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I’m pumped for this next release of ignite-element. I’ve been using the v3 beta on my personal projects and I think it’s nearly ready. Just polishing a few things and cleaning up the docs.
If you want to try it early:
`pnpm add ignite-element@beta xstate`
0xjcf.github.io/ignite-eleme…
Feedback is always appreciated.
(v2 stays on `@latest` if you need stable.)
JOSΞ retweeted
So I’ve now grabbed an old Amazon Echo Dot 2nd generation and over 10 years old and rooted it like I did with the Fire tablet. Now my Grok Bot is building out a dedicated solution on it to make it the voice of my top level Chief of Staff Charlie over wireless. This will enable to get updates, issue team commands and more anywhere in my house without needing a computer or phone. Doing this on my Omarchy Linux laptop with the help of Grok Bot.
JOSΞ retweeted
Learn software architecture. I know actually learning to code is hard and takes a long time. Learn architecture at a higher level. Also, don't just send multiple agents to work on multiple features. Stay with the agent and build feature by feature so that you can always follow the spec and know what is happening.
JOSΞ retweeted
nah bro we're in a simulation for sure
This entire ocean is a 61 KB HTML file.
Built with Claude Code + Opus 5.5 in about 30 minutes, according to its creator.
It runs in the browser using WebGPU: FFT waves, whitecaps, sun glitter, a physically based sunset sky with clouds, and a free-flying camera. No game engine or rendering library.
Claude rendered screenshots in headless Chrome, then had separate subagents critique them. The creator gave feedback along the way, mainly on the clouds.
The 61 KB build is minified and self-contained. Download it, open it in Chrome with WebGPU support, and explore with WASD.
JOSΞ retweeted
I'd call this a bubble in a bubble
Tech people somehow still think normies are not spinning up personal software already
They're not doing it in Claude Code in a terminal like tech people for sure
But their AI chat app is already doing it for them without them even realizing they're building personal software, like generating PDF reports, full web app dashboards and even entire web apps
That will keep getting more advanced and soon ChatGPT will just spin up a Photoshop clone (but ofc only if they need it, preferring to just do their photo edits for them)
Everyone will mostly use personal ephemeral software inside AI chat apps I think
Some software moats will remain like social media (community), ecommerce (think like Shopify and Stripe), etc but they will just be used by AI to build the personal software with
So maybe that's the point here, become a tool agents use to solve their user's problems and charge agents for it (like many are saying)
i actually think there's a huge opportunity here
we're so caught up in our indie hacker bubble that we forget most people have no clue how any of this works
the average person doesn't want to build their own software, they just want something that works
i think who's buying software is shifting more than software itself
Slow, deep work where I take my time to review has become Codex work. Working with Astra or Sol is much slower, and quick implementation (my version of startup mode) have turned into Grok bot work. It feels snappy to me. And the quality is great for web dev work IMO..
JOSΞ retweeted
> This seems compelling, but I don't know much about formal verification. Read Boris's tweet and create a video explaining the concept.
I used Opus 5.5 to formally verify the Claude Agent SDK using Lean. A couple short prompts = 16 PRs fixing various bugs and race conditions. Video attached.
TLA+ also works well. I sometimes combine Lean and TLA+ to look for issues around data flow, concurrency, and state mgmt.
I don't know either language well, but Claude is excellent at both. This approach is super useful for formally modeling your code and finding bugs that a human probably wouldn't have spotted.
Is formal verification the future of coding (or at least, bug finding)?
JOSΞ retweeted
New coolest thing I’ve seen AI do…
Opus 5.5 designing LEGO 👀
I asked it to design a Microduck I can build with real LEGO pieces. It:
> designed it life-size using 1113 real LEGO parts
> verified: 3,204 connections, 0 collisions, every step buildable, centre of mass inside the feet 🤯
> made a 141-page LEGO-style booklet (237 steps)
> priced every piece in the browser and prepared the orders on BrickLink
JOSΞ retweeted
ok now I find the best Jev use case
🤖 Made with AI
I shared 10 Jev use cases for marketers.
Here are 10 more:
11. Ad creative scoring - Feed it 100 ad variations. Jev can score which hooks, headlines, or angles are most worth testing first.
12. Social post filtering - Monitor thousands of posts. Jev can flag the ones worth replying to, reposting, or using as sales signals.
13. ICP detection - Give it a company, profile, or website. Jev can score how closely it matches your ideal customer.
14. Buying signal detection - Someone posts that they're switching tools, hiring, raising money, or struggling with a problem.
15. Comment prioritization - Get hundreds of comments across LinkedIn, X, YouTube, or Product Hunt. Jev can score which ones deserve a reply first.
16. Review analysis - Feed it thousands of customer reviews. Jev can classify sentiment, complaints, feature requests, and purchase intent.
17. Influencer matching - Give it 5,000 creators. Jev can score which ones best match your product, audience, and campaign.
18. Sponsorship qualification - Feed it newsletters, podcasts, or creator media kits. Jev can score audience fit, relevance, and whether they're worth reviewing.
19. UGC selection - Give it dozens of videos, screenshots, and testimonials. Jev can score which ones are strongest for ads or landing pages.
20. Product Hunt monitoring - Scan launches, comments, and makers to find competitors, customers, partners, or interesting products.
The more repetitive marketing decisions you have to make at scale, the more interesting Jev becomes.
