‘Something Big Is Happening’ + A.I. Rocks the Romance Novel Industry + One Good Thing
Episode
60 min
Read time
3 min
Topics
Relationships, Investing, Fundraising & VC
AI-Generated Summary
Key Takeaways
- ✓SaaS Business Model Disruption: Software companies like Salesforce, Workday, and Monday.com experienced significant stock declines as investors recognize AI enables businesses to build custom tools internally rather than purchasing per-seat licenses. Outcome-based pricing models emerge as alternatives, exemplified by Sierra's customer service platform charging per resolved inquiry rather than per user seat, fundamentally threatening traditional enterprise software revenue structures.
- ✓AI Coding Acceleration Metrics: Claude Code currently authors 4% of all public GitHub commits, with projections reaching 20%+ by 2026. OpenAI's GPT 5.3 Codex represents the first model instrumental in creating itself, enabling recursive self-improvement. Engineers report coding work is approximately 90% automated currently, with full automation predicted within twelve months, driven by AI's relentless 24/7 operation without fatigue or morale decline.
- ✓Romance Novel Production Pipeline: Author Coral Hart created 21 pen names and published 200+ romance novels in one year using AI, generating six-figure income through volume-based strategy. Effective workflow requires detailed prompting with specific subgenres, blocking overused phrases like "turgid manhood," and instructing models to "slow down" since they rush to scene conclusions. Claude writes elegant prose but fails at banter; ChatGPT frequently refuses requests; Grok accepts any prompt.
- ✓AI Content Quality Limitations: Romance novels generated by AI lack emotional nuance and character depth despite following genre tropes correctly. Models struggle with pacing—converting enemies-to-lovers arcs into immediate romance within one chapter. Writers must provide extensive guidance including unusual settings (winery fermentation tanks, stalled ski lifts) and detailed inventories of non-standard romantic scenarios to avoid generic bedroom/shower scenes and clichéd language patterns.
- ✓Political and Labor Market Response: Washington DC policymakers express heightened concern about AI's workforce impact as unemployment remains near record lows. Bernie Sanders proposes legislation for data center moratoriums. The comparison to February 2020 pandemic awareness suggests exponential adoption curves that most people haven't recognized yet. Constituents need to engage lawmakers about job displacement scenarios and demand government responses beyond industry reassurances about job creation.
What It Covers
Hard Fork examines AI's accelerating impact across industries, from software company stock crashes to automated romance novel production. The episode explores why Washington DC is alarmed about AI capabilities, how coding tools like Claude are automating engineering work, and how romance authors now produce 200+ books annually using AI assistance.
Key Questions Answered
- •SaaS Business Model Disruption: Software companies like Salesforce, Workday, and Monday.com experienced significant stock declines as investors recognize AI enables businesses to build custom tools internally rather than purchasing per-seat licenses. Outcome-based pricing models emerge as alternatives, exemplified by Sierra's customer service platform charging per resolved inquiry rather than per user seat, fundamentally threatening traditional enterprise software revenue structures.
- •AI Coding Acceleration Metrics: Claude Code currently authors 4% of all public GitHub commits, with projections reaching 20%+ by 2026. OpenAI's GPT 5.3 Codex represents the first model instrumental in creating itself, enabling recursive self-improvement. Engineers report coding work is approximately 90% automated currently, with full automation predicted within twelve months, driven by AI's relentless 24/7 operation without fatigue or morale decline.
- •Romance Novel Production Pipeline: Author Coral Hart created 21 pen names and published 200+ romance novels in one year using AI, generating six-figure income through volume-based strategy. Effective workflow requires detailed prompting with specific subgenres, blocking overused phrases like "turgid manhood," and instructing models to "slow down" since they rush to scene conclusions. Claude writes elegant prose but fails at banter; ChatGPT frequently refuses requests; Grok accepts any prompt.
- •AI Content Quality Limitations: Romance novels generated by AI lack emotional nuance and character depth despite following genre tropes correctly. Models struggle with pacing—converting enemies-to-lovers arcs into immediate romance within one chapter. Writers must provide extensive guidance including unusual settings (winery fermentation tanks, stalled ski lifts) and detailed inventories of non-standard romantic scenarios to avoid generic bedroom/shower scenes and clichéd language patterns.
- •Political and Labor Market Response: Washington DC policymakers express heightened concern about AI's workforce impact as unemployment remains near record lows. Bernie Sanders proposes legislation for data center moratoriums. The comparison to February 2020 pandemic awareness suggests exponential adoption curves that most people haven't recognized yet. Constituents need to engage lawmakers about job displacement scenarios and demand government responses beyond industry reassurances about job creation.
- •Spotify Prompted Playlists Feature: Premium subscribers in US, Canada, and New Zealand access AI-powered playlist generation using natural language requests and personal listening history. Users can request songs played 20+ times but not recently, opposite-taste recommendations, country-specific hits, or abstract concepts. The system employs "world knowledge" beyond song metadata, enabling complex queries like identifying songs whose titles don't appear in lyrics, with automatic daily updates available.
Notable Moment
Google researchers developed Perch 2.0, a bioacoustics model trained exclusively on birdsong that successfully classifies whale, dolphin, and orca vocalizations underwater. This transfer learning breakthrough demonstrates that making models better at one animal communication task improves performance on related species, outperforming models trained specifically on marine mammal sounds and advancing cetacean translation research.
Episode Transcript
Well, Kevin, did you see this? Elon Musk told employees at XAI that the company needs a factory on the moon to build AI satellites and a massive catapult to launch them into space. Yes. This is his new pivot from Mars. He's no longer interested in Mars, as he was all those years. Now he's gone to the moon. This Looney Tunes ass company. I swear to god. Elon Musk, I have a message for you. If Bugs Bunny ever shows up and tells you to climb into that catapult, do not trust him. Okay? That is a rascally rabbit, and and you you might find yourself in space, my friend. He's gonna launch you from the moon catapult. You know what? That might be the way I wanna go out, honestly, is just have a nice long career in journalism and then put me in the moon catapult. I'm I'm ready. I'm Kevin Roose, a tech columnist at the New York Times. I'm Casey Noon from Platformer. And this is Hard Fork. This week, labor pains, why AI is causing freakouts from the markets to the workforce. Then the Times' Alexander Alter on how the romance novel industry is being overtaken by AI authors. And finally, it's time for our new segment, one good thing. It replaces our previous segment, a lot of terrible things. Well, Kevin, welcome back from our nation's capital. Yes. I was in DC very briefly this week, there for some book meetings, and it was very cold. But the bigger observation is that Washington DC is, like, freaking out about AI. Is that right? Yes. So everywhere I went, every meeting I had, people were sort of asking me, is this stuff real? Is it happening? Are we in the takeoff? Is the singularity approaching? And it does feel like the sort of political salience of AI has gotten much, much higher just in the past couple of weeks. Well, why do you think that is? So there are a lot of reasons for that. I think one of them is that I think there's been a lot of people waking up to the new agentic coding capabilities of these models. We've obviously talked about that on the show, Cloud Code, etcetera. I think that is starting to kind of make its way out into the world. There's also the stock market stuff, that's been going on with a lot of the software stocks that are falling because of the threat of AI. And then I think there's just sort of this ambient cultural vibe shift happening that has led to a lot of people in my life who are not, like, AI bubble people, texting me and saying, hey. Is this really something I should be worried about? Is my job at risk here? And, so today, I think we should talk about this because among other reasons, there is this viral essay, that I've been sent now no fewer than three …
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Books, tools, and gear mentioned in this episode
SignalCast may earn commission on purchases via these links. As an Amazon Associate, SignalCast earns from qualifying purchases.
Tools
by Google
“Google researchers developed Perch 2.0, a bioacoustics model trained exclusively on birdsong that successfully classifies whale, dolphin, and orca vocalizations underwater.”
“ChatGPT frequently refuses requests; Grok accepts any prompt.”
by Anthropic
“Claude Code currently authors 4% of all public GitHub commits, with projections reaching 20%+ by 2026.”
by OpenAI
“OpenAI's GPT 5.3 Codex represents the first model instrumental in creating itself, enabling recursive self-improvement.”
by Spotify
“Spotify Prompted Playlists Feature: Premium subscribers in US, Canada, and New Zealand access AI-powered playlist generation using natural language requests and personal listening history.”
Products
company
“Software companies like Salesforce, Workday, and Monday.com experienced significant stock declines”
“Software companies like Salesforce, Workday, and Monday.com experienced significant stock declines”
“Software companies like Salesforce, Workday, and Monday.com experienced significant stock declines”
More from Hard Fork
We summarize every new episode. Want them in your inbox?
The A.I. Mob That Attacked Hugging Face + METR’s Ajeya Cotra
Meta Shifts the Blame + Do Data Center Bans Work? + The Final HatGPT
OpenAI’s Two-Week Pause + Jill Lepore on the Threat of the “Artificial State” + Train of Thought
Zuckerberg’s Anti-Doom Fantasy + Finally an A.I. Detector That Works + A.I. Math
The White House’s Secret A.I. Rules + The State of Model Alignment With METR’s Chris Painter + The Final Hot Mess Express
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