Show HN: Typedframes – Pandas/polars column name checking at lint time https://ift.tt/blBLuNg

Show HN: Typedframes – Pandas/polars column name checking at lint time https://ift.tt/WziVekB June 7, 2026 at 03:32AM

Show HN: Resonate – Low-latency, high-resolution spectral analysis https://ift.tt/LZCkxMu

Show HN: Resonate – Low-latency, high-resolution spectral analysis Last April I shared about my Resonate project here ( https://ift.tt/uGF07fQ ) A lot has happened since: the work I presented in much more detail at last June's International Computer Music Conference (ICMC) got best paper award. I also gave a talk at the Audio Developer Conference in Bristol last November, the video is on YouTube). This year's work, which I recently presented at this year's ICMC, starts with known techniques from the phase vocoder literature to build self-tuning filter banks that extract very efficiently the frequency components that are actually present in the input signal. Overview on the project website, more details in the papers, including applications to super-resolution spectrograms and re-synthesis experiments. As many people have pointed out, none of the techniques I have used are new (some of them even have different names across different fields), but I haven't seen them applied together in this way, and to me the results are incredibly satisfying and sometimes look magical. See for example this demo: https://youtu.be/LasdoIJJkw8 Of course the best way to experience in person is through the free demo app: https://ift.tt/k4V5jdU Looking forward to feedback from the community! https://ift.tt/Oxc31La June 7, 2026 at 01:09AM

Show HN: Ccgs – Collaborative Claude Code sessions, stored in Git branches https://ift.tt/a5LTeUx

Show HN: Ccgs – Collaborative Claude Code sessions, stored in Git branches My team uses Claude Code daily, and the sessions have become some of the most useful artifacts we produce. But they're trapped in ~/.claude/projects/ on whichever laptop they happened on. There's no good way to hand a colleague "the session where I untangled the migration" so they can claude --resume it and keep going from where I left off. Enter ccgs: Share Claude Code sessions through an orphan branch (@ccgs/) in your existing repo's remote - Session files carry the author's absolute paths. On pull, ccgs rewrites the working dir back to your path so resume actually works — surgically editing only the structural cwd field, not a blind find-and-replace that would happily corrupt the transcript. - Everything goes through git plumbing (hash-object/commit-tree/update-ref) against a throwaway index. It never touches your working tree, index, or current branch, and it's fine with a dirty tree. It will not git checkout something behind your back. To try it without installing: `npx claude-git-sessions`. This also incidentally allows you to move a directory and carry the claude code transcripts with it (just push first, then move the directory, then pull) IMPORTANT CAVEAT: Unless you have a very good security hygiene, your Claude Code sessions are likely full of sensitive information such as environment secrets. Use with caution and avoid using on public repositories. Branches used by ccgs are prefixed by `@ccgs/` so you can easily filter them out. This project was written by and with Claude Code. This Show HN was not. (Reposted with URL fixed) https://ift.tt/xXdmpH8 June 6, 2026 at 11:04PM

Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk https://ift.tt/6AmawyR

Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk Hi! This is an infinite canvas note-taking tool where notes are laid out in a non-Euclidean, hyperbolic geometric space. As you drag and navigate through the view, you’ll experience a unique fluid distortion that naturally leverages your brain's spatial memory. I’ve been obsessed with the concept of space in HCI for years. Many modern UI patterns are essentially workarounds for the lack of screen real estate. While researching zoom-based UIs a while back, I stumbled upon old HCI papers that used the Poincaré disk model of the hyperbolic plane to organize data. It elegantly projects an infinite space into a finite disk, keeping everything contextually visible. I wanted to build an experimental app around this concept years ago, but the non-Euclidean math was a significant roadblock. Recently, I decided to give it a shot with the help of LLMs. It turns out that LLMs can handle the mathematical heavy lifting quite well, specifically in designing the coordinate systems and optimization algorithms, provided that you guide them with a solid architectural design. This is still an experimental demo, but I hope it leaves an impression. I’d love to know if you find this paradigm practical for organizing your thoughts. https://uonr.github.io/poincake/ June 2, 2026 at 11:08PM

Show HN: Bash Runtime for AWS Lambda https://ift.tt/0D9N6PH

Show HN: Bash Runtime for AWS Lambda Hi HN, I built a Bash runtime for AWS Lambda to make writing glue code simpler and faster. Sometimes, all you need is a bit of `sed`, `awk`, maybe a loop and a few HTTP API calls, and this runtime gives you all the tools to do that. It comes bundled with `jq` and `curl` so you can handle JSON payloads and string together HTTP API calls right out of the box, including calling AWS services with `curl --aws-sigv4`. In keeping with the theme, the Lambda handler contract is also made as simple as practical: read from stdin, write to stdout, return 0 for success and non-0 for error. You can run shell scripts, call binaries (either what's available in `al2023.provided` or you can package your own static binaries with your handler), or a combination of both. If you remember nodding along to Adam Drake's post about how bash and coreutils can be faster than a Hadoop cluster, I hope you give this a whirl and find it useful. The runtime is packaged as a Lambda layer, so it should drop right into your normal AWS infrastructure. https://ift.tt/d7uwzFN June 6, 2026 at 02:12AM

Show HN: MimicScribe – transcriber with ~97% accurate on-device speaker IDing https://ift.tt/lVmoPIf

Show HN: MimicScribe – transcriber with ~97% accurate on-device speaker IDing I’ve spent the last seven months building a tool I wish I’d had in my previous roles. MimicScribe is a macOS menu bar app that fits the "AI notetaker" category. It has accurate on-device speaker identification (a first possibly?), real-time meeting talking points for discovery calls, and a fully keyboard- and voice-driven interface. I believe the accuracy of the speaker ID system is its biggest strength. I used fluid audio’s port of ( https://ift.tt/fPnWwcH ) Pyannote's community-1 as a base. To improve accuracy, the system uses grammar structure cues from the Parakeet STT to mask by sentence. By taking a second set of samples within that mask for cluster assignment, it leverages the fact that most people don’t finish each other's… sandwiches in business meetings. It tends to slightly oversegment, as I’ve found it much easier to merge segments or reassign a speaker than it is to untangle an incorrect merge. The app provides in-meeting talking points using a prompt tuned for discovery type calls. It can suggest probing questions to help you extract more detail or helps you refocus on the big picture with “magic wand” type questions (e.g. “how would your ideal system work”). Getting low latency models to provide novel, relevant, and totally not hallucinated information is a bit of a reach and it tends to restate the transcript frequently but little gems do come from it sometimes so it’s best to think of it as a source of inspiration and be a vigilant gatekeeper. It’s set up so recording can be started and ended via holding a keyboard shortcut instead of connecting to your calendar service. I prefer this for privacy and to keep transcript history from getting cluttered. Tapping the shortcut shows and hides an always-on-top overlay on your active screen regardless of whether you have other apps full-screen or not. Beyond simple navigation, you can also use voice commands to make post-meeting corrections or additions, for instance, you can simply say "merge this speaker with that speaker" to clean up the transcript. It also has push-to-talk/dictate functionality with LLM cleanup - what the app started as but that tool was developer catnip, soo many of them. A developer friend who’s worked in finance reviewed the site and said he’d bounce because the privacy story wasn’t strong enough so I added a completely on-device mode and a bring-your-own-key option. Using cloud models does add a lot to the experience, including context aware speaker merging and fragment cleanup, summary items during meetings, action items attributed, etc. On-device mode is completely free and the speaker identification is still very useful. The privacy story is my biggest worry with the app, particularly since its target audience is more technical people. I’d love to get people's thoughts on it and any feedback would be super helpful. https://ift.tt/3fU4FJ8 June 6, 2026 at 12:33AM

Show HN: SnapToCode – Screenshot any UI and get clean Tailwind code https://ift.tt/n8VrsZb

Show HN: SnapToCode – Screenshot any UI and get clean Tailwind code https://ift.tt/f9v8WSB June 6, 2026 at 12:05AM

Show HN: A Simplistic UI for Rich Hickey's Design in Practice https://ift.tt/JaBM034

Show HN: A Simplistic UI for Rich Hickey's Design in Practice For making it easier to iterate with an LLM on Decision Matrices. Try it: https://bmillare.github.io/design_in_practice_ui/ https://ift.tt/2FWYh6o June 5, 2026 at 11:09PM

Show HN: Bot or Not – Spot AI-generated randomness https://ift.tt/A19l3WZ

Show HN: Bot or Not – Spot AI-generated randomness https://play-bot-or-not.vercel.app/ June 5, 2026 at 02:56AM

Show HN: Cost.dev (YC W21) – making agents cost-aware and cheaper to call https://ift.tt/2iHZRVo

Show HN: Cost.dev (YC W21) – making agents cost-aware and cheaper to call We launched Infracost on HN five years ago ( https://ift.tt/qyGdZWr ) where our CLI generated cost estimates for infra-as-code, e.g. "this Terraform PR adds $400/mo". The idea was to shift cloud costs (FinOps) left, so engineers get visibility of costs before deployment and make better decisions. Earlier this year we started seeing agent traffic in our logs and it looked like coding agents were calling our CLI. But that CLI wasn't designed with coding agents in mind. We went down a philosophical rabbit hole to see if a CLI is even needed anymore given that Claude, Copilot et al. already follow best practices. Ultimately we decided to create a new CLI from the ground up with coding agents in mind for two reasons: 1. We optimized the CLI for agent callers and cut Claude's output token usage by up to 79% and API cost by up to 67% versus a bare-Claude baseline. We wrote a blog documenting our lessons on optimizing user token usage when designing a CLI, e.g. using predicate flags so the agent doesn't compose jq | python | wc pipelines, output format that strips JSON's redundant field names. The blog is here: https://ift.tt/8VK5JcQ... 2. With cloud costs, precision matters. Telling a coding agent "make this Terraform cost-optimized" can be expensive and lossy. You burn tokens loading code and policy context into every conversation. Your agent could make up a price and you wouldn't know because it's difficult to verify that across the ~10M price points that AWS, Azure and Google have. The CLI runs static analysis on the code, uses the latest prices from cloud vendors, and passes that context to the coding agent. So that's what we're launching today - Cost.dev: https://cost.dev/ . - It runs locally. Your code never leaves your machine, you get a fast feedback loop, and you're not burning API calls per character when you want to fetch prices. - The CLI does the deterministic work. Fetching price points, scanning the code, validating fixes. The coding agent does the natural-language part. You don't have to trust the LLM to remember the rules, and can verify it called the right CLI command. - It provides a consistent rule layer across every tool you use. Get cost estimates in your IDE and your coding agent with a single install. We support Claude Code, GitHub Copilot, Cursor, Windsurf, OpenAI Codex, Gemini CLI, as well as IDEs like VS Code and JetBrains Before we keep building more in that direction, I want to sanity-check with HN: is "agents writing IaC in prod" actually a thing yet, or am I betting on a future that's still a year out? I know software developers are using coding agents heavily, but are platform/infra folks doing that for prod too? Also, if you have any feedback on Cost.dev, I'd love to hear it! https://cost.dev/ June 4, 2026 at 06:30PM

Show HN: ClearLogo – a logo API that returns usable logos, not raw files https://ift.tt/MhH1tZO

Show HN: ClearLogo – a logo API that returns usable logos, not raw files https://ift.tt/Tdn6avw June 4, 2026 at 09:28PM

Show HN: Capture, compress, and copy screenshots to clipboard https://ift.tt/YKqU1mH

Show HN: Capture, compress, and copy screenshots to clipboard https://ift.tt/TvaPJAE June 3, 2026 at 11:46PM

Show HN: Rscrypto, pure-Rust crypto with industry leading public benches https://ift.tt/DpJAUM5

Show HN: Rscrypto, pure-Rust crypto with industry leading public benches https://ift.tt/I7y69Rb June 3, 2026 at 11:41PM