Let's face it, the wild west days of endless new frameworks competing on a level playing field are fading into the sunset. LLMs, those code-slinging AI deputies, are riding into town and tipping the scales towards the established heavyweights.
It's not that frameworks are dead, but those hot, new gunslingers with their fancy tricks and clean APIs have a problem. Think of it this way: most settlers out on the frontier would trust a grizzled veteran with encyclopedic knowledge of the terrain over a flashy stranger, however promising. And while some will always follow those promising upstarts, LLMs will keep that knowledge gap wide.
For seasoned domains, the calculus changes. LLM support for popular frameworks means it's faster and easier to just use what the AI is already good at. The more devs hop on the bandwagon, the stronger that knowledge advantage gets. Why rewrite the rulebook when your friendly AI sheriff knows it back to front?
And hey, those big, sometimes clumsy behemoth frameworks – the full-stack ones? Suddenly, they look like a safe haven. You got a single territory for AI to patrol, no jarring jumps from one style to another. That translates to better, more reliable AI-generated code in your toolbox.
Don't mistake this for the end of innovation. There's still a wild frontier out there – spatial computing, heck, anything where there aren't firmly established rules of the road. These are the lands where those gutsy framework creators can make their mark, where experimentation is more valuable than AI familiarity.
But be warned: Those upstart frameworks in settled domains? Unless they offer something truly groundbreaking, they'll always be fighting an uphill battle. Now, it's not just about building a better mousetrap; it's about attracting enough builders, fast enough, to rival the AI posse backing the big players.
It's a brave new world for software. LLMs may not be outlaws, but they sure are changing how the game is played.