# Jake Handy: full site text > Plain-text dump of public pages on https://jakehandy.com. Each section is delimited by a level-2 heading containing the page title and canonical URL. Author: Jake Handy · Staff PM at The MLC · Handy AI newsletter · Nashville, TN For the curated URL index, see https://jakehandy.com/llms.txt. For crawl metadata, see https://jakehandy.com/sitemap.xml. ## Jake on AI URL: https://jakehandy.com/ai Date: 2026-06-21 Summary: My thoughts on the AI industry as it evolves. My thoughts on the AI industry as it evolves. Published here and weekly(ish) on [my Substack](https://handyai.substack.com). This page collects my editorials: the opinion pieces, not the weekly news roundups or model drops. New editorials show up here automatically when they're published to the [Handy AI newsletter](https://handyai.substack.com). --- ## AI music models URL: https://jakehandy.com/ai-music-models Date: 2026-04-23 Summary: Every AI music model and provider, mapped. My work at Vobile (Pex) involves building the world's greatest AI music detector, which requires keeping track of every AI music model out there. This page is a living document of all the music-generation models that have been, are, and will be. This catalog tracks 87 AI music-generation models across 23 providers (15 open-weight, 72 closed-weight). ### Suno - Suno v2 · Sep 2023 · closed weights, https://help.suno.com/en/articles/5782721 - Suno v3 · Apr 2024 · closed weights, https://suno.com/blog/v3 - Suno v3.5 · Jun 2024 · closed weights, https://aicreators.tools/model/audio/81 - Suno v4 · Nov 2024 · closed weights, https://suno.com/blog/v4 - Suno v4.5 · May 2025 · closed weights, https://suno.com/blog/introducing-v4-5 - Suno v4.5+ · Jul 2025 · closed weights, https://medium.com/@creativeaininja/suno-v4-5-the-ai-music-revolution-just-got-personal-cf27c48ffd98 - Suno v5 · Sep 2025 · closed weights, https://help.suno.com/en/articles/8105153 - Suno v5.5 · Mar 2026 · closed weights, https://suno.com/blog/v5-5 - Suno v6 · Sep 2026 · closed weights, https://suno.com/blog/introducing-v6 - Suno v6-wild · Sep 2026 · closed weights, https://suno.com/blog/introducing-v6 - Suno v6-mini · Sep 2026 · closed weights, https://suno.com/blog/introducing-v6 ### Google - MusicLM · Jan 2023 · closed weights, https://musiclm.com/ - Lyria (Dream Track) · Nov 2023 · closed weights, https://blog.youtube/inside-youtube/ai-and-music-experiment/ - Lyria 2 · Apr 2025 · closed weights, https://medium.com/vertical-bar-media/google-launches-lyria-2-for-advanced-music-generation-vbm-75ee668b9101 - Lyria 3 Clip · Feb 2026 · closed weights, https://deepmind.google/models/lyria/ - Lyria 3 Pro · Mar 2026 · closed weights, https://blog.google/innovation-and-ai/technology/ai/lyria-3-pro/ - Lyria 3.5 · Jul 2026 · closed weights, https://blog.google/innovation-and-ai/models-and-research/google-labs/lyria-3-5/ - Riffusion v1 · Oct 2022 · open weights, https://huggingface.co/riffusion/riffusion-model-v1 - FUZZ-0.7 (Riffusion) · Jan 2025 · closed weights, https://musically.com/2025/01/31/ai-music-startup-riffusion-launches-its-service-in-public-beta/ - FUZZ-0.8 (Riffusion) · Feb 2025 · closed weights, https://www.reddit.com/r/udiomusic/comments/1ihc7v6/riffusion_have_released_fuzz08_with_more_natural/ - FUZZ-1.0 (Riffusion) · Apr 2025 · closed weights, https://futuretools.io/tools/riffusion - FUZZ-1.0 Pro (Riffusion) · Apr 2025 · closed weights, https://futuretools.io/tools/riffusion - FUZZ-1.1 Pro (Riffusion) · Jun 2025 · closed weights, https://queencaffeineai.com/post/790376528452222976/riffusion-11-pro-review-is-fuzz-11-the-best-ai - FUZZ-2.0 (Producer.ai) · Jul 2025 · closed weights, https://medium.com/@CherryZhouTech/producer-ai-launches-fuzz-2-0-powered-conversational-music-creation-tool-5645f822a363 ### OpenAI - MuseNet · Apr 2019 · closed weights, https://openai.com/index/musenet/ - Jukebox · Apr 2020 · open weights, https://openai.com/index/jukebox/ ### Meta - MusicGen · Jun 2023 · open weights, https://audiocraft.metademolab.com/musicgen.html - MusicGen Stereo · Jun 2023 · open weights, https://audiocraft.metademolab.com/musicgen.html ### Udio - Udio v1 · Apr 2024 · closed weights, https://www.prnewswire.com/news-releases/former-google-deepmind-researchers-assemble-luminaries-across-music-and-tech-to-launch-udio-a-new-ai-powered-app-that-allows-anyone-to-create-extraordinary-music-in-an-instant-302113166.html - Udio v1.5 · Jul 2024 · closed weights, https://www.udio.com/blog/introducing-v1-5 - Udio v1.5 Allegro · Mar 2025 · closed weights, https://www.reddit.com/r/udiomusic/comments/1jef4ky/introducing_v15_allegro_featuring_substantially/ ### Stability AI - Stable Audio · Sep 2023 · closed weights, https://ed.newtonrex.com/blog/stable-audio-launch - Stable Audio 2.0 · Apr 2024 · closed weights, https://stability.ai/news-updates/stable-audio-2-0 - Stable Audio 2.5 · Sep 2025 · closed weights, https://stability.ai/news-updates/stability-ai-introduces-stable-audio-25-the-first-audio-model-built-for-enterprise-sound-production-at-scale - Stable Audio Open · Jul 2024 · open weights, https://stability.ai/news-updates/introducing-stable-audio-open - Stable Audio Open Small · May 2025 · open weights, https://huggingface.co/stabilityai/stable-audio-open-small - Stable Audio 3.0 Small · May 2026 · open weights, https://stability.ai/news-updates/meet-stable-audio-3-the-model-family-built-for-artistic-experimentation-with-open-weight-models - Stable Audio 3.0 Medium · May 2026 · open weights, https://stability.ai/news-updates/meet-stable-audio-3-the-model-family-built-for-artistic-experimentation-with-open-weight-models - Stable Audio 3.0 Large · May 2026 · closed weights, https://stability.ai/news-updates/meet-stable-audio-3-the-model-family-built-for-artistic-experimentation-with-open-weight-models ### ElevenLabs - Music v2 · May 2026 · closed weights, https://elevenlabs.io/blog/introducing-music-v2 - Music v1 · Aug 2025 · closed weights, https://elevenlabs.io/blog/eleven-music-is-here ### Minimax - Hailuo Music 1.0 · Aug 2024 · closed weights, https://www.minimax.io/news/music-01 - Hailuo Music 1.5 · Sep 2025 · closed weights, https://www.minimax.io/news/minimax-music-15 - Hailuo Music 2.0 · Oct 2025 · closed weights, https://www.minimax.io/news/minimax-music-20 - Hailuo Music 2.5 · Jan 2026 · closed weights, https://www.minimax.io/audio/introducing/music-2-5/ - Hailuo Music 2.5+ · Mar 2026 · closed weights, https://www.minimax.io/news/music-25-unlock-instrumental-music - Hailuo Music 2.6 · Apr 2026 · closed weights, https://www.minimax.io/news/music-26 - Hailuo Music 3.0 · Jul 2026 · open weights, https://www.minimax.io/blog/minimax-music-3-0-next-generation-open-weights-production-ready-versatile-music-model ### Mureka - Mureka v2 · Jul 2024 · closed weights, https://www.mureka.ai/ - Mureka v5.5 · Dec 2024 · closed weights, https://www.facebook.com/61567153665824/posts/murekas-brand-new-self-developed-v55-music-model-is-coming-soon/122124779060571788/ - Mureka v6 (O1) · Mar 2025 · closed weights, https://x.com/Mureka_AI/status/1904806339920224468 - Mureka v7 · Jul 2025 · closed weights, https://www.reddit.com/r/aicuriosity/comments/1m7bc08/mureka_v7_update_a_leap_in_ai_music_creation/ - Mureka v7.5 · Sep 2025 · closed weights, https://www.howtogeek.com/mureka-latest-version-first-fully-ai-generated-song/ - Mureka v7.6 · Nov 2025 · closed weights, https://www.reddit.com/r/aicuriosity/comments/1p8rs7d/mureka_ai_o2_and_v76_major_update_released_new/ - Mureka O2 · Nov 2025 · closed weights, https://www.reddit.com/r/aicuriosity/comments/1p8rs7d/mureka_ai_o2_and_v76_major_update_released_new/ - Mureka v8 · Jan 2026 · closed weights, https://x.com/Mureka_AI/status/2016544920283365831 - Mureka v9 · Mar 2026 · closed weights, https://x.com/Mureka_AI/status/2037558834521338362 ### ByteDance - Seedmusic · Sep 2024 · closed weights, https://seed.bytedance.com/en/special/seed-music ### Tencent - LeVo / SongGeneration · Sep 2025 · open weights, https://levo-demo.github.io/ - LeVo / SongGeneration 2 · Feb 2026 · open weights, https://github.com/tencent-ailab/songgeneration ### Adobe - Firefly Generate Soundtrack · Oct 2025 · closed weights, https://news.adobe.com/news/2025/10/adobe-max-2025-firefly ### ACE Studio - ACE-Step · May 2025 · open weights, https://ace-step.github.io/ - ACE-Step v1.5 · Jan 2026 · open weights, https://ace-step.github.io/ace-step-v1.5.github.io/ - ACE-Step v1.5 XL · Jan 2026 · open weights, https://ace-step.github.io/ace-step-v1.5.github.io/ ### Soundraw - Soundraw V1 · Sep 2024 · closed weights, https://www.musicbusinessworldwide.com/ai-powered-beat-generator-soundraw-secures-3m-from-investors-including-eminem-manager-paul-rosenberg1/ - Soundraw V2 · Mar 2025 · closed weights, https://macaubusiness.com/soundraw-launches-v2-ushering-in-a-new-era-of-ai-driven-music-creation/ ### Boomy - Boomy · Mar 2019 · closed weights, https://www.axios.com/2021/05/12/ai-music-startup-boomy-launches ### Loudly - Loudly · Aug 2023 · closed weights, https://www.loudly.com/blog/ai-music-generator-from-text - VEGA-2 · Mar 2026 · closed weights, https://www.loudly.com/blog/vega-2-is-live-loudly-launched-its-most-advanced-ai-music-generator ### Beatoven.ai - Composer · Jan 2024 · closed weights, https://www.beatoven.ai/blog/introducing-text-to-music-a-dedicated-music-composer-for-content-creators/ - Maestro · Sep 2025 · closed weights, https://www.beatoven.ai/blog/introducing-maestro/ ### Sonauto - Melodia · Mar 2024 · closed weights, https://www.ycombinator.com/launches/Kb5-sonauto-make-hit-songs-with-ai - Melodia 1.5 · Jun 2024 · closed weights, https://www.ycombinator.com/launches/Kb5-sonauto-make-hit-songs-with-ai - Melodia 2.0 Beta 3 · Jan 2025 · closed weights, https://www.ycombinator.com/launches/Kb5-sonauto-make-hit-songs-with-ai - Melodia 2.0 Beta 4 · Jan 2025 · closed weights, https://www.ycombinator.com/launches/Kb5-sonauto-make-hit-songs-with-ai - Melodia 2.0 Beta 6 · Feb 2025 · closed weights, https://www.ycombinator.com/launches/Kb5-sonauto-make-hit-songs-with-ai - Melodia 2.1 · Jul 2025 · closed weights, https://x.com/SonautoAI/status/1948530889845342213 - Melodia 2.2 · Sep 2025 · closed weights, https://x.com/SonautoAI/status/1961180501391413373 - Melodia 3 · Feb 2026 · closed weights, https://www.reddit.com/r/sonauto/comments/1rg6vj2/sonauto_v3_is_excellent_my_super_long_post_about/ ### Tad AI - Tad 1.0 · Oct 2024 · closed weights, https://www.prnewswire.com/news-releases/tadai-launches-a-next-gen-ai-music-generator-set-to-redefine-the-future-of-music-creation-302272294.html - Tad 3.0 · May 2025 · closed weights, https://www.prnewswire.com/news-releases/tadai-launches-a-next-gen-ai-music-generator-set-to-redefine-the-future-of-music-creation-302272294.html ### AIVA - Lyra · May 2025 · closed weights, https://blog.aiva.ai/ - Influence · May 2025 · closed weights, https://blog.aiva.ai/ ### Soundful - Soundful · Apr 2022 · closed weights, https://www.prnewswire.com/news-releases/soundfuls-ai-powered-platform-empowers-new-future-for-music-creation-301527943.html ### HeartMuLa - HeartMuLa-oss-3B · Jan 2026 · open weights, https://heartmula.github.io/ ### Sonilo - Sonilo v1.0 · Mar 2026 · closed weights, https://www.prnewswire.com/news-releases/sonilo-eliminates-text-prompts-in-ai-music-generates-soundtracks-directly-from-video-302761956.html - Sonilo v1.1 · Jun 2026 · closed weights, https://www.prnewswire.com/news-releases/sonilo-launches-licensed-ai-music-generator-for-video-on-falai-302806164.html --- ## Business and the beast URL: https://jakehandy.com/business-and-the-beast Date: 2026-01-06 Summary: A conversation on modern AI coding with Khe Hy *A conversation on modern AI coding with Khe Hy* There's a particular moment that happens when someone with zero coding background starts building software with AI. It usually involves equal parts wonder and frustration and a lot of "wait, that actually worked?" (and probably at least one existential question about what programming even means anymore). I wanted to have this conversation with [Khe Hy](https://www.khehy.com/) because his path to AI is one that I’m seeing with a lot of business leaders. He's got a CS degree from Yale, spent 15 years analyzing quant funds, became Managing Director at BlackRock by 31, and then walked away from Wall Street to focus on his family. I’ve been having conversations with Khe here and there and I was surprised to hear that despite his CS background, he hasn’t been in the weeds of actual coding for decades. The current moment is changing that though, and now he’s back to building software in a world where the tools have fundamentally changed. I'm coming at this from the other direction. I spend my days in Cursor, running SQL queries, shipping prototypes, and thinking about AI tools as someone who lives inside them. We're both looking at the same technology but from very different angles. What follows is an unfiltered Q&A about what it actually feels like to build software in 2025, whether you're a technical PM or a business person picking up code for the first time. --- ### On AI coding tools **When you first opened Cursor (or Replit, or whatever AI coding tool you started with), what did it actually feel like? Was there a moment where something clicked, or was it mostly confusion?** **Jake:** I had been familiar with IDEs in the past, learning how to write a few odd scripts here and there pre-coding agents. Cursor felt, of course, very similar to VS Code with a few distinctions, chief among them being the chat panel. It didn’t take long for me to realize the power of that panel, especially its early Agent mode. I had previously been copy/pasting code snippets from ChatGPT, so watching Cursor’s Agent mode pretty much entirely automate processing that was taking up a considerable chunk of my time was a big “a-ha” moment for me. There was no turning back at that point. **Khe:** I’m embarrassed, but I had to take an online course on Cursor/Vibe Coding. I had to Google what IDE stood for and to this day I have never used VS Code. The course was aimed at non-coders and, honestly, just understanding Cursor’s three panels felt like freedom. And don’t get me started on using the terminal. --- ### On the skill curve **There's this debate about whether AI coding tools flatten the skill curve or just hide it. A seasoned developer knows why the code works, not just that it works. Khe, do you feel like you're actually learning, or are you just getting things done without understanding them? And Jake, from your side, do you think that distinction even matters anymore?** **Khe:** As someone who likes to be in control, I feel deeply uncomfortable knowing that some code is running, yet I have no idea what is happening. This has led me to a new style of learning. First, I spend a lot of time describing the problem I’m trying to solve with code and asking an LLM (typically ChatGPT) to suggest frameworks, unit tests, back-ends. I also try to understand these decisions. Then I have the LLM actually describe the code in *pseudo code* and see if I can track down the logic. The actual writing of the code is fairly straightforward. Then I pray that there are no bugs, because I don’t really know how to fix them without just saying “try harder.” That being said, I’ve started to incorporate unit tests (which I learned from ChatGPT) to test my code along the way. **Jake:** I like Khe’s approach, but in general I think the distinction is mattering less and less. Eventually I think most people won’t know the specifics of how their code works, just like most people don’t know the specific of how their car’s engine works. Once the value of an output is commoditized to a point where anyone can take advantage of it, the underlying understanding slowly fades away. That can and will happen with code (though there will always be code junkies that understand it all, just like motorheads). --- ### On the risks of AI coding **What's the worst thing you've broken while building something with AI assistance? And more importantly, how did you figure out how to fix it?** **Jake:** It’s less common nowadays with models that have been optimized away from making mistakes, but I used early ChatGPT to debug a lot of my SQL queries. At those times it was a bit risky, and I can recall at least a few times where the model confidently gave me an incorrect query (that worked!) that I used and generated some data reports with, no questions asked. Eventually, after I realized the reports had some inaccuracies, the cleanup wasn’t dissimilar from when I’d mess up SQL queries on my own. Lots of apologies and lots of tweaks to make sure the output is correct. **Khe:** I tend to struggle with what I call the “glue tasks.” These are the services that sit between your code and the end-user and in this case it was Resend.com being unable to send Supabase’s auth emails. There was an issue between the domains, SMTP servers and database access. With a challenge like this, I zoom out to fully understand the chain of steps that leads to the error (or outcome). I guess the antidote is a lot of patience! --- ### On ambition inflation **AI coding tools seem to make people more ambitious about what they try to build. Before, you might have hired someone or used a no-code tool. Now you're trying to build actual software. Is this ambition inflation a good thing, or are people setting themselves up for projects they can't maintain?** **Jake:** I think it’s a double sided sword. For technical product folks like myself, someone who historically has patched together mockups on Google Slides or Balsalmiq, using AI coding tools to create interactable web apps is a net benefit. I can go from ideation to workable prototype without bugging my devs. Everyone’s happy. For less technical product folks (or perhaps entry level analysts who have bosses that insist they can vibe code an entire feature set), there are problems and slow down. There’s a whole messy underbelly needed in terms of preview deployments, necessary database structures, etc, that these types of people are going to get caught up in. A lot of this type of infrastructure needs the careful guidance of a senior developer to ensure that the prototype is scalable and secure. As models continue to get smarter and smarter, people are going to be more and more convinced that they don’t need to worry about that stuff. And that’s just not true. **Khe:** I think it’s a good thing and vibe coders life myself get a quick dose of reality when we need to think about marketing our apps or having them pass crucial security tests. But the challenge for me has now actually become time. Despite all the AI, these projects are extremely time consuming, which leads me to ask myself: Why am I actually doing this? For now, it’s usually to scratch an itch of a product I’ve wanted to use myself. Other times it’s to learn something new (like the Claude Agent SDK) or to build solutions from my clients. Ultimately, it’s become a pretty vanilla resource allocation question. --- ### On the moment when AI stops being helpful **Let's talk about the moment when AI stops being helpful. That point where the project gets too complex, or the context gets too messy, and suddenly you're spending more time managing the AI than building. Khe, have you hit that wall yet? Jake, how do you navigate it?** **Khe:** I have, but usually it’s when I try to one-shot a pretty expansive PRD. I then subsequently realize that not only is one-shotting is all about feeding my ego, but it usually overcomplicates what I’m trying to build – and more importantly, what I’m able to test. So now, I still have the expansive PRDs but just build and test in incremental units. **Jake:** Historically, yes. I’ve got some old AI-generated repos that I have no desire to go back into and clean up. Lately, no. The more recent Codex models (5.1 and 5.2 on Extra High reasoning, specifically) are able to chew through an insane amount of context. Tasks in the past that required extensive repository knowledge are handled easily, sometimes taking 10-20 minutes. Their autonomy is fascinating to watch; oftentimes the model will explore websites/documentation unprompted to find stable solutions. Makes me feel like a proud parent. --- ### On product-market fit **There's a difference between building something that works and building something people actually want to use. Khe, you come from a world of analyzing investments, which is fundamentally about understanding what makes something valuable. How does that mindset translate when you're the one building? Jake, how do you think about product-market fit when you can ship so much faster?** **Khe:** It’s interesting since while I do have a finance background, I think I’m better served by my decade of Digital Marketing experience by building out the RadReads platform. So first I ask myself, what channels/platforms could I use to get early users? How would I message, position and name it? I haven’t done much building in the enterprise category for investment firms yet – if (or when) I get to that point, I’d be much more focused on the TAM, unit economics, distribution strategy, etc. **Jake:** Product-market fit for me is an upfront task. Once that’s settled, and you’re iterating/shipping quickly, the product-market fit becomes the feedback you’re getting from active users. If you can cross that first barrier and get a solid atomic network, the speed at which AI lets you ship becomes a tool multiplier in your iterative development process. --- ### On getting your hands dirty **Both of you could easily hire developers or agencies to build things. What made you decide to get your hands dirty instead? Is this about cost, control, learning, or something else?** **Jake:** Honestly it’s just who I am. I started out my career by parking myself next to an entrepreneur at a local business center and telling him that I’d work for him until he could pay me, and then I’d work for him more. In high school I spent an inordinate amount of time cataloging my digital music library. I’ve got control issues and a gnarly work ethic. It gets me into trouble sometimes. But for vibe coding and rapidly generating prototypes it’s pretty much the perfect combination. **Khe:** The fact that I never hired a developer should be telling here. Prior to agentic coding, most of my coding projects were half-baked ideas that I thought “would be cool.” So not only could I not justify the cost, I didn’t even know how to “speak developer.” I wouldn’t have known which questions to ask. When I tried learning how to code via a programming language, it just felt like too steep of a curve – and too long of a climb. --- ### On knowing when to trust the output **AI makes confident mistakes. It'll write code that looks perfect but fails silently, or suggest solutions to problems that don't exist. How do you develop the judgment to know when to trust the output and when to be skeptical? Khe, without deep technical background, how do you even know when something's wrong?** **Jake:** Those types of issues are happening less and less, but I do still think it's pertinent (and will remain so) to know what code your agent is outputting. You’ve gotta be the master planner and ensure that, even if you don’t know the color of the cogs, you know where they’re being placed and what they’re connecting to. Also: ask your agent about the code, often, and test locally (or in preview branches) whenever possible. Use the time saved with vibe coding to test your software more intently. It’s worth it. **Khe:** Ummm, I don’t! That’s why I focus heavily on testing and understanding edge cases before I start building. I’m currently using ChatGPT to help me understand the principles of testing. I do wonder if the LLMs will get good enough at identifying mistakes, which would then mean that the “meta skill” I need is how to do this *alongside* AI. --- ### On building software yourself **Khe, you're building LaTour AI to help buy-side firms save time with AI. What have you learned from building software yourself that changes how you think about what you're selling to finance professionals?** **Khe:** I’ve focused primarily on small and mid-sized investment firms conducting financial research. These firms tend to be quite ingrained in their existing practices and subject to tight compliance constraints (particularly around emerging tech). Right now, I’ve worked with individual clients to build specific tools that they might use themselves for creating dashboards, scraping web data and assessing trends. **Jake, flip side: how does understanding business context (from your PM work) change how you approach building?** **Jake:** The critical role in my product management work is always in reconciling the business side with the development side. Engineers don’t (and shouldn’t have to) speak the language of sales, and vice versa. My job is to gather a holistic picture of the prospective user, the market they reside in, and the technical requirements needed to serve them. Agents benefit from this same kind of information. I try to synthesize it all down to the critical bits, feed it that information, and then pair program alongside it. That’s where I see the best results. --- ### On building and maintaining **Everyone talks about building. Nobody talks about maintaining. Jake, what percentage of your AI-assisted coding time is building new things versus fixing, updating, or managing things you've already built? Khe, are you thinking about this at all, or is it a problem for future-you?** **Jake:** I’m primarily a prototyper so post-build management is something I don’t deal with too often. I’ve got some legacy websites I’ve gone back and updated, and manage going forward, but the repos are small enough for modern agent models to handle that pretty handedly. **Khe:** Since my apps only have a few users, there isn’t a ton of maintenance (yet). But I’m trying to stay ahead of the curve by trying to understand which logs I should be monitoring and how a tool (like Sentry) could help facilitate the process. --- ### On advice for the future **If you could go back to when you started using AI coding tools seriously, what advice would you give yourself?** **Jake:** Go fast and break things (responsibly). Try a million different things and stick with what works. Be hard on your agent. I’d also probably spend a bit more time learning to manually code, for my own posterity. It feels like it's too late to bother with that now. **Khe:** Follow the aliveness. For me, this isn’t core to my job so I can treat it more like a hobby. I want to lean into the thing that I can’t stop thinking about and am always trying to fix. Then I use that as a launching pad to better understand the underlying architecture. --- ### On the future of coding **Final question: In five years, what does "knowing how to code" even mean? Is it going to be more about prompt engineering and system design than syntax and algorithms? Are we both going to look back at this conversation and laugh at how primitive these tools were?** **Jake:** I always balk at a future of “prompt engineering”. If we get to a point where the only thing needed is managing how we talk to AI agents, then the AI agents themselves can probably manage that too. I think a non-insignificant portion of the software engineering career field shifts into agent management. We’re seeing a lot of that now, and we’re still in the pretty early days of this tech. If the AI bubble were to pop today, AI code generation is by far the most likely segment to remain. I think the concept of coding continues to shift more into the abstract. Those that know the inner depths will likely see a future of fixing shoddy AI code and managing infrastructure scaling and security. Everyone else just needs to get friendly with the bots. **Khe:** Primitive, yes! If we had this interview last January we’d be talking about how primitive coding “auto-complete” was – that for sure wouldn’t have gotten me interested. There’s always going to be a need to write high quality and reliable code. But there’s going to be an entire group of folks untethered to a specific approach AND willing to play around the edges of what AI can do. This group will be large and very heterogeneous, but here’s one thing I’d bet on: they’re going to be very valuable to companies. --- Want to follow along with both of our AI journeys? Check out [Khe's newsletter on future-proofing your career with AI](https://www.khehy.com/) and [Jake's work on all things AI-tech](https://handyai.substack.com/). --- ## The modern AI workspace URL: https://jakehandy.com/modern-ai-workspace Date: 2025-09-10 Summary: You should probably start using Cursor for non-coding tasks Most people know [Cursor](https://www.cursor.com/) as an AI-powered code editor - a supercharged fork of Visual Studio Code that gives developers intelligent code completions, refactoring capabilities, and contextual assistance. But there's an untapped potential here that extends far beyond the realm of software development. I've been using Cursor for nearly all of my non-coding work, and it's quickly become my favorite productivity tool. Cursor can (and should) be your digital command center for nearly everything you do (And for you [Windsurf fans out there](https://www.windsurf.com/), everything here applies for you, too). ## Why Cursor for non-coding work? ![Workspace](https://jakehandy.com/blogmedia/workspace1.png) We've all been there. Multiple applications open, documents scattered across various folders, endless browser tabs, and that nagging feeling that your computer is working against you rather than for you. Traditional productivity tools like Microsoft Office, Google Workspace, or Notion are powerful, but they lack something crucial: **an AI that can take direct action on your files and folders**. This is where Cursor shines in unexpected ways. By opening a root workspace folder in Cursor for your daily non-coding tasks (be it writing, research, project management, or content creation), you're essentially giving an AI assistant direct access to help organize, edit, and enhance your work. ### AI that takes action ![Workspace](https://jakehandy.com/blogmedia/workspace2.png) Unlike chatbots that merely suggest, Cursor's Agent can directly perform actions across your entire workspace: - **Organize your files.** "Move all my research PDFs into a references folder and rename them with today's date." - **Batch edit documents.** "Find all mentions of 'quarterly goals' in my notes and update them to our new objectives." - **Format and structure.** "Convert my meeting notes into a properly formatted report with sections for action items." - **Extract and synthesize.** "Pull key statistics from all my research files and create a summary document." The power comes from Cursor's ability to understand both your instructions and the context of your entire workspace, then make changes across multiple files without you having to manually implement every suggestion (using Python scripts or whatever methods it feels necessary). ### Tab completion beyond code ![Workspace](https://jakehandy.com/blogmedia/workspace3.png) Cursor's tab completion feature isn't limited to programming syntax. When working with any text document, especially Markdown files, Cursor offers intelligent completions that can: - Auto-format your text as you type, maintaining consistent styles - Suggest relevant links from your workspace or recently viewed websites - Complete citations or references based on your existing documents - Fill in boilerplate text for recurring document patterns - Automatically format lists, tables, and structured content These seemingly small assistances add up to significant time savings, especially when composing longer documents or working with structured content. ### Built-in version control for peace of mind Cursor's built-in Git integration offers another significant advantage, especially in content writing contexts. Even for non-coders, Git allows you to track every change to your documents, revert to previous versions when needed, and maintain a complete history of your work. This gives you the confidence to experiment freely, knowing you can always go back to any previous state of your documents. ### The latest AI models without extract subscriptions ![Workspace](https://jakehandy.com/blogmedia/workspace4.png) One of Cursor's most compelling advantages is access to multiple state-of-the-art AI models without forking over the cash for multiple subscriptions. For a single $20/month subscription, Cursor provides unlimited access to: - **Claude 3.7 Sonnet.** Anthropic's powerful model with advanced reasoning capabilities - **GPT-4o.** OpenAI's latest generation model with enhanced coding and text capabilities - **Gemini 1.5 Flash.** Google's model optimized for long-context interactions Beyond the included models, Cursor allows you to connect your own API keys (at cost) for even greater flexibility: - **OpenAI API keys.** Use any OpenAI models you have access to through your own account (o1, o3-mini, others) - **Anthropic API keys.** Connect directly to Claude models at your own cost - **Google API keys.** Access other Gemini models through your Google API credentials Cursor also supports OpenRouter, a unified interface for multiple LLM providers, allowing you to connect your workspace to virtually any LLM provider out there (including DeepSeek and many, many more). This effectively eliminates the need for separate subscriptions to ChatGPT Plus, Claude, or other AI services. You're getting enterprise-grade AI capabilities built directly into your workspace environment. * * * ## Real-world applications Here are some practical non-coding scenarios where Cursor shines: - **For researchers and students** - Manage literature reviews with AI assistance organizing papers and extracting key concepts - Draft papers with AI-powered suggestions and formatting help - Create and maintain bibliographies with proper formatting - Generate summaries of research findings across multiple documents - **For content creators** - Organize content calendars and drafts in a unified workspace - Get AI assistance with drafting, editing, and polishing content - Manage asset libraries with AI helping to find and organize images or references - Track version history of all content with built-in Git support - **For project managers** - Create and maintain project documentation in Markdown - Generate reports from raw data files - Track tasks and updates across multiple project documents - Use AI to summarize status updates from team documentation - **For personal knowledge management** - Build and navigate your personal knowledge base - Link notes and concepts with an intelligent system that understands connections - Use AI to help refine ideas, generate summaries, and extract action items - Keep everything version-controlled and accessible ### Getting started with Cursor in your workspace 1. **Download Cursor** from [cursor.com](https://www.cursor.com/) 2. **Create a dedicated workspace folder** for your non-coding project (or projects) 3. **Open this folder as a workspace** in Cursor 4. **Add a .cursorrules file** in your root directory with guidelines for how AI should handle your documents (get creative; different projects may have different guidelines) 5. **Learn the keyboard shortcuts** for AI assistance (Cmd+K for editing, Cmd+I for inline commands) * * * ## Unlimited customization for advanced workflows Where Cursor starts to get really crazy as a workspace solution is its virtually limitless customization potential. Far beyond just being an editor with AI capabilities, Cursor can become a central command center that connects to virtually any external system, tool, or data source. ### Model Context Protocol: Extending AI capabilities [Model Context Protocol (MCP)](https://docs.cursor.com/context/model-context-protocol) is an open standard that allows Cursor to connect with external data sources and tools (think APIs for AI). This means your AI assistant can: - **Query databases directly.** Connect to SQL, MongoDB, or any database to fetch, analyze, and manipulate data - **Access knowledge bases.** Pull information from Notion, Confluence, or internal documentation - **Interact with version control.** Create branches, generate pull requests, and manage git workflows - **Process specialized data.** Connect to data analysis tools, visualization libraries, or industry-specific systems Setting up an MCP server can be as simple as creating a small script that responds to specific commands (and hey, you can ask the Agent to help you with that). This effectively turns Cursor into an orchestration layer that can control any external system that has an API or command-line interface. ### Custom scripts: Automation your workspace ![Workspace](https://jakehandy.com/blogmedia/workspace5.png) The ability to run scripts directly from Cursor in general transforms makes it a powerful automation hub: - **Build data pipelines.** Create scripts that pull data from multiple sources, process it, and generate reports - **Automate publishing workflows.** Set up scripts that prepare content, optimize images, and deploy to publishing platforms - **Generate dynamic content.** Create scripts that fetch real-time data and inject it into your documents - **Customize AI behaviors.** Write scripts that pre-process your content before AI acts on it, or post-process AI outputs Since Cursor is built on the VS Code architecture, it inherits a vast ecosystem of extensions and capabilities that can be leveraged for non-coding tasks. ### Real-world advanced examples Once you start to really think about Cursor as an open-ended workspace where you can instructre your Agent to do basically anything on your documents and data, the possibilities are mind-boggling: - **A journalist** could create a workspace that connects to news APIs, scrapes relevant websites, manages interview transcripts, and automatically formats articles for publication. - **A researcher** could build connections to academic databases, data analysis tools, and collaboration platforms, with custom scripts that format citations and generate literature reviews. - **A project manager** could set up automated reporting that pulls data from JIRA, analyzes GitHub activity, and creates weekly status reports with visual progress indicators. - **A content creator** could integrate with social media APIs, media asset management systems, and analytics platforms to create a comprehensive and completely customizable content management system. What makes all this uniquely powerful is that these integrations live within your workspace, not as separate applications you need to context-switch between. The Agent becomes the interface layer that understands both your intent and how to utilize these connections to accomplish complex tasks. * * * ## The future of work is agentic As AI agents continue to evolve, the lines between coding and non-coding tools can and will blur. Cursor (and Windsurf) represents an early example of what's possible when we expand our thinking about development tools beyond their original purpose. The most powerful productivity boost won't come from yet another app in your workflow, it's from making your existing workflows smarter, more open, and slapping an AI agent on top of them. Transforming Cursor from a coding environment to your central workspace goes beyond just adopting a new tool, it's about embracing a new way of working where AI becomes an active participant in your daily tasks. Try it for a week. Open a workspace folder in Cursor for your next non-coding project. You might be surprised at how quickly it becomes indispensable. --- ## Resume and work history URL: https://jakehandy.com/resume Date: 2025-06-01 Summary: All the things I've done (and am still doing). Jake Handy's work history, newest first. Staff Product Manager, Automation at The Mechanical Licensing Collective in Nashville, Tennessee, previously Senior Product Manager at Vobile and Pex. ### The Mechanical Licensing Collective - Staff Product Manager, Automation · Jun 2026 - Present · 2 mos · Full-time · Nashville, Tennessee · Hybrid Architecting automation solutions to put more money in songwriters' pockets. Skills: Product Management, Prototyping ### Vobile - Senior Product Manager · Apr 2025 - Jun 2026 · 1 yr 3 mos · Full-time · Remote Following acquisition, continuing Pex's mission to use cutting-edge tech to fairly protect and compensate creatives and their work. ### Pex - Senior Product Manager I · Nov 2022 - Apr 2025 · 2 yrs 6 mos · Full-time · Remote Senior PM leading Pex's R&D efforts. Projects include a proprietary machine learning model that aggregates massive disparate data sources, hands-on RLHF training of various metadata resolution models, research into improvements for Pex's numerous advanced audio and melody fingerprints, and exploration into emerging technologies like generative artificial intelligence. Skills: Artificial Intelligence (AI), Music Publishing, Machine Learning - Product Manager II · Oct 2020 - Nov 2022 · 2 yrs 2 mos · Full-time · Remote PM on the ingestion and metadata portion of Pex's Attribution Engine. Responsibilities included vetting and establishing metadata standards, running agile operations for two distinct teams of developers, partnering with rightsholders to establish content ingestion feeds, and working with our database team to ensure product requirements were working in harmony with database designs. Skills: Artificial Intelligence (AI), Music Publishing, Agile ### Ingram Content Group - Digital Product Specialist · Apr 2019 - Oct 2020 · 1 yr 7 mos · Full-time · Nashville, Tennessee Product management for numerous products, both B2B and B2C, within an agile, fast-paced team. Products included a marketing platform for authors, a metadata enhancement service for publishers, and others. Skills: Go-to-Market Strategy, Machine Learning - Business Operations Analyst · Sep 2017 - Apr 2019 · 1 yr 8 mos · Full-time · Nashville, Tennessee Analyzed numerous book and media business operations, utilizing SQL and multiple data visualization tools to serve Ingram teams. Day-to-day work in collaboration with media analysts, marketers, IT professionals, front-end developers, and others. Skills: Go-to-Market Strategy, Software Development, SQL ### Naxos of America - Music Data Consultant · May 2017 - Sep 2017 · 5 mos · Contract · Franklin, Tennessee Onsite consultant for numerous music data-related issues and tasks. Improved Classical metadata for numerous albums and helped existing staff to improve data workflows. Skills: Go-to-Market Strategy, Metadata Standards ### Dart Data - Head of Metadata · Nov 2016 - Jun 2017 · 8 mos · Full-time · Nashville, Tennessee Served as Head of Metadata and worked to expand the technology developed from our platform into a complete metadata cleanup B2B solution. Skills: Music Publishing, Go-to-Market Strategy - Music Metadata Specialist · Jun 2015 - Nov 2016 · 1 yr 6 mos · Full-time · Nashville, Tennessee Served as SaaS product lead and music metadata specialist in developing an advanced Classical music distribution platform that collected and distributed music metadata and processed it to perfection for consumption and categorization by iTunes, Spotify, Google Play, Amazon, etc. Developed proficiencies in HTML, CSS, Javascript, SQL, and numerous pieces of mockup and design software. Skills: Music Publishing, Go-to-Market Strategy, SaaS ---