I love the hands-on developer experience of programming in Svelte. But since we're in October of 2026 I have to ask, is the vibe-coding experience in Svelte any different than in React? Can anyone with experience in both comment?
Yes. We open sourced an SSG based off SvelteKit about a year ago and were starting building AI tooling and product workflows around it, <a href="https://statue.dev" rel="nofollow">https://statue.dev but have since mothballed it.
For most of 2024-2025 frontier models really struggled with Svelte 4 vs 5 compatibility issues. Some of the main contributors, to their credit, really put in a lot of work to create benchmarks/MCP/other tools to make AI better at using Svelte. Personally I am just not a fan of MCP and other tools like that at all, and decided I'd rather just use vanilla css/js for new projects.
Look at this; it's literally multiple times more expensive to have a model sifting through all this stuff in every context use them with a tool: <a href="https://svelte.dev/docs/ai/prompts/llms.txt" rel="nofollow">https://svelte.dev/docs/ai/prompts/llms.txt All of these are input tokens and turns to gather context.
The "too niche to be a major training priority" dilemma is actually a really big problem that almost all new or emerging dev tools have now. Incumbents and category leaders are priorities and show up in major benchmarks, so models develop excellent tacit knowledge and capabilities with them and expose it everywhere all the time for "free" in their weights. Everything else is at a major disadvantage because models don't know about them, how to use them, how they work, what they're for/why, and every time you use them you pay a big capability and token hit because models only learn about them in-context.
I don't blame the Svelte team for this at all. There should be a better way for devtool projects to contribute to frontier labs training pipelines or properly posttrain their own agent coding models.
> and decided I'd rather just use vanilla css/js for new projects.
So is the rise of AI coding, the end of frameworks?
Frameworks were created to reduce boiler plate ( at the expense of new abstractions which occasionally leak ) - boiler generation is less of an issue for AI, and the underlying platform is very well specified?
I guess the only problem with vanilla is if the sheer volume of text overwhelms the context?
> Frameworks were created to reduce boiler plate
Even more fundamentally, frameworks were created to reduce the developer time and skill required to build applications. This has been a pipe dream many have chased since COBOL replaced assembly language.
LLMs are probably the first technology that actually approaches doing that. And yes, they don't need frameworks, they're indifferent to the amount of code or boilerplate needed, don't care about the developer "experience," and will write vanilla JS and HTML just as well as anything else you ask them to do, maybe better.
stillatit · · focus · HN ↗
weitendorf · · focus · HN ↗
For most of 2024-2025 frontier models really struggled with Svelte 4 vs 5 compatibility issues. Some of the main contributors, to their credit, really put in a lot of work to create benchmarks/MCP/other tools to make AI better at using Svelte. Personally I am just not a fan of MCP and other tools like that at all, and decided I'd rather just use vanilla css/js for new projects.
Look at this; it's literally multiple times more expensive to have a model sifting through all this stuff in every context use them with a tool: <a href="https://svelte.dev/docs/ai/prompts/llms.txt" rel="nofollow">https://svelte.dev/docs/ai/prompts/llms.txt All of these are input tokens and turns to gather context.
The "too niche to be a major training priority" dilemma is actually a really big problem that almost all new or emerging dev tools have now. Incumbents and category leaders are priorities and show up in major benchmarks, so models develop excellent tacit knowledge and capabilities with them and expose it everywhere all the time for "free" in their weights. Everything else is at a major disadvantage because models don't know about them, how to use them, how they work, what they're for/why, and every time you use them you pay a big capability and token hit because models only learn about them in-context.
I don't blame the Svelte team for this at all. There should be a better way for devtool projects to contribute to frontier labs training pipelines or properly posttrain their own agent coding models.
DrScientist · · focus · HN ↗
So is the rise of AI coding, the end of frameworks?
Frameworks were created to reduce boiler plate ( at the expense of new abstractions which occasionally leak ) - boiler generation is less of an issue for AI, and the underlying platform is very well specified?
I guess the only problem with vanilla is if the sheer volume of text overwhelms the context?
SoftTalker · · focus · HN ↗
Even more fundamentally, frameworks were created to reduce the developer time and skill required to build applications. This has been a pipe dream many have chased since COBOL replaced assembly language.
LLMs are probably the first technology that actually approaches doing that. And yes, they don't need frameworks, they're indifferent to the amount of code or boilerplate needed, don't care about the developer "experience," and will write vanilla JS and HTML just as well as anything else you ask them to do, maybe better.