Friday, June 12, 2026

I want to build an app called "AISlop Detector". ## The Problem Online communities are flooded with AI-generated content and existing flag/report systems don't distinguish AI slop from other rule violations, making it hard to maintain content quality. ## Target Audience Power users of HN, Reddit, and Twitter who value authentic human-written content ## Core Idea A browser extension that scores online content for AI-generation likelihood and lets communities collectively label slop. HN and Reddit communities are increasingly frustrated by AI-generated content flooding discussions, with users requesting dedicated slop-flagging tools separate from existing report systems. AISlop Detector adds a subtle confidence score badge to posts and comments across major platforms, powered by a lightweight on-device classifier. Users can upvote or downvote slop labels, building a crowd-sourced dataset that improves detection over time and can be exported as a community blocklist. ## Monetization Strategy Free extension with optional $4/month Pro tier for advanced filters, cross-platform sync, and API access for community moderators ## 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 "SlotWatch". ## The Problem Event-goers are locked into Ticketmaster's monopoly with no price transparency, no inventory alerts, and no cross-platform visibility when tickets become available. ## Target Audience Concert-goers, sports fans, and event enthusiasts frustrated by ticketing monopolies ## Core Idea Get instant alerts and analytics when event tickets drop on any platform — without the Ticketmaster monopoly. Fans are frustrated that every venue funnels through Ticketmaster and that no real competitor has emerged. SlotWatch monitors ticket availability across all platforms (Ticketmaster, SeatGeek, AXS, venue direct sites) via scraping and APIs, sends real-time push/email/SMS alerts when inventory drops or prices fall, and shows historical price charts so buyers know when to strike. It also tracks face-value drops from resellers and flags suspicious listing patterns. ## Monetization Strategy Free basic alerts, $7/month for real-time notifications, price history charts, and multi-event tracking; affiliate commissions on ticket purchases ## Requirements - Category: E-commerce - Difficulty: Week - Suggested stack: Next.js + Shopify API or 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 "AlertZone". ## The Problem Emergency alerts like Red Flag Warnings are broadcast county-wide to hundreds of thousands of people, but the actual danger polygon is small and precise — residents have no easy way to check if their specific address is inside the real risk zone. ## Target Audience Homeowners in wildfire-prone or flood-prone regions, emergency preparedness enthusiasts ## Core Idea Instantly check if your exact address is inside any active emergency warning zone, not just your county. AlertZone lets anyone enter their address and immediately see whether they fall within the precise polygon of any active emergency warning — wildfire red flag zones, evacuation orders, flood warnings, and more — using real NWS and FEMA geodata. Existing county-wide alerts reach half a million people even when only a small area is affected, causing panic and confusion. AlertZone also offers opt-in SMS alerts tied to your specific location polygon. ## Monetization Strategy Free address lookups, $3/month for SMS alerts tied to your home and work addresses ## Requirements - Category: SaaS - Difficulty: Weekend - 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 "AgentFence". ## The Problem AI agents given access to production systems (databases, Kubernetes, cloud infra) can cause unintended damage, and teams have no runtime guardrail layer to intercept dangerous operations. ## Target Audience DevOps engineers, platform teams, and indie hackers running autonomous AI agents in production ## Core Idea A runtime security firewall that prevents AI coding agents from making unintended destructive changes to your production systems. As AI agents gain access to real production systems — databases, Kubernetes clusters, cloud infrastructure — the risk of unintended destructive actions grows significantly. AgentFence sits between your agent and production, intercepts tool calls in real time, checks them against configurable policy rules, and requires human approval for high-risk operations like deletes, schema migrations, or external API calls. It logs every agent action with a full audit trail. ## Monetization Strategy Free self-hosted open-core, $29/month SaaS for hosted policy management, audit logs, team approvals, and integrations ## Requirements - Category: Developer Tool - Difficulty: Month - 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 "CodeReview Classic". ## The Problem AI-generated codebases are syntactically correct but architecturally poor — interns and junior devs using AI produce code with bad directory structure and design patterns that standard linters don't catch. ## Target Audience Engineering managers, senior developers, and teams onboarding AI-assisted junior developers ## Core Idea Automated code review that enforces software engineering principles from 12 foundational engineering books, not just linting rules. AI-generated code often passes linters and tests but violates fundamental software engineering principles around structure, naming, cohesion, and maintainability. CodeReview Classic integrates into GitHub PRs and CI pipelines, analyzing code against patterns distilled from books like Clean Code, The Pragmatic Programmer, and SICP. It gives line-level feedback grounded in named principles, helping developers understand the 'why' behind each suggestion rather than just auto-fixing. ## Monetization Strategy Free for public repos, $15/month per developer seat for private repos with GitHub/GitLab integration and team dashboards ## 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 "SideBuilder". ## The Problem Developers with side project ideas fail to ship because they lack accountability partners and the casual async camaraderie needed to stay motivated without the overhead of formal collaboration. ## Target Audience Indie hackers, employed engineers with side projects, and solo developers building on nights and weekends ## Core Idea Find async accountability partners for side projects and track tiny daily progress together — no meetings required. Solo indie hackers and engineers with side project ideas frequently cite lack of accountability and partnership as the reason projects stall, but don't want the overhead of synchronous collaboration. SideBuilder matches you with 1-3 builders with complementary skills or similar project types based on your stack and goals, provides a simple async check-in system (one daily sentence of progress), and visualizes momentum streaks. Public project pages double as a soft launch platform. ## Monetization Strategy Free core matching and check-ins; $8/month Pro for private project rooms, skill-based matching filters, and integration with GitHub commit feeds ## Requirements - Category: Social - Difficulty: Week - Suggested stack: Next.js + Supabase Realtime + Auth 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 "LocalFinance". ## The Problem People want to learn personal finance but generic educational content doesn't connect to their real financial situation, and existing finance apps manage money rather than teach principles. ## Target Audience Young professionals, recent graduates, and anyone who feels financially illiterate despite using budgeting apps ## Core Idea A microlearning app that teaches personal finance in 5-minute daily lessons using real numbers from your own accounts. Existing personal finance apps either manage your money or teach generic concepts — none connect real account data to contextual, bite-sized lessons. LocalFinance pulls in read-only transaction data via Plaid, identifies patterns in your actual spending, and generates personalized 5-minute daily lessons (e.g., 'Your coffee habit costs you $X/year — here's what compound interest says about that'). All data stays local on-device, addressing the data privacy concerns raised across multiple posts. ## Monetization Strategy Free for first 30 lessons, then $6/month or $49/year for full curriculum, account sync, and personalized financial health score ## Requirements - Category: Fintech - Difficulty: Month - 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 "FlowGuard". ## The Problem Developers using AI coding agents like Claude lose their flow state because they must constantly watch and babysit slow agents, breaking deep work habits they previously prided themselves on. ## Target Audience Software engineers and indie hackers using AI coding agents daily ## Core Idea Automatically manage your AI coding agent sessions to keep you in a deep work flow state. FlowGuard monitors your AI coding agent activity and intelligently batches tasks, queues follow-up prompts, and sends you focused notifications only when your input is truly needed. It integrates with Claude Code, Codex, and other agentic tools to eliminate the constant context-switching that breaks deep work. Instead of babysitting a slow agent, you get a structured work rhythm with clear focus windows. ## Monetization Strategy Freemium SaaS — free for 1 agent integration, $12/month for multi-agent support and analytics ## 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 "Claumate". ## The Problem Claude has no bulk chat deletion feature, forcing users to scroll and manually delete hundreds of chats one by one, while ChatGPT's bulk delete also has poor discoverability and usability. ## Target Audience Heavy AI assistant users, developers, researchers, and writers ## Core Idea A unified chat history manager and bulk action tool for Claude, ChatGPT, and all major AI assistants. Claumate provides a browser extension and desktop app that lets you search, organize, tag, export, and bulk-delete conversations across Claude, ChatGPT, and other AI chat interfaces. The frustration of Claude having no bulk delete and ChatGPT having poor search is solved in one place. Power users can set retention policies, auto-archive old chats, and export entire histories in structured formats. ## Monetization Strategy One-time purchase $9 or $4/month subscription for cross-platform sync and auto-retention rules ## 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 for Job Seekers". ## The Problem People posting in public job-seeking threads receive predatory spam emails from people scraping their contact information, which is described as 'cruel' in the source post. ## Target Audience Job seekers, freelancers, and developers who post publicly looking for work ## Core Idea Automatically detect and filter predatory recruiter spam targeting people who post in job-seeking threads. Job seekers who post in public 'Who's Hiring' or 'Who wants to be hired' threads are frequently targeted by spammers and scammers who scrape their contact info. SpamShield monitors your inbox and flags or auto-archives messages that match patterns of recruiter spam, using sender reputation, message templates, and behavioral signals. It also lets users collectively report spam campaigns to build a community-driven blocklist. ## Monetization Strategy Freemium: free for basic filtering, $5/month for advanced rules, community blocklist access, and multi-inbox 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 "FlowGuard". ## The Problem Developers using AI coding agents lose flow state during wait times and end up doom-scrolling or task-switching, destroying their deep work sessions. ## Target Audience Software engineers and indie hackers using agentic AI coding tools ## Core Idea Stay in deep focus while AI agents code for you by replacing idle-wait time with structured micro-tasks. Developers using agentic coding tools like Claude Code report losing their flow state while waiting for slow agents to finish. FlowGuard detects when your coding agent is running, locks distracting sites, and surfaces a curated queue of micro-tasks — code review comments, documentation stubs, or learning snippets — relevant to what the agent is building. When the agent finishes, it nudges you back with a summary of what changed. ## Monetization Strategy One-time purchase at $19 or $8/month subscription; potential integration partnerships with coding agent platforms ## 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 "Lathe Academy". ## The Problem Developers are increasingly worried about skill atrophy from using AI tools that do work for them rather than teaching them, and want a way to learn deeply without shortcuts. ## Target Audience Software engineers, career-changers, and students who want to build real skills despite AI availability ## Core Idea Learn any technical domain hands-on with AI-generated tutorials that force you to type, not just read. Generic AI tools do the work for you, eroding skills rather than building them. Lathe Academy generates structured, source-backed, hands-on tutorials for any technical topic and requires learners to type code themselves in a local editor — with hints but no copy-paste. Progress is tracked, spaced repetition surfaces forgotten concepts, and a streak system keeps learners accountable. It directly addresses the growing anxiety among engineers about skill atrophy from AI over-reliance. ## Monetization Strategy Freemium: 3 tutorials free, then $12/month or $99/year for unlimited topics, progress tracking, and community forums ## 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 "BrooksReview". ## The Problem AI-generated code often passes functional tests but has terrible structure, poor organization, and violates established engineering principles — there is no automated metric or tool to catch this. ## Target Audience Engineering teams using AI coding tools, CTOs, and senior engineers doing code reviews ## Core Idea AI code review that enforces real software engineering principles, not just syntax correctness. BrooksReview runs automated code reviews grounded in classic software engineering literature — clean architecture, SOLID principles, The Pragmatic Programmer, and more — and flags structural and design issues that LLMs typically produce when writing code. It catches the atrocious directory structures, god objects, and anti-patterns that pass all tests but are unmaintainable. Integrates directly into GitHub PRs and CI pipelines. ## Monetization Strategy Free for public repos, $15/month per developer for private repos and CI integration ## 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 "LaunchStack". ## The Problem Indie hackers and solo founders spend too much time debating tech stack choices with no real-world data on what stacks are actually being used to ship successful products in their niche. ## Target Audience Indie hackers, solo founders, and developers planning new SaaS or app launches ## Core Idea Instantly see what tech stack every indie product was built with, before you start building yours. LaunchStack crawls new product launches from Product Hunt, Show HN, and indie directories and automatically detects the hosting provider, frontend framework, backend language, database, and payment processor behind each product. Founders wasting time on stack decisions can browse what successful launches in their category actually used. Includes filters by category, team size, and launch recency. ## Monetization Strategy Free browse with limited history, $9/month for full search, stack trend analytics, and API access ## 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 "FocusFence". ## The Problem People with ADHD and overstimulation tendencies fall into highly specific personal procrastination patterns that generic blockers cannot detect — they need pattern-aware intervention that understands their unique distraction loops. ## Target Audience Students, indie hackers, remote workers, and people with ADHD managing their own productivity ## Core Idea A distraction blocker that learns your personal rabbit-hole patterns and intervenes before you fall in. FocusFence monitors browsing and app switching behavior to detect when you are drifting into procrastination loops — not just blocking social media, but recognizing your personal patterns like 'researching random topics instead of studying'. When it detects a drift, it surfaces a gentle reminder of your current task and offers a timed reentry ritual. Designed specifically for ADHD-adjacent users who build productivity tools to avoid the actual work. ## Monetization Strategy Free 14-day trial, $7/month subscription or $49 lifetime deal ## 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 "SoloShip". ## The Problem Solo developers with side project ideas struggle to maintain momentum and motivation because they lack accountability partners and the camaraderie of building with someone else, even on nights-and-weekends schedules. ## Target Audience Employed developers with side projects, indie hackers, and open source contributors ## Core Idea Find an accountability partner and ship open source side projects together on nights and weekends. SoloShip matches indie developers who have side project ideas but lack accountability and collaboration partners, based on tech stack, time zone, availability, and project type. Pairs commit to weekly async check-ins, shared milestones, and public build logs. It solves the isolation of solo building without the overhead of a formal co-founder relationship. ## Monetization Strategy Free to join and match, $10/month for premium features like private project rooms, milestone tracking, and featured placement ## Requirements - Category: Social - Difficulty: Week - Suggested stack: Next.js + Supabase Realtime + Auth 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 Claude Pro and Max plan users have no usage forecasting — they can only see current usage but not where they are heading, leading to surprise cutoffs mid-project. ## Target Audience Developers using AI coding agents on paid plans, indie hackers, and small teams ## Core Idea Predict and budget your Claude Code and AI agent token usage before you hit the wall. TokenWatch tracks your real-time AI coding agent usage and uses forecasting models to predict when you will hit your plan limits, how much budget remains for the day or month, and which tasks are consuming the most tokens. It sends alerts before you hit limits and suggests cheaper alternatives or task batching strategies. Supports Claude Pro, Max, Team plans, and OpenAI Codex. ## Monetization Strategy Free tier for single model tracking, $8/month for multi-model support and team dashboards ## 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 "ExtensionPass". ## The Problem Chrome extension developers face opaque and inconsistent rejections from the Chrome Web Store with vague reasons like 'spam' or 'additional functionality', and have no clear path to understand what changes are needed or how to successfully appeal. ## Target Audience Browser extension developers, indie hackers building Chrome extensions, and small software teams ## Core Idea Navigate Chrome Web Store rejection appeals with AI-powered guidance and compliance checklists. ExtensionPass analyzes your Chrome extension manifest and code against the latest Chrome Web Store policies and generates a specific compliance report explaining why your extension may be rejected and exactly how to fix it before submission. For developers already rejected, it generates appeal templates grounded in the specific policy language Google uses. It tracks policy changes over time so developers are never caught off guard by shifting rules. ## Monetization Strategy Free one-time compliance scan, $19 one-time fee for full appeal package with policy-matched templates and revision tracking ## 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 "Claumon Pro". ## The Problem Claude Pro and Max plan users can only see current usage snapshots, not where they're heading, causing unexpected agent shutdowns and wasted compute mid-task. ## Target Audience Developers and power users running AI agents on metered API plans ## Core Idea Predict and visualize your AI API usage limits before you hit them, across all major providers. Users on Claude Pro, Max, and similar plans have no way to forecast where their usage is heading — they only see current consumption, not trajectory. Claumon Pro aggregates usage data across Anthropic, OpenAI, and other providers, applies time-series forecasting to predict when you'll hit rate limits, and sends alerts so you can throttle agents before getting cut off mid-task. It also surfaces cost anomalies and usage spikes. ## Monetization Strategy Free tier for single provider, $6/month for multi-provider tracking, Slack/email alerts, and export reports ## 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 "PartFinder". ## The Problem PCB engineers waste enormous time searching for electronic components that match complex multi-dimensional specifications because existing search tools require exact parameter filters and cannot interpret nuanced queries. ## Target Audience Hardware engineers, PCB designers, electronics hobbyists, and procurement teams ## Core Idea A semantic search engine for electronic components that understands complex multi-spec queries. PartFinder indexes millions of electronic components and lets engineers search using natural language multi-attribute queries like 'low noise op-amp under 5mA quiescent current with SOIC-8 package rated for -40C'. Existing component databases like Digi-Key and Mouser require exact filter navigation and do not understand semantic intent. PartFinder aggregates stock data from major distributors and surfaces alternates when primary parts are unavailable. ## Monetization Strategy Free for basic search, $20/month for API access, BOM upload batch search, and stock alerts ## 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.