Sunday, June 7, 2026

I want to build an app called "PoliticalOptOut". ## The Problem A person who made a single political donation now receives hundreds of emails and texts from unrelated candidates they've never supported and can't figure out how to get off the lists. ## Target Audience Anyone who has ever donated to a political party or campaign and is drowning in follow-up solicitations ## Core Idea One-click mass opt-out from political party email and SMS lists using FEC donor data matching. People who made a single political donation years ago find themselves on shared lists sold to hundreds of campaigns, receiving thousands of unsolicited emails and texts they never agreed to. PoliticalOptOut matches your contact info against known political list brokers using FEC public data, then sends TCPA-compliant opt-out requests in bulk on your behalf and monitors for re-addition. It also generates a suppression file you can send directly to the DNC or RNC. ## Monetization Strategy One-time $9.99 payment for a full opt-out sweep, with a $2.99/month monitoring subscription to catch re-additions ## Requirements - Category: Productivity - Difficulty: Week - Suggested stack: Next.js + localStorage or Supabase + PWA Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "Cork". ## The Problem People constantly save Instagram Reels and TikToks about restaurants and events but forget about them because they get buried in saves, with no location-aware reminder system. ## Target Audience Urban millennials and Gen Z who heavily use Instagram and TikTok to discover local food and events ## Core Idea Save Instagram Reels and TikToks about restaurants, events, and pop-ups, and get reminded when you're nearby. Cork lets you forward any social media video about a place or event directly from within the app, extracts the location and date automatically, and sends you a push notification when you're physically near that spot or when the event is coming up. It solves the universal frustration of saving hundreds of restaurant reels and never acting on them because they get buried. Clean map view, zero friction saving via share sheet. ## Monetization Strategy Free with premium at $3.99/mo for unlimited saves, collaborative lists, and calendar sync ## Requirements - Category: Productivity - Difficulty: Week - Suggested stack: Next.js + localStorage or Supabase + PWA Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "CloudSave". ## The Problem A founder with $1M ARR had their entire business killed overnight by a Google account suspension triggered by an exposed API key, and another lost their Stripe account by routing pre-seed funding through it — both with zero warning. ## Target Audience Early-stage startup founders and solo developers running production SaaS products ## Core Idea Monitor your startup's critical cloud and payment accounts for suspension risk before it kills your business overnight. Founders have lost six- and seven-figure businesses overnight when Google, Stripe, or AWS suspended their accounts with no warning, locking them out of everything at once. CloudSave continuously monitors your account health signals — API key exposure, unusual usage spikes, ToS-triggering patterns — across major cloud and payment providers and sends early alerts so you can act before a suspension happens. It also generates a one-click 'business continuity backup' with instructions to migrate critical services. ## Monetization Strategy $19/month per workspace covering up to 5 cloud accounts, with a free tier for 1 account and 30-day alert history ## Requirements - Category: SaaS - Difficulty: Month - Suggested stack: Next.js + Supabase + Stripe Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "PaymentSafe". ## The Problem Founders are losing entire businesses overnight when Google or Stripe silently suspends accounts with no warning and no recourse path, as described by multiple HN posts about $1M ARR companies going dark. ## Target Audience SaaS founders and indie hackers processing payments via Stripe or Google ## Core Idea A payment processor risk monitor that alerts founders before Stripe or Google freezes their account — with instant mitigation playbooks. PaymentSafe continuously monitors your Stripe, Google, and other payment accounts for risk signals and policy changes, alerting you before a freeze happens. It provides a step-by-step playbook the moment a freeze occurs, including who to call, what documents to prepare, and how to migrate revenue to a backup processor fast. Founders who lost $1M ARR overnight due to silent account suspensions are the core audience. ## Monetization Strategy $19/mo per connected payment account; free tier monitors one account with delayed alerts ## Requirements - Category: Fintech - Difficulty: Week - Suggested stack: Next.js + Plaid API + Stripe Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "Vaani Clips". ## The Problem Content creators produce great short-form video but lose global reach because dubbing into other languages produces robotic voices, destroys background music, and loses lip sync. ## Target Audience Short-form video creators on TikTok, Instagram, and YouTube Shorts with existing audiences in one language ## Core Idea Automatically dub short-form video content into 40 languages in the creator's original voice, optimized for Reels and TikTok dimensions. Vaani Clips is a lightweight web app where creators upload a short-form video and receive dubbed versions in up to 40 languages with preserved voice tone, background music, and lip-sync alignment — all within minutes. It targets the massive gap where creators have viral content in one language but can't affordably reach global audiences. Output files are pre-formatted for TikTok, Instagram Reels, and YouTube Shorts. ## Monetization Strategy Credit-based pricing — 10 free dubs on signup, then $0.50 per minute of dubbed video; $39/mo unlimited plan for power creators ## Requirements - Category: AI/ML - Difficulty: Month - Suggested stack: Next.js + Anthropic Claude API + Vercel AI SDK Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "TokenWatch". ## The Problem Developers are burning excessive LLM tokens due to over-provisioning model tier for simple tasks, and bad MCP designs that waste 5x more tokens than necessary. ## Target Audience Indie hackers, startups, and dev teams using LLM APIs at scale ## Core Idea Real-time LLM cost monitoring and intelligent model routing that automatically picks the cheapest model capable of completing each task. TokenWatch tracks your LLM API spending across providers in real-time and uses a classifier to route each request to the least expensive model that can handle it. Developers set quality thresholds and cost budgets, and TokenWatch enforces them automatically — similar to what posts describe achieving 3x usage for the same spend. Integrates via a drop-in SDK or proxy endpoint. ## Monetization Strategy Free tier up to $500/mo monitored spend, then 1% of monitored spend or $29/mo flat — whichever is lower ## Requirements - Category: Developer Tool - Difficulty: Week - Suggested stack: Node.js CLI or VS Code extension + TypeScript Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "SaaSLaunchpad". ## The Problem Technical founders — especially those in difficult personal situations — build working products but have no framework for marketing them and don't know where to start, leading to zero traction despite real solutions. ## Target Audience Solo technical founders and indie hackers who have launched or are about to launch a SaaS product ## Core Idea A step-by-step marketing and distribution playbook generator for solo founders who have built a product but have no idea how to get their first users. SaaSLaunchpad asks a founder 10 questions about their product, target audience, and constraints, then generates a prioritized 30-day marketing plan with specific actions, copy templates, subreddit targets, cold outreach scripts, and SEO quick wins. It directly addresses the overwhelm described by technical founders who are great at building but lost when it comes to marketing. Updates the plan weekly based on what's working. ## Monetization Strategy Free one-time plan generation; $19/mo for ongoing weekly plan updates, A/B copy variations, and community access ## Requirements - Category: SaaS - Difficulty: Week - Suggested stack: Next.js + Supabase + Stripe Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "TokenTrim". ## The Problem Developers are burning excessive LLM tokens on verbose CLI output and poorly designed MCP servers, with one builder reporting 91.8% token savings from manual filtering and others noting bad MCP design causes 5x token overhead. ## Target Audience Developers using AI coding agents like Claude Code or Codex ## Core Idea Automatically strip verbose CLI and log output before it hits your LLM agent, slashing token costs by up to 90%. Developers using AI coding agents waste enormous amounts of tokens feeding raw, noisy CLI output and logs into LLM context windows. TokenTrim sits as a middleware layer between your terminal and your AI agent, using configurable rules and ML-based noise detection to compress output while preserving semantically important lines. It supports Claude Code, Codex, and any MCP-compatible agent as a drop-in shell wrapper. ## Monetization Strategy Free CLI tool with a $9/month SaaS dashboard for team analytics, cost tracking, and shared filter presets ## Requirements - Category: Developer Tool - Difficulty: Week - Suggested stack: Node.js CLI or VS Code extension + TypeScript Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "AgentCost". ## The Problem Developers running LLM agents have poor visibility into per-agent token costs and lack tooling to automatically route to cheaper models, with multiple posts describing surprise bills and manual workarounds to reduce spend. ## Target Audience Indie hackers, startups, and developer teams running AI agents in production ## Core Idea Real-time LLM cost dashboard that tracks, alerts, and optimizes spending across all your AI agents and projects. Teams and solo developers running multiple AI agents have no unified view of what each agent, task, or project is actually costing them until the bill arrives. AgentCost integrates with OpenAI, Anthropic, and other LLM APIs to provide a real-time cost dashboard broken down by agent, session, and task type, with budget alerts and automatic model-routing recommendations to minimize spend. It also benchmarks your prompts to suggest cheaper equivalent models. ## Monetization Strategy $0 free tier for 1 project, $15/month Pro for unlimited projects and team seats, $49/month for enterprise with Slack alerts ## Requirements - Category: SaaS - Difficulty: Week - Suggested stack: Next.js + Supabase + Stripe Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "CorkMap". ## The Problem Users constantly save Instagram Reels and TikToks about restaurants and events but forget about them because they get buried in saves with no location-aware reminder system — a founder built a solution but couldn't get traction against flawed competitors. ## Target Audience Urban millennials and Gen Z who heavily use TikTok and Instagram for restaurant and event discovery ## Core Idea Save TikToks and Instagram Reels about places you want to visit and get reminded when you're actually nearby. People constantly save food, event, and travel content from social media but forget about it because saves get buried and there's no location-aware reminder system. CorkMap lets you forward any social media reel or video link to extract the venue or event, pins it on a personal map, and sends you a push notification when your phone's GPS puts you within walking distance. It works as both a standalone app and a Telegram bot for frictionless saving. ## Monetization Strategy Free app with a $3.99/month premium tier for unlimited saves, collaborative lists, and calendar sync ## Requirements - Category: Productivity - Difficulty: Week - Suggested stack: Next.js + localStorage or Supabase + PWA Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "SaaSMarketer". ## The Problem A laid-off developer in a third-world country supporting a family of 5 built a SaaS product but explicitly says they have no idea how to market it, reflecting a widespread gap between technical building ability and go-to-market knowledge. ## Target Audience Non-native English speaking solo developers and indie hackers who can build products but lack marketing knowledge ## Core Idea AI-powered marketing launch kit that generates a full go-to-market strategy, landing page copy, and outreach templates for solo founders. Technical solo founders in emerging markets and beyond consistently ship products they can't market — they know how to build but not how to find customers, write copy, or pick channels. SaaSMarketer takes your product description and target user and generates a prioritized channel strategy, SEO-optimized landing page copy, cold outreach email sequences, and a 30-day content calendar tailored to your budget. It also provides a lightweight CRM to track early user conversations. ## Monetization Strategy $29 one-time for a full launch kit, $49/month for ongoing strategy updates, content calendar refreshes, and A/B copy variants ## Requirements - Category: AI/ML - Difficulty: Week - Suggested stack: Next.js + Anthropic Claude API + Vercel AI SDK Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "Lathe Pro". ## The Problem Developers are using LLMs to skip past learning rather than deeply understand new domains, creating shallow knowledge and long-term skill debt — a recurring concern across multiple HN threads. ## Target Audience Software developers wanting to genuinely learn new technical domains, bootcamp graduates, and CS students ## Core Idea An AI-powered interactive learning environment that teaches developers new technical domains through hands-on exercises, not AI-generated answers. Lathe Pro generates structured, source-backed tutorials for any technical topic and forces learners to type code by hand and solve problems themselves, with the AI acting as a Socratic tutor rather than an answer machine. It tracks progress, surfaces knowledge gaps, and adapts difficulty — bridging the gap between passive consumption and actual skill acquisition. Targets developers worried that AI is eroding deep learning and genuine understanding. ## Monetization Strategy Freemium — 3 tutorials/month free, then $12/mo for unlimited with progress tracking and spaced repetition ## Requirements - Category: Education - Difficulty: Month - Suggested stack: Next.js + Supabase + MDX for content Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "CleanRead". ## The Problem Users are manually appending /llm.txt to URLs because they find LLM-optimized content cleaner and more useful than the marketing-heavy standard web, but no tool automates this. ## Target Audience Tech-savvy readers, researchers, and developers who are frustrated with modern web content bloat ## Core Idea A browser extension that converts any webpage into its clean llm.txt-style content view, stripping marketing fluff for humans who prefer it. CleanRead fetches or generates the llm.txt equivalent of any webpage you visit and displays a toggle to switch between the standard marketing-heavy view and a stripped-down, information-dense plain-text view. It addresses the growing frustration that content written for LLMs is actually more readable and useful for humans than the original SEO-bloated web pages. Works offline for cached pages and learns your preferences per domain. ## Monetization Strategy Free extension with a $4.99/mo pro tier for cross-device sync, custom extraction rules, and offline reading queue ## Requirements - Category: Productivity - Difficulty: Weekend - Suggested stack: Next.js + localStorage or Supabase + PWA Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "SpamShield Political". ## The Problem People who donated to political parties once are now receiving hundreds of unsolicited emails and texts from random candidates with no clear way to opt out from all sources. ## Target Audience US voters who donated to political parties and are now overwhelmed by political spam ## Core Idea One-click removal tool that scrubs your contact info from US political party donor and marketing lists. SpamShield Political uses opt-out automation to submit removal requests to political party data brokers, campaign list vendors, and political PACs on your behalf, and monitors for re-addition. It addresses the nightmare of donating once to a political party and then receiving hundreds of unsolicited texts and emails from unrelated candidates forever. Sends weekly reports on removal status and any new sources that have acquired your data. ## Monetization Strategy One-time $9.99 cleanup fee plus $2.99/mo monitoring subscription ## Requirements - Category: SaaS - Difficulty: Week - Suggested stack: Next.js + Supabase + Stripe Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "SpamShield Jobs". ## The Problem Job seekers posting in HN 'Who Wants to Be Hired' threads receive spam emails from people who scraped their contact info and send irrelevant pitches, which is described as 'cruel'. ## Target Audience Job seekers, developers, and professionals actively looking for work ## Core Idea Automatically detect and filter recruiter spam from job-seeking posts so your inbox stays clean. Job seekers posting in 'Who's Hiring' threads or LinkedIn are bombarded by irrelevant solicitations from people who scraped their contact info. SpamShield Jobs uses AI to detect unsolicited recruiter outreach that doesn't match your stated skills or preferences and routes it to a filtered folder with a one-click unsubscribe blast. It integrates with Gmail and Outlook and learns your preferences over time. ## Monetization Strategy Freemium — free for up to 50 filtered emails/month, $5/month for unlimited filtering and multi-account support ## Requirements - Category: Productivity - Difficulty: Week - Suggested stack: Next.js + localStorage or Supabase + PWA Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "FocusReader". ## The Problem Developers and students struggle to focus on dense technical PDFs and textbooks now that their attention spans have been conditioned by AI assistants that do the thinking for them. ## Target Audience CS students, self-taught developers, and researchers reading dense technical material ## Core Idea A local-first PDF study app that keeps you engaged with dense technical books through AI-powered Socratic dialogue, annotations, and active recall. FocusReader is a beautiful, distraction-free PDF reader designed for studying dense technical content like textbooks and papers. As you read, an on-device AI surfaces questions, prompts you to explain concepts in your own words, and lets you have a dialogue about what you just read — without doing the thinking for you. All data stays local, with optional sync across devices. ## Monetization Strategy $8.99 one-time purchase on macOS with a $4.99/mo cloud sync add-on ## Requirements - Category: Education - Difficulty: Month - Suggested stack: Next.js + Supabase + MDX for content Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "PlainWeb". ## The Problem Users are manually appending /llm.txt to website URLs because they find machine-readable content cleaner and more useful than the standard marketing-heavy web, and privacy tools like Pi-hole sometimes break critical functionality. ## Target Audience Privacy-conscious developers, researchers, and power users who spend significant time reading online ## Core Idea Browser extension that strips any webpage to its clean, readable llm.txt-style content with one keystroke. Tech-savvy users are frustrated by the marketing-heavy, cookie-banner-laden, JS-bloated modern web and have noticed that /llm.txt versions of sites are cleaner and more informative than the human-facing versions. PlainWeb is a browser extension that fetches and renders a simplified, typography-focused version of any webpage by stripping tracking, ads, and decorative elements — falling back to a Readability parse if no llm.txt exists. It also lets users toggle between the original and plain view and save pages to a local reading list. ## Monetization Strategy Free base extension, $4/month for sync across devices, highlighting, and a personal reading archive ## Requirements - Category: Productivity - Difficulty: Weekend - Suggested stack: Next.js + localStorage or Supabase + PWA Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "SessionSync". ## The Problem Teams using Claude Code daily find their most valuable session artifacts trapped in local ~/.claude/projects/ folders with no way to share, search, or hand off sessions to colleagues. ## Target Audience Engineering teams using AI coding agents like Claude Code or Codex collaboratively ## Core Idea Share, search, and hand off Claude Code and AI coding agent sessions across your entire team via Git. Developers using Claude Code and similar agents generate incredibly valuable session artifacts — context, decisions, debugging threads — but these are trapped on individual laptops with no way to share them. SessionSync automatically commits agent sessions to dedicated Git branches, makes them searchable by project and topic, and lets teammates check out any session to resume where someone else left off. It integrates as a lightweight CLI wrapper that requires zero changes to existing workflows. ## Monetization Strategy Free for individuals and open source, $12/seat/month for team features including session search, tagging, and access control ## Requirements - Category: Developer Tool - Difficulty: Weekend - Suggested stack: Node.js CLI or VS Code extension + TypeScript Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "SessionSync". ## The Problem Claude Code and Codex sessions are trapped on individual laptops with no way to share or search them across a team, meaning valuable AI-assisted debugging sessions are permanently lost. ## Target Audience Engineering teams of 2–20 developers using agentic coding tools like Claude Code or Codex ## Core Idea Sync, share, and search your Claude Code and Codex agent sessions across your entire team via Git. SessionSync automatically captures agentic coding sessions and stores them in a searchable Git-backed repository so the whole team can access, replay, and build on each other's AI coding sessions. No more losing the session where someone untangled a gnarly migration on their local laptop. It integrates with existing repos and surfaces relevant past sessions as context when starting new tasks. ## Monetization Strategy $10/user/month after a free 5-user trial; self-hostable open core ## Requirements - Category: Developer Tool - Difficulty: Week - Suggested stack: Node.js CLI or VS Code extension + TypeScript Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.

I want to build an app called "LLMSkillBench". ## The Problem Developers building LLM skills and prompts have no way to know if a skill is actually good or to compare similar prompts, leading to manual and unreliable evaluation — one builder created regression tests from scratch just to solve this. ## Target Audience AI engineers, prompt engineers, and power users building custom LLM workflows and skills ## Core Idea Test, compare, and regression-test your AI prompts and skills so you can stop guessing if they actually work. Developers and power users who build custom LLM prompts, skills, and agents have no systematic way to measure whether a prompt is good, compare competing prompts, or catch regressions when a model update changes behavior. LLMSkillBench lets you define a prompt or skill, write expected-output test cases, and run automated regression suites against any LLM model version, scoring outputs with a judge model and displaying diffs over time. It supports Claude skills, GPT system prompts, and custom MCP tools. ## Monetization Strategy Free for up to 50 test runs/month, $19/month for unlimited runs, team sharing, and multi-model comparison ## Requirements - Category: Developer Tool - Difficulty: Week - Suggested stack: Node.js CLI or VS Code extension + TypeScript Please help me build this step by step. Start with: 1. A project structure and initial setup 2. The core data models 3. The main feature implementation 4. A simple but polished UI Keep it lean — MVP first, ship fast. Use modern best practices and make it production-ready.