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
Telecom service apps require data purchases to access login or basic functions
Users cannot check balances, support, or services without buying bundles first, blocking access and frustrating customers reliant on the provider.
X5mo agoToolBusiness
Bug bounty platforms delay responses to vulnerability reports for months with no communication
Ethical hackers submit bugs to bounty programs but receive no acknowledgment or feedback for extended periods, creating frustration and temptation to exploit maliciously instead.
X5mo agoToolDev
SaaS apps default to chat UIs forcing users to restate needs on every login
Non-general-purpose apps lack persistent interfaces or personalization, making users repeat queries each time due to misguided chatbot hype over user empathy.
X5mo agoToolProductivity
No reliable app to track followers and detect inactive accounts on social media
Users need an app to monitor who follows them and identify inactive accounts, indicating current tools are insufficient or unavailable.
X5mo agoToolProductivity
AI agents overload with unconsolidated memory, breaking usefulness over time
AI agents remember everything without proper memory consolidation, leading to bloated, inaccurate, or unusable context that degrades performance and requires manual intervention.
X5mo agoToolOther
Fast fashion delivery with friction-free returns
On-demand fashion shopping with same-day or next-day delivery and instant returns, reducing the friction of online fashion retail.
YC Graveyard4y agoToolE-Commerce
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 News5mo 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 News5mo 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 News5mo agoToolAI
Every CEO and CFO change at US public companies, live from SEC
Built this solo. It watches SEC filings for executive and board changes, extracts the data, and shows it in real time. 2,100+ changes in the last 30 days. The comp data is interesting: average new CEO total comp is $8.4M across 284 appointments. The /explore page is fully open, no login needed.
Hacker News5mo agoToolDesign & Creative
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 News5mo 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 News5mo agoToolAI
University students lack ABNT formatting skills even in later semesters
Brazilian university students in 5th semester and beyond still don't know how to properly use ABNT norms for academic papers, leading to frustration in group work where members have to redo formatting. Current tools or education fail to make it intuitive.
X5mo agoToolEducation
Small businesses can't afford or find suitable group health insurance
Small business owners struggle to provide reasonable health insurance plans for teams and families due to high costs ($1000+/month premiums) and limited options. Employees often waive coverage to save money, rolling the dice on health risks, as current plans are unaffordable and inadequate.
X7mo agoOtherBusiness
Schengen travelers risk border issues from poor stay tracking
Individuals struggle to accurately track their 90/180-day Schengen visa compliance manually, leading to potential border denials; simple tools save users from real problems.
X5mo agoToolTravel
AI code generation demotivates developers
AI makes coding feel un-fun and unnecessary for manual work, while hand-coding seems tedious, paralyzing developers and reducing enjoyment.
X6mo agoToolDev
Small businesses overspend on managing multiple SaaS integrations
Small businesses rely on 5+ SaaS tools but lose the equivalent of a full-time secretary's salary annually on manual integrations and management. Custom or better integrated solutions are needed as fragmented tools hinder efficiency without seamless connectivity.
X5mo agoToolProductivity
Small businesses manually handle data transfers, quotes, status meetings, and follow-ups
Every small business faces the same issues: manual data movement between systems, recreating quotes from scratch, unnecessary status update meetings, and chasing un-automated follow-ups. Existing tools aren't connected, wasting owner time despite revenue growth.
X5mo agoToolBusiness
Helping non-technical builders navigate go-to-market and selling after building software
Non-technical people who build functional software get stuck in a 'valley of despair' because they don't know how to market, sell or get users to pay for their product.
X5mo agoArticleVC & Startups