760 karma · joined June 11, 2023
Having said that, there is nothing to make the bronze age epoch impossible. There is nothing in the epic which may not have been possible in the bronze age based on what we already know about history.
=> 80% of engineering problems == budget models like gpt-mini can handle.
=> 15% of complex reasoning, vibe coding == frontier models like Opus, still sustainable.
=> 5% of 'really complex enterprise grade reasoning' == need massive tokens, impossible at scale unless pockets are deep.
Before LLMs came, there used to be the technical debt to deal with in a project, now there is also the added cognitive debt which is way more subtle and impactful long-term. If your source of truth isn't source code but a prompt (or even a series of prompts with branches) and the executor of prompts is a non-deterministic agent, I think you've already lost the battle there.
Computers and LLMs are great at automation of low-level human cognitive tasks like memory, decisions and loops, etc. but struggle enormously with high cognitive tasks like reasoning, deep logic, nuance, etc. Not that it can't be done (Claude platform is proof that it can) - but the cost and scaling advantage in this realm belongs to the human brain, not the LLM.
The present Sonnet/Opus versions (~4.8) will likely be what everyone in the enterprise might end up using eventually. And even though local models aren't there yet, there are budget alternatives from the families of DeepSeek, Kimi, GPT, MiniMax, etc. available through APIs of NVidida, OpenRouter, Groq, etc. which are very much Sonnet grade.
Most AI companies are just testing the waters with paid tiers right now, their greatest fear with increased pricing is folks reverting back to wikipedia, stack-overflow and other public domain organic activity buzzing back to life; that will kill any RoI potential in LLMs forever. They're playing the wait game instead, observing how the digital sphere reacts to every little increase in price.
If that weren't the case, they'd be pricing at lucrative premiums already and even gotten away in short-term considering the increased dependency in the enterprise world. But that'd be like killing for the golden egg too soon and losing all long-term potential.
Once the folks are so addicted to LLMs that even writing a hello world program sounds like a nightmare and coming up with an article draft feels like reinventing Egyptian glyphs, that's when the real pricing hammer will come.
- Intermittent fasting (16x8 or at least stop eating after sun down)
- Daily morning pranayama (or 'breath work' if you prefer that term)
- Daily morning intake of copper utensil stored water (~8 hours or overnight)
- Weekly oil pulling for gum health.
This approach feels a bit stoic and neanderthal initially, less attuned to our modern and progressive society, but as effective as Ozempic in long-run (minus the side-effects or addiction).
One way is what I call the "Modular MVC pattern" that involves pure js routing and manual DOM manipulation without using any framework at all. You handle complexity in two ways: by modularizing the "controller" parts into multiple js modules for each route, and "view" parts into multiple HTML partials - and using the event bus pattern if your app gets too complex (as alternative to modern reactive frameworks like react/vue).
Shameless plug: I've tried to implement this exact pattern with limited success in Abhyasa Quiz App[1], a side project.
The alternative to using tailwind here is to define the specific style elements for each one in the css stylesheets yourself with something like this:
.bg-sky-500 { background-color: blue; }
Tailwind proponents argue that they avoid this "stylesheet hell" by picking ready pre-defined tailwind classes like bg-sky-500, etc. Plus they also argue that this workflow will increase productivity by standardizing "style mindsets" of your dev team who all will think "blue" means "sky-500" (for example).
Maybe it has use cases in deep or professional design work but for most backend or full-stack devs, bootstrap is definitely better than meddling with this structure.
Also open-quiz-commons, the mcq dataset that powers the above quiz app: https://github.com/prahladyeri/open-quiz-commons
For several years, ngrok was practically free, only recently they've started monetizing once it gained popularity.