Tim Hanlon

My original goal for effect-grep was giving agents context for how to write good Effect v4 code. I think I'm finally making some progress on the layer/composition side of things. Here's a Markdown graph from github.com/joelhooks/rat-sta…

Struggling to navigate the demented online culture during "ai fall", and its polarizing black-and-white thinking, following a summer slaughtered by burned out, overpromised, oversubscribed hype exposure? Try the 3-era™ meme! Hi, are you a computer musician using librosa, numpy, and torch as your instrument? Congratulations, you're no longer doing AI 🧠 you're just engineering! ⚙️🛠️🔧 We delight to inform you AI has moved on. With the dadaist power of absurdity invested in us, we hereby relieve you of this burden. The term "AI" has been officially excised from the description of your practice. *## Countering the lobotomizing hype-cycle meme of "AI" w/ the "3-era" meme ##* Since 1955, the meme "AI" was a future capability, a moving target 🎯 (as s soon as a capability is achieved, it's no longer "AI" it's just engineering). The name is designed as a vehicle for fundraising (and was more successful over its alternatives like "cybernetics"). By nature of a moving target, the meme's behavior has a predictable structure: attract attention (talent, mindshare, funding, customers), over-promise, and under-deliver. Hence we have seasons of ai winters & boom-bust cycles. However, @karpathy's three paradigms of software engineering are not moving targets, nor economic cycles, they're just capabilities. Software 1.0: Coding - Understand the problem, define the rules, computer automates the solution. Software 2.0: ML - Understand the problem, define the solution, computer automates the rule-writing. Software 3.0: Vibecoding - Describe the problem in english, computer automates the computer Computer music creative coders, confused about how to differentiate themselves, can instead think of their practice in these terms: 1.0 → livecoders using strudel, max/msp, bytebeats; musicians coding procedurally 2.0 → @dadabots, ISMIR, magenta, neural synthesis, librosa, numpy, torch; musicians doing machine learning, training models, coding in python 3.0 → suno, udio, gemini lyria, making music by describing it in english Or computer artists in general: 1.0 → Tools - You operate the software. 2.0 → Learned tools - The software learns patterns. 3.0 → Agents - The software participates in the creative process. The era of 2.0 was 2012-2022 and was underground unless you were orbiting the hacker or academic community and had GPUs. Though the term "AI" was abused by over-promised product marketing in this decade, it never really hit a winter. Whereas 3.0 (prompting, vibecoding) started in 2023, reached mass awareness and buy-in at an unprecedented scale, and its over-optimism is feeling like burnout. *## Computer Music Software 2.0 ##* Are librosa, numpy, & torch your instrument? Run your own GPU? Like to play with matrix math? The meme of "AI" is so strong it's easy to think you're swept up in it. But nope. You're no longer AI. The moving target has passed. You're just engineering in era 2.0. New eras don't replace old, they continue to develop in tandem, at their own pace. Awareness of the creative practice: 3.0 → Popular. 100 million users have tried making music with prompt apps. It was shoved into people's faces with ads. 2.0 → Has yet to hit much awareness as a music practice. Still underground. Gets confused for 3.0. 1.0 → Recently gained popularity with strudel blowing up last year (thanks dj dave & switch angel!). Still very few musicians are doing it, or have learned to code, or have followed in the statistical/procedural footsteps of Brian Eno or Dennis Mårtensson. 2.0 was inaccessible to most musicians during its era, has not gained very much popularity yet, but continues to become more accessible as - Everything gets faster - Costs go down - Matrix math in regular computers / laptops / phones gets faster (e.g. CPU SIMD instructions, apple sillicon) - Algorithms make breakthroughs in speed (diffusion, quantization) - More open models front-load the expensive parts (e.g. neural codecs) @dadabots was born in 2012, experienced fully the era of 2.0 from the start, was partly responsible for it, and made a music practice out of it. We fell in love with ML. Music that is based on statistics & linear algebra felt even more extreme & we were even more fascinated by it than purely regular DSP and procedural coding. (Watch our documentary PIZZAFIRE on our website to hear the full story.) Do we care THAT MUCH to chase the moving target that is "AI"? Well, the scifi stuff is cool. And agents do funny shit. BUT let's pause for a second. We actually just really love 2.0, because it breaks out brains. We love neural synthesis for itself. 2.0 isn't done yet. It's this super crazy giga playdough that's still vastly under-understood. ⚙️🛠️🔧

Nobody on board the Enterprise actually knows how "warp drives" or "holodecks" work. They are 300 years into the age of Vibe-Engineering.