Court after they made it public that they are against the invasion of Ukraine and started skyrocketing in the polls. Other Russians wanted to vote for Nemtsov or Navalny but couldn’t for obvious reasons.
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Wild!
JUST IN: Chinese robots have begun building other Chinese robots, as a new factory capable of producing 1 humanoid every 10 minutes comes online.
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This seems a wild!
JUST IN: Startup builds autonomous drone system using GPT-6 Astra to locate & track a specific person from a single reference image.
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Great read! may be the best example yet of what happens when AI, distribution, and feedback compound together.
We grew from ~0 to $500M ARR, adding $250M last year alone while being EBITDA profitable. 1,300-word post on every growth tactic that worked for us: 1. What got us from 0-$400M ARR in the US works in every country. 2. Retention and Monetisation Hacks. 3. Localization > Translation. 4. Experiment with $1M internal seed checks. 5. Pivoting to only AI content production unlocked 100% ARR growth. Pocket FM is like Netflix for audio-only dramas, with our own pool of one-person studios. 1. Acquisition Playbook for 0-$10M ARR in any country in 6 months We run a 90 sec video trailer of an audio drama as an Ad and ask users to download the app if they're interested in the rest of the story. Our core insight after spending >$100M on acquisition is: If the clickthrough rate (CTR) for an ad goes from 2% to 2.25%, our customer acquisition cost (CAC) decreases by ~ 30%. We remodelled our system around this insight and built an AI-first 2.25% CTR ad manufacturing machine that works in every country. For every new country, we take our hit shows -> use LLMs to extract and most intriguing moments -> Write a 5-min script combining all the best parts. The first 60 seconds has to have a hook every 5 seconds and needs to end with a crazy cliffhanger to force a download mid-scroll. If a marketing video is not hitting our benchmarks (2.5% CTR and 55% 3-second through-play), a creative director gets involved to change the hook or cliffhanger to get the numbers there. AI lets us make 1,000 Ads per show, and in total we do ~17.5k Ads per month. When a business creating scales from 1k to 10k Ads, the normal thing is for CAC to skyrocket. But with what I just shared, we 7-8x'd our User Acquisition budget without increasing our CAC materially. It took us 8 months to figure this out, but then the timeline from 0-$10M in every country got shorter and shorter: US revenue grew to $25M in 19 months. (US is now 78% of total) Germany to 21M in 11 months. France to $10M in 3 months. 2. Retention and Monetisation Hacks. We knew we wanted to create an audio entertainment platform, but there was no standard format. For the first 2-3 years, we tried 10 different formats before landing on the winner. After we got it right with audio drama (8-12min chapters, written for mobile fiction, serialized, episodes have strong hooks and end on cliffhangers), avg daily streaming time went from ~25mins to 150+. Audio drama made us realize that Pocket FM was creating a whole new medium. There was no playbook for anything that we were doing. Everything had to be thought & built from scratch. This is what we did for each major bullet: - Monetization: Users have some free daily minutes to listen; then it's pay per episode. We also added the option for users to unlock episodes by watching ads, which is doing extremely well. Ads scaled from zero to a ~$90M run rate in 12 months. - Engagement & production: You don't become obsessed with an app you open once a week. To have users engage daily, we make the next episode free every day. Also helps them build the habit. - Discovery. Huge problem because people consuming Pocket FM enter the app, tap the show, and lock the screen. We fixed it by doing "playlists" of episodes. Once users's free minutes on a show are done, we ask users if they want to pay. If they say no, we play a new show, one where they haven't used their free mins. And we stitch episodes of different shows together that way, creating natural discovery. 3. Localization > translation. 78% of our revenue is still concentrated in the US. Localisation is fixing this: You might write a show for a Spanish audience where language, jokes, folklore, have a certain flavor; if you merely translate the show for, say, a Norwegian audience, that color is lost and hurts the show in the Norway. Listeners would relate more if the show was written by a Norwegian. That's why, instead of translating, we localize shows to different regions. We use AI to take the spine of stories and adapt their whole cultural layer to the other country. The results: a US show that was localized for a German audience had 50% higher retention than the translated version. Localization + our user acquisition playbook led to: - $10M+ ARR in France within 3 months - $21M+ ARR in Germany within 11 months. And this expands writers' addressable market. We get messages of writers thrilled to have revenue coming from the US, India, EU, LatAm, without them doing much incremental work. 4. Experiment. We give $1M checks to new internal initiatives, and the team has 12-18 months to prove their thesis. If they prove it, we double down. This is how Pocket Saga came about, our AI video microdrama app. It's an AI video equivalent of Pocket FM. Same shows and structure, but as a vertical 2-min mobile video series. We launched it two months ago and it's at ~$15M ARR. Pocket's broader thesis is to help creators tell their stories to as many people as possible. Start with audio drama -> multiple languages or localize to diff countries -> microdrama -> more formats like movies, TV shows, and games. Best of all is that writers get revenue streams not only from countries they wouldn't have tapped into, but also from formats they wouldn't have thought possible. 5. Pivoting to only AI content production unlocked 100% ARR growth. In mid-2024, we pivoted to only AI content production. Our growth took a very direct hit. Pocket was already at $200M ARR, growing 50% YoY, and we flatlined for a whole semester. Six months later, the business exploded. After the switch, we went from ~25k hours of content produced per year to over 2.5M hours, which are also higher quality. Because AI orchestrates the writing and more data is fed into it, more blockbusters come out. Over 90 titles have $1M+ in lifetime earnings and 13 crossed $10M. Quality control is done with LLM as a judge, and LLMs are quite tough. Results are very encouraging: - 12-month revenue retention went from 44% to 76%. - In the past year, we added $250M in net new ARR. __________________________________ Pocket Entertainment (Pocket FM + Pocket Saga) has become the largest AI entertainment platform. We have the largest storytelling catalog with 770,000 titles, 550k creators, and 5.5B hours of playtime with minute by minute retention & engagement data. We are using all of this data to improve every aspect of our business. Our Bet: In the next 3 years we will be able to produce Naruto-like series for $1000. Netflix has to spend $17B to find 100 Blockbusters per year. What happens when you can produce 1M high quality shows for $1B? The streaming wars caused a $300B reallocation of market cap. The AI entertainment wars may be a $1T+ reshuffling of market cap. We are at a unique spot. Unlike other AI creator tools like Runway or Midjourney, we own both the supply and demand side of AI content. We've attracted over 550,000 writers who are producing an annualized 2.5M hours of content every year. This pairs with 137B+ minutes streamed. Because of this, growth is accelerating as we scale further. We have multiple S-curves inflecting at the same time: - AI produces better and more ads -> scale faster in new countries - ⁠Writers + AI produce more shows -> more blockbusters - ⁠Localisation -> more reach per blockbuster - ⁠Audio to video format expansion -> larger TAM -> more creators Every aspect of our business is designed to improve another, and everything is aligned so that the number of blockbusters continues to rise. If you're interested in building at the intersection of ai, tech and entertainment, DM me.
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this is why i am a big fan of community notes!
BREAKING NEWS🚨: Iran shoots down an F-15 with a man on a flying carpet 😱😱
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GTM is going to need its own CI/CD loop. 500 calls → find failure patterns → generate prompt diff → manager approves → deploy to 10% → measure → roll forward/revert. We added MCP to @TwinsAInet so Claude/Codex can start doing this against real call outcomes. Prompts are becoming production artifacts. We should probably start treating them that way.
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Personal AI assistants are quickly getting enough tools to do almost anything. The interesting problem now is permission. Not OAuth permission. Judgment permission. When can the agent send the email, make the purchase or change the calendar without asking me? That boundary probably needs to be learned per user, per action, over time.
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Really enjoyed this conversation. This take especially stuck with me: “An AI that does 100% of the job feels categorically different from one that gets you 90% there” Thank you both!
Really enjoyed this conversation. Thanks for having me, @lennysan!
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This is a great idea!
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good!
Instinct + 1Password 32% of Instinct users already securely share their credentials with Instinct through our Vault. Today, we’re excited to announce our partnership with @1Password . Together, we are working with 1Password to roll out a product integration that enables users to seamlessly and securely share their credentials with Instinct. Our users already use Instinct’s Vault to: - Log in to loyalty accounts to book flights and hotels with points - Manage streaming, software, and other recurring subscription accounts - Book or cancel restaurant, fitness, and event reservations  - Sign in to healthcare portals to schedule and cancel appointments  - Easy access to tax, payroll, benefits, and expense management services Together with 1Password, we’re working toward a future where people can share their credentials without compromising on security or control. We’ll be rolling this out across our early access group. If you’re not already in the platform, join at app.instinct.com/login.
 More details about 1Password here:
1password.com/
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Massive thanks! @JensenHuang @NVIDIAAI
**१ करोड डलरको सहयोग. हार्दिक आभार श्री जेन्सन हवाङ, प्रमुख कार्यकारी अधिकृत, एनभिडिया। यस अभूतपूर्व सहयोगसँगै प्रधानमन्त्री दैवीप्रकोप उद्धार कोषमा रु. १० अर्ब भन्दा बढी रकम संकलन भएको छ।
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Tried something with WebMCP today. I built a page that exposes the buying process as tools: get_pricing check_stack_fit get_security_docs ask_the_seller start_meeting_booking When a buyer’s agent visits, it can use these tools to evaluate the product, answer its own questions, and decide whether it’s worth taking the next step. We’ve spent years building websites for buyers. Now their agents are showing up too.
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The scale of the devastation in Nepal is difficult to comprehend. @sama, I hope you and @OpenAI will consider supporting the relief and rebuilding efforts. Your technology, resources and reach could make a meaningful difference at a time when Nepal needs help most. 🇳🇵 Thanks Pukar for all your efforts!
Would love your help @sama in helping Nepal 🇳🇵 with the rebuild efforts after this extinction level event. I understand @OpenAI’s mission is to ensure AGI benefits ALL of humanity. It would mean a lot to Nepal and American 🇺🇸 efforts to accelerate the relief and recovery process for Nepal 🇳🇵. Thank you 🙏 ❤️‍🩹 Happy to coordinate with your team directly. I am based out of SF 🌁.
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Claude Code is already getting pretty good at subagents, context and handoffs. But what happens when Agent A changes an API or its interpretation of the spec while Agent B is already building against the old one? How does B know its context is now stale? Feels like we're going to need some form of state versioning or invalidation between agents?
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