Introducing Sherpa: the most advanced fiction writing AI We accelerated from $250M in ARR to $500M because Sherpa helped increase content production by 1200% in 1 year Sherpa was trained on 5.5B hours of playtime with minute by minute dynamic retention data. 550K+ creators have produced 2.6M hours of... content annualised using it Pocket FM is like Netflix for audio-only dramas, with our own pool of one-person studios. 10% of eligible writers on Pocket FM make >$200K One blockbuster produced >$100M in revenue 3 writers have become millionaires in $1M by writing world-class fiction stories: 1. The Idea: Drop a 1-2 sentence concept. Sherpa interrogates it like a veteran editor on tension, stakes, and psychology 2. World & Characters: It builds out the complete lore, tone, and character psychologies 3. Sub-Plot planning: Breaks the premise into arcs, arcs into episodes, and episodes into scenes 4. Scene-by-Scene Generation: Outlines and drafts entire episodes, with you able to steer, rewrite, or override anytime 5. Editorial Review: Stress-tests every draft for pacing, engagement drop-offs, prose, and coherence before it locks 6. One-Tap Production: Pick a voice, convert to audio drama, and publish directly to Pocket FM’s millions of listeners 7. Global Scale & Monetization: Revenue-share on performance, with automatic localization so you earn across international markets Test Sherpa for free here: _____________________________________________ Generic LLMs fail at serialized fiction because they lack a long-horizon narrative reward function. Sherpa solves this through three core technical leaps: 1. Narrative World Model (State Tracking & Retrieval): Context windows degrade over long runs. Sherpa constructs an evolving semantic knowledge graph tracking character states, secrets, and plot dependencies. High-speed retrieval surfaces exact context on demand, maintaining zero continuity decay across hundreds of episodes 2. Hierarchical Story Planner: When writing a 500-episode story like Naruto, you need to plan 100s of sub plots. Rather than generating linearly, Sherpa decomposes narrative across discrete levels: season -> arc -> sequence -> episode -> scene. Rather than generating everything upfront, like a generic LLM, Sherpa uses progressive planning and dynamic replanning. As the story evolves, it identifies what changed, traces the downstream impact, and replans only the affected parts. 3. Prose Engine (Trained on series' retention data): LLMs write robotically, but serial fiction needs emotion, tension, pacing, and dialogue that sounds like real people. Sherpa's Prose Engine was designed specifically for storytelling. It was built on 1B+ tokens of Pocket's own stories, trained by learning from what listeners engage with, where they drop off, and what keeps them hooked. Feedback is taken from specialized evaluator models that measure every scene against a 40-item checklist. (Evaluator models were benchmarked against human reviewers and matched them 80–90% of the time.) _______________________________________________ Owning distribution and creation puts us in a very unique spot. More shows -> More data -> Sherpa becomes better -> more creator success -> more creators -> more shows Pocket FM has already seen one $100M IP. I believe Sherpa will soon lead to dozens of single-person studios creating billion-dollar shows. Most people are scared of AI but I think it'll unlock more human creativity, help creators earn more, and bring the next great IPs to life. This will create millions of jobs and new income streams.show more

Rohan Nayak

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