Ideas Lab
Real problems people complain about online, pulled every morning and scored out of 100. Build, validate, or skip. How scoring works
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- 11h ago
Kampala (YC W26) – Reverse-Engineer Apps into APIs
Hey! I am Alex and together with my co-founder Tarun built Kampala (https://www.zatanna.ai/kampala). It’s a man-in-the-middle (MITM) style proxy that allows you to agentically reverse engineer existing workflows without brittle browser automation or computer use agents. It works for websites, mobile apps, desktop apps.Demo: https://www.youtube.com/watch?v=z_PeostC-b4. Many people spend hours per day in legacy dashboards and on-prem solutions reconciling data across platforms. Current attempts at automation use browser automations or computer use agents which are brittle, slow, and nondeterministic. I come from a web reverse engineering background and spent the last 7-8 years building integrations by hand for sneaker/ticket releases, sportsbooks logins, and everything in\ between. During that time I consulted for several companies and brought them off of browser based infrastructure into the requests layer.When we started Zatanna (that’s our company name) we worked in dental tech, which meant we had to deal with tons of insurance payer dashboards and legacy dental-practice solutions. Our superpower (as a fairly undifferentiated voice agent/front desk assistant company) was that we could integrate with nearly any system requested. During this time we built extensive tooling (including what we’re now calling Kampala) to allow us to spin up these integrations quickly. Existing MITM proxies and tooling didn’t work for a few reasons: (1) They manipulated the TLS and HTTP2 fingerprint over the wire which was detected by strict anti-bots. (2) They had bad MCPs which did not adequately expose necessary features like scripts/replay. (3) They did not allow for building workflows or actions given a sample or sequence of requests.As the tools we built got more powerful, we began to use them internally to scrape conference attendees, connect to external PMS systems, and interact with slack apps. I even sent it to my property manager
Hacker News6mo agoToolAI
CodeBurn – Analyze Claude Code token usage by task
Built this after realizing I was spending ~$1400/week on Claude Code with almost no visibility into what was actually consuming tokens.Tools like ccusage give a cost breakdown per model and per day, but I wanted to understand usage at the task level.CodeBurn reads the JSONL session transcripts that Claude Code stores locally (~/.claude/projects/) and classifies each turn into 13 categories based on tool usage patterns (no LLM calls involved).One surprising result: about 56% of my spend was on conversation turns with no tool usage. Actual coding (edits/writes) was only ~21%.The interface is an interactive terminal UI built with Ink (React for terminals), with gradient bar charts, responsive panels, and keyboard navigation. There’s also a SwiftBar menu bar integration for macOS.Happy to hear feedback or ideas.
Hacker News6mo agoToolAI
Easiest UX for Seniors
I have been running a SaaS for ~10 years used heavily by people 65+ and a lot of them are tired and frustrated about remembering the domain/path to login screen and then which email/password they used, having to go through the whole forgot-password-flow, etc. I have tried simplifying this as much as i can but I feel like there must be better options. Google sigin in is confusing for them because they get thrown into Googles horrible UX flow where they might have multiple accounts and they don't like when the website suddenly changes.In general, what is the best way to simplify the auth UX for this group of users? Is there any UI libraries out there targeting this group more specifically? Any good web examples you know of?thx
Hacker News6mo agoToolAI
Kelet – Root Cause Analysis agent for your LLM apps
I've spent the past few years building 50+ AI agents in prod (some reached 1M+ sessions/day), and the hardest part was never building them — it was figuring out why they fail.AI agents don't crash. They just quietly give wrong answers. You end up scrolling through traces one by one, trying to find a pattern across hundreds of sessions.Kelet automates that investigation. Here's how it works:1. You connect your traces and signals (user feedback, edits, clicks, sentiment, LLM-as-a-judge, etc.) 2. Kelet processes those signals and extracts facts about each session 3. It forms hypotheses about what went wrong in each case 4. It clusters similar hypotheses across sessions and investigates them together 5. It surfaces a root cause with a suggested fix you can review and applyThe key insight: individual session failures look random. But when you cluster the hypotheses, failure patterns emerge.The fastest way to integrate is through the Kelet Skill for coding agents — it scans your codebase, discovers where signals should be collected, and sets everything up for you. There are also Python and TypeScript SDKs if you prefer manual setup.It’s currently free during beta. No credit card required. Docs: https://kelet.ai/docs/I'd love feedback on the approach, especially from anyone running agents in prod. Does automating the manual error analysis sound right?
Hacker News6mo agoToolAI
A memory database that forgets, consolidates, and detects contradiction
Vector databases store memories. They don't manage them. After 10k memories, recall quality degrades because there's no consolidation, no forgetting, no conflict resolution. Your AI agent just gets noisier.YantrikDB is a cognitive memory engine — embed it, run it as a server, or connect via MCP. It thinks about what it stores: consolidation collapses duplicate memories, contradiction detection flags incompatible facts, temporal decay with configurable half-life lets unimportant memories fade like human memory does.Single Rust binary. HTTP + binary wire protocol. 2-voter + 1-witness HA cluster via Docker Compose or Kubernetes. Chaos-tested failover, runtime deadlock detection (parking_lot), per-tenant quotas, Prometheus metrics. Ran a 42-task hardening sprint last week — 1178 core tests, cargo-fuzz targets, CRDT property tests, 5 ops runbooks.Live on a 3-node Proxmox homelab cluster with multiple tenants. Alpha — primary user is me, looking for the second one.
Hacker News6mo agoToolAI
Libretto – Making AI browser automations deterministic
Libretto (https://libretto.sh) is a Skill+CLI that makes it easy for your coding agent to generate deterministic browser automations and debug existing ones. Key shift is going from “give an agent a prompt at runtime and hope it figures things out” to: “Use coding agents to generate real scripts you can inspect, run, and debug”.Here’s a demo: https://www.youtube.com/watch?v=0cDpIntmHAM. Docs start at https://libretto.sh/docs/get-started/introduction.We spent a year building and maintaining browser automations for EHR and payer portal integrations at our healthcare startup. Building these automations and debugging failed ones was incredibly time-consuming.There’s lots of tools that use runtime AI like Browseruse and Stagehand which we tried, but (1) they’re reliant on custom DOM parsing that's unreliable on older and complicated websites (including all of healthcare). Using a website’s internal network calls is faster and more reliable when possible. (2) They can be expensive since they rely on lots of AI calls and for workflows with complicated logic you can’t always rely on caching actions to make sure it will work. (3) They’re at runtime so it’s not interpretable what the agent is going to do. You kind of hope you prompted it correctly to do the right thing, but legacy workflows are often unintuitive and inconsistent across sites so you can’t trust an agent to just figure it out at runtime. (4) They don’t really help you generate new automations or help you debug automation failures.We wanted a way to reliably generate and maintain browser automations in messy, high-stakes environments, without relying on fragile runtime agents.Libretto is different because instead of runtime agents it uses “development-time AI”: scripts are generated ahead of time as actual code you can read and control, not opaque agent behavior at runtime. Instead of a black box, you own the code and can inspect, modify, version, and debug
Hacker News6mo agoToolAI
LangAlpha – what if Claude Code was built for Wall Street?
Some technical context on what we ran into building this.MCP tools don't really work for financial data at scale. One tool call for five years of daily prices dumps tens of thousands of tokens into the context window. And data vendors pack dozens of tools into a single MCP server, schemas alone can eat 50k+ tokens before the agent does anything useful. So we auto-generate typed Python modules from the MCP schemas at workspace init and upload them into the sandbox. The agent just imports them like a normal library. Only a one-line summary per server stays in the prompt. We have around 80 tools across our servers and the prompt cost is the same whether a server has 3 tools or 30. This part isn't finance-specific, it works with any MCP server.The other big thing was making research actually persist across sessions. Most agents treat a single deliverable (a PDF, a spreadsheet) as the end goal. In investing that's day one. You update the model when earnings drop, re-run comps when a competitor reports, keep layering new analysis on old. But try doing that across agent sessions, files don't carry over, you re-paste context every time. So we built everything around workspaces. Each one maps to a persistent sandbox, one per research goal. The agent maintains its own memory file with findings and a file index that gets re-read before every LLM call. Come back a week later, start a new thread, it picks up where it left off.We also wanted the agent to have real domain context the way Claude Code has codebase context. Portfolio, watchlist, risk tolerance, financial data sources, all injected into every call. Existing AI investing platforms have some of that but nothing close to what a proper agent harness can do. We wanted both and couldn't find it, so we built it and open-sourced the whole thing.
Hacker News6mo agoToolAI
AI-accelerated development produces low-quality UX
Companies building software rapidly with AI overlook basic UX issues, resulting in frustrating products that customers endure despite dissatisfaction.
X7mo agoToolAI
AI tools generate incomplete and buggy code updates
AI coding assistants like Grok provide supposedly complete code but omit sections, make undocumented changes, and introduce new errors while fixing others.
X6mo agoToolAI
Indian MSMEs cannot access affordable AI workflow automation
MSMEs in India rely on basic tools like WhatsApp and Excel because enterprise AI solutions are prohibitively expensive (lakhs per month), needing practical affordable automation.
X7mo agoToolAI
AI agents lack identity and authentication infrastructure
As AI agents evolve into digital workers, they require dedicated authentication systems, session management, and access control to securely log into services like humans do.
X6mo agoToolAI
Do you trust AI agents with API keys / private keys?
are you ok sharing secrets or api keys to you ai agent via .env?or is there any other tool or mechanism that one use to safegaurd from potential exploit or leaks
Hacker News6mo agoToolAI
QVAC SDK, a universal JavaScript SDK for building local AI applications
Hi folks, today we're launching QVAC SDK [0], a universal JavaScript/TypeScript SDK for building local AI applications across desktop and mobile.The project is fully open source under the Apache 2.0 license. Our goal is to make it easier for developers to build useful local-first AI apps without having to stitch together a lot of different engines, runtimes, and platform-specific integrations. Under the hood, the SDK is built on top of QVAC Fabric [1], our cross-platform inference and fine-tuning engine.QVAC SDK uses Bare [2], a lightweight cross-platform JavaScript runtime that is part of the Pear ecosystem [3]. It can be used as a worker pretty much anywhere, with built-in tooling for Node, Bun and React Native (Hermes).A few things it supports today: - Local inference across desktop, mobile and servers - Support for LLMs, OCR, translation, transcription, text-to-speech, and vision models - Peer-to-peer model distribution over the Holepunch stack [4], in a way that is similar to BitTorrent, where anyone can become a seeder - Plugin-based architecture, so new engines and model types can be added easily - Fully peer-to-peer delegated inference We also put a lot of effort into documentation [5]. The docs are structured to be readable by both humans and AI coding tools, so in practice you can often get pretty far with your favorite coding assistant very quickly.A few things we know still need work: - Bundle sizes are larger than we want right now because the current packaging of Bare add-ons is not as efficient as it should be yet - Plugin workflow can be simpler - Tree-shaking is already possible, but at the moment it still requires a CLI step, and we'd like to make that more automatic and better integrated into the build process This launch is only the beginning. We want to help people build local AI at a much larger scale. Any feedback is truly appreciated! Full vision is available on the official website [6].References:[0] S
Hacker News6mo agoToolAI
boringBar – a taskbar-style dock replacement for macOS
Hi HN!I recently switched from a Fedora/GNOME laptop to a MacBook Air. My old setup served me well as a portable workstation, but I’ve started traveling more while working remotely and needed something with similar performance but better battery life. The main thing I missed was a simple taskbar that shows the windows in the current workspace instead of a Dock that mixes everything together.I built boringBar so I would not have to use the Dock. It shows only the windows in the current Space, lets you switch Spaces by scrolling on the bar, and adds a desktop switcher so you can jump directly to any Space. You can also hide the system Dock, pin apps, preview windows with thumbnails, and launch apps from a searchable menu (I keep Spotlight disabled because for some reason it uses a lot of system resources on my machine).I’ve been dogfooding it for a few months now, and it finally felt polished enough to share.It’s for people who like macOS but want window management to feel a bit more like GNOME, Windows, or a traditional taskbar. It’s also for people like me who wanted an easier transition to macOS, especially now that Windows feels increasingly user-hostile.I’d love feedback on the UX, bugs, and whether this solves the same Dock/Spaces pain for anyone else.P.S. It might also appeal to people who feel nostalgic for the GNOME 2 desktop of yore. I started my Linux journey with it, and boringBar brings back some of that feeling for me.
Hacker News6mo agoToolAI
Pardonned.com – A searchable database of US Pardons
https://pardonned.comInspired by the videos of Liz Oyer, I wanted to be able to verify her claims and just look up all the pardons more easily.Tech Stack: Playwright - to sccrape the DOJ website SQLite - local database Astro 6 - Build out a static website from the sqlite dbAll code is open source and available on Github.
Hacker News6mo agoToolAI
Waffle – Native macOS terminal that auto-tiles sessions into a grid
Hi HN. I built Waffle because I kept ending up with 15 terminal windows scattered across three spaces with no idea what was running where.Splitting/merging in iTerm kind of works but it never felt intuitive to me.With that in mind, I built something to suit my workflow:Waffle is a native macOS terminal (Built on Miguel de Icaza's SwiftTerm) that tiles your sessions into an auto-scaling grid automatically. 1 session is fullscreen, 2 is side by side, 4 is 2x2, 9 is 3x3. Open a terminal, it joins the grid. Close one, the grid rebalances. No splitting, no config.I've been using it a lot recently and one thing I've found really useful is that sessions detect which repo they're in and group accordingly. Each project gets a distinct colour. Cmd+[ and Cmd+] flip between groups. If you have three repos open across eight terminals, you can filter to just one project's sessions instantly. Also, no accidentally closing a window with CMD-W as it gives you a confirmation and requires a second CMD-W to close.Honestly, if you live in tmux, this probably isn't for you but it's really helped to speed up my workflow.Other things: It comes with a handful of themes (and has support for iTerm themes), bundled JetBrains mono, has keyboard shortcuts for everything. Free, no account, opt-in analytics only. macOS 14+.There's a demo on the landing page if you want to see it in action.
Hacker News6mo agoToolAI
Claudraband – Claude Code for the Power User
Hello everyone.Claudraband wraps a Claude Code TUI in a controlled terminal to enable extended workflows. It uses tmux for visible controlled sessions or xterm.js for headless sessions (a little slower), but everything is mediated by an actual Claude Code TUI.One example of a workflow I use now is having my current Claude Code interrogate older sessions for certain decisions it made: https://github.com/halfwhey/claudraband?tab=readme-ov-file#s...This project provides:- Resumable non-interactive workflows. Essentially `claude -p` with session support: `cband continue <session-id> 'what was the result of the research?'` - HTTP server to remotely control a Claude Code session: `cband serve --port 8123` - ACP server to use with alternative frontends such as Zed or Toad (https://github.com/batrachianai/toad): `cband acp --model haiku`. - TypeScript library so you can integrate these workflows into your own application.This exists cause I was using `tmux send-keys` heavily in a lot of my Claude Code workflows, but I wanted to streamline it.
Hacker News6mo agoToolAI
AI agents lack persistent memory
AI agents cannot retain knowledge or learn from previous sessions, forcing developers to restart context every time.
X6mo agoToolAI