... launched a couple of projects that I'd love to share with this community: 1. LatentTracker.com a fan information hub for India's Got Latent (the hit comedy-reality show hosted by Samay Raina). It tracks Season 2 episodes, guest profiles, bonus content, and even includes interactive tools like countdowns, quizzes, and prediction games for fans. The latest bonus episode

... Every episode of the kids' series I make gets built on a Moto Edge 50 Fusion with a cracked screen and a volume button that stopped working months ago. No editing suite, no timeline software, no team. Grok generates the visuals, Claude helps me script and structure episodes

... just published a new SELF OS podcast episode exploring a question I think will become increasingly important: Should people benefit when their devices help power AI? Billions of phones, laptops, gaming PCs, and other devices sit idle for hours every day while demand for AI compute continues to grow. SELF OS is designed around a hybrid model where workloads can be routed between: Local SLMs Trusted personal devices Resonatia s distributed node network Larger cloud models The goal ... ... replace data centers or promise effortless income. It is to create infrastructure where users can voluntarily contribute unused compute, understand how their resources are being used, and participate in the value they help create. In the episode

... robotics datasets, we've found that quality-aware selection can preserve model performance while using substantially less training data than the full dataset or random selection. I recently had someone try it on their real robotics dataset, inspect the episodes Calibra flagged, and confirm that the demos were actually bad. That was probably the most valuable validation I've gotten so far. I'm now looking for robotics teams and researchers who are willing to try it on their ...

... host video podcasts with AI hosts, digital twins, natural voices, captions, and editing tools. The launch gave us strong validation, but it also showed us where we still need to improve. We re currently reviewing the onboarding experience, first-episode workflow, host realism, voice quality, and editing controls. I d especially love to hear from anyone who tried PodcastorAI: What part of the workflow felt unclear? What stopped you from finishing your first episode

... required to start. What we shipped: a hosted Streamable HTTP MCP server for cloud simulation. You paste one URL into your AI client, and it can simulate production infrastructure, inject failures, analyze costs, and run RL training episodes - all without provisioning anything real. The zero-friction angle is the lead story. No npx install, no Docker container, no local setup. Just: https://www.cloudworldmodel.ai/mcp Drop that into @Cursor (mcpServers config), @Windsurf , or @Claude for Desktop remote servers ...

... agents that deal with infrastructure decisions need a safe place to explore before touching production. Our x402-enabled API lets agents: Spin up a cloud simulation in one call Inject failures and observe recovery behavior Run reinforcement learning episodes to optimize cost and latency Get GPT-5 powered explanations of bottlenecks and scaling decisions No cloud accounts. No bills. No risk. The storefront listing includes the full OpenAPI spec, per-call pricing, and code samples so agents can start using ...

... asked to watch one Bluey episode. Auto-play had other plans. Forty-five minutes later it was unboxing videos, a bedtime meltdown, and me wondering why a video platform built for "watching what you want" had quietly turned into a platform that decides for you. That's the problem I set out to fix with NoSuggest , a free, open-source PWA that strips YouTube down to just the channels you choose. No recommendations, no Shorts, no auto-play, no trending ...

... tighter IaC integration is real, and the community articulated why: Ahmad's @blah_mad framing was precise before deploying an agent-generated IaC change, he wants a "handoff receipt": source sim run, changed resources, blast radius, rollback path. The episode history and final config are stable today. Blast radius as a named field is on the roadmap. The CI integration pattern came from the community, not from us. Jimmy Xu @jimmy_benhsu synthesized it: use Cloud World Model ... ... engineers talking in the comments arrived at it themselves and it's cleaner than anything we'd written. RL agent training opened a serious technical thread. We built a reinforcement learning API into the simulator, agents can run episodes

... overseas founder-interview channel under Alibaba, and we're looking for founders who've recently launched (or are about to) to feature in remote interviews which we then turn into episodes on our official social channels for exposure. Here's the idea: we want to help more people discover interesting startups, and give founders a low-effort way to get their project in front of a wider audience. How it works: It's fully remote, and no live call ...

... confident caption. "They knew." We checked it. Thoroughly. It is not true. Springfield Oracle exists precisely for moments like this. Our database tracks verified Simpsons predictions, cross-referenced against real-world events with documented evidence. There is no episode in which The Simpsons named, depicted, or meaningfully foreshadowed hantavirus as a global outbreak. There is no credible link between the HMPV content circulating online and the hantavirus now affecting the MV Hondius. HMPV and hantavirus are not the same virus ... ... genuine public health messaging at the exact moment people need clarity. The Oracle's Position We debunked this claim. The entry is live in our database, marked as False, with sourcing. If you've seen a specific clip or episode

... tracking application aiming to be shaped by obsessives like myself or just used by casual tv watchers to track where they are, where you can simply open the app, mark as watched and close the app or discuss each episode with superfans like yourself with a community trust based system where you can tag which episode

... Actionow targets the full pipeline of screenwriting, storyboard collaboration, and AIGC production with an agent-driven, self-hostable open-source workspace. The platform organizes every creative action around the content graph Script Episode Scene Storyboard Character / Prop / Style / Asset . Every entity is versioned and lineage-tracked; every interaction is observable, replayable, and reusable by agents. Open Source: https://github.com/actionow-ai/a... Audience Film, ad, and animation teams Connect writers, art, and production through agents; turn storyboards and assets into reusable inventory ...

... ones worth adding to the rotation. Right now my two favorites are Lenny's Podcast and Greg Isenberg's show . Both go deep" not surface-level takes, but real conversations with real depth. The kind where you finish an episode and immediately want to apply something to what you're working on. Lenny tends to go deep on product, growth, and what actually moves the needle for startups. Greg brings a sharp lens on trends, community, and the business ... ... that a lot of podcasts don't. So I'm curious: Which business or startup podcasts are you listening to right now? Any hidden gems that don't get enough attention? And is there a specific episode

... small team of developers and writers. Like many of you, we ve tried using standard AI tools to write scripts and build short dramas. The "honeymoon phase" is great, but by episode 10? The AI forgets the plot, character arcs break, and worst of all the output is an unshootable formatting nightmare. You end up spending more time writing prompts and fixing AI s continuity errors than actually creating. So, we decided to build a solution to scratch ... ... generator needs. 3. Hierarchical Memory (STM / MTM / LTM): A closed-loop system for long-form (1M+ words). It tracks Short-Term scene dynamics, Mid-Term chapter arcs, and Long-Term lore. Our proprietary model actually remembers your setups from episode

... think about workflow optimization probably more than is healthy. Here's the batching approach I've seen work best for weekly podcast production. The problem with "one episode at a time": You context-switch constantly. Monday you're writing, Tuesday you're recording, Wednesday you're editing, Thursday you're publishing. Every day is a different tool, a different mindset. You never build momentum. The assembly line approach: Pick one day per task. Do that task for multiple episodes

... Frqncy (pronounced frequency) solves a problem most podcast listeners know but rarely talk about: the loneliness of shared context. You finish an episode that sticks with you, but there s no one to discuss it with. Frqncy connects you with another listener who s in the same place, one-on-one, for a meaningful conversation. - Only three convos a day, resets at midnight to keep conversations focused - Discover conversation outside of your usual circles - Privacy and security built in from ... ... start Podcasts are deeply personal, immersive, and thought-provoking but the discussion often stops at the end of the episode

... founder of Munch. I built this because I kept watching creators spend hours turning one video into posts. You paste a YouTube or Vimeo URL Munch extracts the transcript using 5 fallback strategies (so it actually works on videos competitors choke on) Claude AI writes 8 complete, platform-ready pieces in ~60 seconds. No file uploads. No per-action credits. One munch = everything. PH exclusive: Your first munch is completely free, no card needed. Just sign up at munch.video ... ... multiple extraction strategies in sequence before giving up. Users rarely see failures. When you do hit one, you can paste the transcript directly and keep going. Vimeo and article URLs have their own dedicated extractors. Podcast RSS feeds parse episode

... multiple extraction strategies in sequence before giving up. Users rarely see failures. When you do hit one, you can paste the transcript directly and keep going. Vimeo and article URLs have their own dedicated extractors. Podcast RSS feeds parse episode show notes from the feed pick an episode

... brings thoughtful discussions on the latest AI headlines, emerging technologies and the trends transforming business and society. Join us each week as we unpack the stories behind the technology and reflect on what they mean for the future. New episodes every Thursday 4:30 PM. Available on YouTube & Spotify. The Tech Lounge: Think With AI - Inside The Era. Follow the show on Spotify to stay updated: https://open.spotify.com/show/2z... Subscribe to the Youtube channel and turn on notifications ... ... never miss our new episode

... Product Hunt, Viral Simpsons prediction videos have no sources. Half the clips are AI-generated fakes, and nobody built the actual database until now. Springfield Oracle tracks every prediction with verified episode references, real event citations, and honest fact-checks. The world so far has been relentless, and the Simpsons wrote all of it. Springfield Oracle tells you which claims are real. And which aren't. I built Springfield Oracle because I was tired of the same cycle. Something happens ... ... world. Someone posts a Simpsons clip. It goes viral. 10 million views. No episode

... According to @RevenueCat 's State of Subscription Apps 2026 report, " hard paywalls convert 5x better than freemium, but with significantly wider variance." Day 35 download-to-paid, freemium vs. hard paywall Does access method impact download-to-paid conversion within 35 days? Quoting the report: Median D35 conversion sits at 10.7% for hard paywalls. Freemium is 2.1%. That gap alone should make you pause. But the more revealing part is the distribution. Hard paywall top decile apps approach 40% conversion ... ... what about it? I mean, if you're not a business, you probably don't need to worry about this topic. Comment from Chris Messina(@chrismessina): @andrew_g_stewart  actually, there was a useful discussion on this episode

... built Story Miner ( novelcat.io ) a web app that analyzes novels and screenplays using a hybrid of deterministic NLP and LLM-powered narrative analysis. What it does: Verdict Strengths, weaknesses, and actionable takeaways - Engagement Map Narrative structure + engagement timeline across episodes - Character Craft Relationship graphs, emotion distribution, co-appearance analysis - Weak Spots Coherence issues, low-engagement episodes

... just launched a new series called Build It Now , where builders take a real idea and ship it live inside CreateOS. No staged demos, no pre-written code; just the build, start to finish. Episode 1 follows Kalash Vasaniya as he builds Justref: a platform where businesses create affiliate programs and participants join, share referral links, and earn based on conversions. He leveraged the following CreateOS features: Backend services Database management Messaging queues Scheduled jobs Version one is complete ... ... being refined, with public launch on CreateOS coming in the next few weeks. Each episode

... This will make discovery and trend tracking much easier. 5. Introducing a Prediction Confidence Meter One of the most requested features. We re adding a confidence meter to every prediction that indicates how strong the connection is between the episode and the real-world event based on the fact-checked evidence we have. For pending predictions, we ll also introduce a likelihood percentage to indicate how plausible it is that the prediction could actually happen in the future. The goal ...