I think the trick to using libraries like this is to not go all in on them. Applying these effects to every element would be garish.
But for a single like button, an effect slider, or magic search bar? It would be be a lovely touch.
HN user
http://peticol.as
I think the trick to using libraries like this is to not go all in on them. Applying these effects to every element would be garish.
But for a single like button, an effect slider, or magic search bar? It would be be a lovely touch.
Just 25 years too late to be used to design Jelly World
I agree. We're seeing more variants of "RAG" that aren't semantic at all (e.g. coding agents or simple memory systems that feed summary indexes directly into context).
I think, over time, it's going to become a SQL / NoSQL sort of divide. There will be the right kind of RAG for the job and lots of forcing the wrong kind because the developer doesn't understand the nuances.
Wow. This is so freaking cool.
I say this with a lot of love: The vibecoded applications in your demo reek of AI slop design.
This isn't a critique of your product. It's just that the a beige-orange theme, the pill components, and the left-border highlight give me that visceral reaction as reading a paragraph littered with em dashes and "not X but Y." It makes me take you less seriously.
Cool demo otherwise.
Apt for self-hosting
Oil changes aren't the best example. They're pretty easy to do at home for basically everything and filters are pretty standardized.
But car batteries, brake pads, tire pressure sensors are all becoming increasingly software-locked in. We're lacking open standards for this stuff.
Why does AI want to stress me with that cup about to fall off the desk
Eh, it was the exact same system for the Switch 2 and no one I know waited more than a week for theirs.
Given it requires a Steam login of a certain age to register, I suspect this is just to limit the scalpers.
pause for 5 seconds between responses
I'm sure I'm not the only one, but I've gotten so aggressive about monitoring for this. I do most interviews zoomed in on the candidate's eyes and I rubric on how they "thought" through the problem, not just the results.
Thankfully the interview tools are catching on as well and now tracking this like browser focus, number of monitors, window size, and sending notifications when any of those change.
This is an insane take.
Also wrong, gay marriage had 60% support before Obergefell v. Hodges.
I have one of these. Basically dead with modern MacOS but runs Linux Mint XFCE really well.
OpenAI API also supports defer_loading https://developers.openai.com/api/docs/guides/tools-tool-sea...
And it's not actually necessary for it to exist at the API level. It's a pattern. Making it API-side is just an optimization.
To do it client-side: 1. Define a single tool, tool_search 2. List the names of your deferred tools in context (or tool_search's description) 3. When tool_search is called, match the query against the tool names (or names + descriptions) 4. Append the matched tool def to the context in a new <system>-esque tag
Claude Code (as of the leak) does this client side. You can even see the custom matching function and A/B tests about whether to include the descriptions.
Whether or not that tool definition comes from MCP or a local definition is kind of beside the point.
+1
Its crazy that people are still discussing this. It's ancient history. Deferred tool loading, large contexts, and prompt caching have made 2026 completely different from 2025.
Also, the "CLI saves token" debate really falls apart when step one of using the CLI is running "--help". The problem remains: if knowing how to call the thing isn't in parametric memory, it has to be in context.
There was a time, in the early to mid 2010s, when the phrase "Fake News" was almost exclusively used by people in publishing to talk about a very real rise in editorial disruption as news readers shifted from being desktop and homepage-driven to mobile and facebook-driven.
And then, one day, the politicians started saying it...
I work for an "AI-native" company now and have found this to be the case.
EVERYONE (engineers, pms, managers, sales) uses Claude Code to read and write Google Docs (google workspace mcp). Ideas, designs, reports. It's too much for one person to read and, with a distributed async team, there's an endless demand for more.
So for every project there's always one super Google Doc with 50 tabs and everyone just points their claude code at it to answer questions. It's not to be read by a human, it's just context for the agent.
If that's true, it's very unsustainable.
Gemma-4 26B-A4B + M5 MacBook Pro + OpenCode isn't Claude Code _yet_, but it's good enough that if I were forced to use it I would be fine.
I love the batteries included in Helix. Just the right amount that I don't need much else.
At this point I just want a decent Helix-Evil-Mode.
I had a few years of writing clojure for work ten years ago and it's still my mental model of how I think about programming.
TheVerge launched a full RSS Feed for paid subscribers about a year ago and I've never so happily subscribed to something.
I feel the same about Claude Code. It's a fast but average developer at just about everything and there are some things that average developers are just consistently bad at and therefore Claude is consistently bad at.
That person's actions were only possible because the administration explicitly decided to put that much unchecked power into poorly vetted individuals.
I'm teaching a class in agent development at a university. First assignment is in and I'm writing a human-in-the-loop grader for my TAs to use that's built on top of Claude Agent SDK.
Phase 1: Download the student's code from their submitted github repo URL and run a series of extractions defined as skills. Did they include a README.md? What few-shot examples they provided in their prompt? Save all of it to a JSON blob.
Phase 2: Generate a series of probe queries for their agent based on it's system prompt and run the agent locally testing it with the probes. Save the queries and results to the JSON blob.
Phase 3: For anything subjective, surface the extraction/results to the grader (TA), ask them to grade them 1-5.
The final rubric is 50% objective and 50% subjective but it's all driven by the agent.
The truth is, God really gave 11 commandments.
It's just "Thou shalt not grow a brain in a test tube and force it to play a 1993 shooter" didn't make any sense to Moses and therefore didn't make the editors cut.
I wonder if it has to do with how meaning is tied to the tokens. c+amara+derie (using the official gpt-5 tokenizer).
There's also just that weird thing where they're obsessed with emoji which I've always assumed is because they're the only logograms in english and therefore have a lot of weight per byte.
Right now I'm working two AI-jobs. I build agents for enterprises and I teach agent development at a university. So I'm probably too deep to see straight.
But I think the future of programming is english.
Agent frameworks are converging on a small set of core concepts: prompts, tools, RAG, agent-as-tool, agent handoff, and state/runcontext (an LLM-invisible KV store for sharing state across tools, sub-agents, and prompt templates).
These primitives, by themselves, can cover most low-UX application business use cases. And once your tooling can be one-shotted by a coding agent, you stop writing code entirely. The job becomes naming, describing, and instructing and then wiring those pieces together with something more akin to flow-chart programming.
So I think for most application development, the kind where you're solving a specific business problem, code stops being the relevant abstraction. Even Claude Code will feel too low-level for the median developer.
The next IDE looks like Google Docs.
I also have and use this iPad. Mainly for procreate and watching things.
Even at 9 years old, I don't see myself upgrading in the foreseeable future.
This is beautiful and highly readable but, still, I yearn for a detailed line-by-line explainer like the backbone.js source: https://backbonejs.org/docs/backbone.html
True for coding agents running SotA models where you're the human-in-the-loop approving, less true for your deployed agents running on cheap models that you don't see what's being executed.
But yeah, a concrete example is playwright-mcp vs playwright-cli: https://testcollab.com/blog/playwright-cli
How is OP using Claude relevant?