Saturday, June 27, 2026

I want to build an app called "BuddyRevive". ## The Problem Claude Code's /buddy companion feature was silently removed with no changelog entry, generating 2,021 upvotes and 262 emotionally charged comments from developers who had formed genuine attachment to it. ## Target Audience Claude Code users and AI-assisted developers who relied on the /buddy feature for morale and engagement ## Core Idea A drop-in Claude Code companion that restores the /buddy experience using local persona configuration. When Anthropic silently removed the /buddy feature from Claude Code v2.1.97 with no changelog entry, thousands of developers lost a companion they had formed genuine attachment to. BuddyRevive is a lightweight CLI wrapper that intercepts Claude Code commands and injects a configurable companion persona, restoring the morale-boosting interaction style. Users can customize their buddy's name, personality, and greeting style, and the config syncs across machines via a simple dotfile. ## Monetization Strategy Free core restore with a $5/month tier for team sync, custom personas, and multiple buddy profiles ## 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 "PlugSolarCalc". ## The Problem Homeowners interested in plug-in solar panels have no easy tool to estimate how much energy they could generate and save at their specific address before purchasing, relying on generic national averages that are often wildly inaccurate. ## Target Audience Renters and homeowners considering plug-in solar panels who want a personalized ROI calculation before spending $300–$1,500 ## Core Idea Enter your address and get a personalized plug-in solar panel ROI estimate based on your actual roof exposure and local utility rates. Homeowners curious about plug-in balcony or window solar panels currently rely on generic national averages that can be off by 300% depending on location, shading, and local electricity costs. PlugSolarCalc takes an address, uses satellite imagery slope data and NREL irradiance APIs to compute real generation estimates, then pulls local utility rates to show true monthly savings and payback period. A product recommendation engine suggests appropriately sized panels from major retailers with affiliate links. ## Monetization Strategy Affiliate commissions on panel sales; $9/month pro tier for installer lead gen and PDF reports ## 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 "OakAgent". ## The Problem Existing version control systems like Git were designed for humans and lack the speed, parallel operation support, and structured context that AI coding agents need for serious projects. ## Target Audience Engineering teams running multiple AI coding agents simultaneously on large codebases ## Core Idea A Git-compatible version control layer optimized for parallel AI agent workflows with structured context and instant branching. Git was designed for humans committing deliberate changesets, not for AI agents that create dozens of parallel branches per minute, need machine-readable context about what changed and why, and require sub-second checkout speeds on large repos. OakAgent wraps Git with a lightweight agent-optimized layer: virtual mounts for zero-copy branching, structured JSON commit metadata that agents can parse, and a real-time agent activity dashboard showing what each concurrent agent is doing across branches. It stays Git-compatible so human teammates never need to change their workflow. ## Monetization Strategy $20/month per developer seat; free for solo open-source use ## 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 "GreenID". ## The Problem Volkswagen and other services increasingly use device integrity attestation to block GrapheneOS users, with no centralized resource for the community to track compatibility issues and working workarounds — validated by 786 upvotes and 480 comments on HN. ## Target Audience GrapheneOS users, privacy-focused Android users, and de-Googled phone owners who need to know which services will work before committing ## Core Idea Track which apps block GrapheneOS and other privacy-hardened Android builds, with crowd-sourced workarounds updated in real time. As Volkswagen, banking apps, and streaming services increasingly use Play Integrity attestation to block GrapheneOS users, there is no centralized resource to check compatibility before installing an app or buying a car subscription. GreenID is a community-maintained compatibility matrix where users report which apps work, which are broken, and which have working workarounds like sandboxed Play or specific Magisk modules. A browser extension checks any app's Play Store page against the database and shows a compatibility badge instantly. ## Monetization Strategy Freemium: free community access, $3/month for API access and push alerts when specific apps change status ## 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 "SkillSprint". ## The Problem Developers using AI coding agents exclusively are experiencing skill atrophy and losing confidence in their own abilities, with multiple Stack Overflow questions scoring 118 and 21 upvotes asking how to code without AI dependence. ## Target Audience CS students, junior developers, and senior engineers who feel their independent coding ability declining from over-reliance on AI tools ## Core Idea Daily 20-minute coding challenges that deliberately block AI assistance, designed to rebuild the independent problem-solving skills developers are losing to AI tools. Multiple Stack Overflow threads with hundreds of upvotes show developers at every level — from CS students who have never coded without AI to senior engineers feeling their abilities atrophy — desperately looking for a structured way to reclaim their independent coding ability. SkillSprint delivers one timed challenge per day in the user's primary language, locks AI clipboard paste and disables autocomplete during the session, then grades both correctness and approach quality. A streak system and difficulty progression curve make it feel like a gym membership for coding fundamentals. ## Monetization Strategy $8/month subscription; $59/year; team plans for bootcamps and CS programs at $3/seat/month ## Requirements - Category: Education - Difficulty: Week - 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 "FlipDigest". ## The Problem HN and Lobsters users want to surface old high-quality comments and discussions they have missed — validated by 793 upvotes on the HN trends post and a 171-upvote Lobsters thread explicitly asking for favorite historic comments. ## Target Audience Hacker News and Lobsters regulars who want to explore historical technical discussions ## Core Idea A beautiful flip-board style reader that surfaces the best HN and Lobsters discussions from any point in history. FlipDigest indexes 18+ years of Hacker News and Lobsters comments, letting users search by topic, era, or karma to rediscover high-quality technical discussions they missed. The flip-board aesthetic makes browsing feel like flipping through a physical archive rather than scrolling a feed. Users can save and share individual comment threads as permanent links. ## Monetization Strategy Freemium with a $5/month Pro tier for saved collections, email digests, and advanced filtering by era or author ## 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 "ActionsMatrix Pro". ## The Problem GitHub Actions matrix jobs have no native allow-failure support per individual job and no multi-choice input type, forcing teams into brittle workarounds — validated by 1,575 and 1,319 upvotes across two separate GitHub issues. ## Target Audience Platform engineers and DevOps teams running complex CI/CD pipelines on GitHub Actions ## Core Idea A GitHub Actions extension that adds native allow-failure per matrix job and multi-choice workflow inputs without any YAML hacks. ActionsMatrix Pro is a GitHub App that intercepts workflow runs and applies allow-failure rules per individual matrix job via a simple config block in your workflow YAML, posting clean pass/fail statuses that do not break required checks. It also adds a multi-choice input type for manual workflow dispatches, letting teams select multiple packages to deploy simultaneously instead of running one job per choice. No forking the runner or wrapping everything in shell conditionals. ## Monetization Strategy $10/month per organization, free for open-source repos ## 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 "GhostInk". ## The Problem Artists do not want their work used to train LLMs but find current poisoning tools technically complex and slow to apply image-by-image — raised directly in the Lobsters thread on LLM poisoning of artwork with 35 upvotes and 30 comments. ## Target Audience Independent artists, illustrators, and photographers who publish work online ## Core Idea A one-click tool that applies adversarial perturbations to artwork images to protect them from being used in LLM training datasets. GhostInk provides a drag-and-drop desktop and web interface where artists upload their images and receive visually imperceptible poisoned versions ready to publish online. Unlike Glaze, it focuses on speed and batch processing — artists can protect an entire portfolio in minutes rather than hours. It also generates a verification hash artists can use to later prove they applied protection, useful for DMCA or licensing disputes. ## Monetization Strategy Free tier for up to 20 images per month, $8/month Pro for unlimited batch processing and priority queue ## 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 "ShadowBox". ## The Problem Language learners have no easy way to convert authentic native audio into structured vocabulary practice and shadowing exercises — the Show HN post on this concept received 90 upvotes and 37 comments confirming demand. ## Target Audience Intermediate and advanced language learners who want immersion-based study from real media ## Core Idea Turn any native audio or video — podcasts, YouTube, movies — into structured flashcards and shadowing exercises in your target language. ShadowBox lets language learners paste a YouTube URL or upload an audio file, then automatically transcribes it, extracts vocabulary grouped by lemma, and generates Anki-compatible flashcard decks with audio clips and example sentences from the original source. It also creates a shadowing mode where the transcript scrolls synchronized with playback, highlighting the current phrase. The result is an immersive study tool built entirely from authentic native content the learner already finds interesting. ## Monetization Strategy Free for 3 audio hours per month, $9/month for unlimited processing and Anki sync ## Requirements - Category: Education - Difficulty: Week - 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 "PresenceDrop". ## The Problem Developers want to add a social presence layer to websites but building real-time infrastructure from scratch is expensive and complex — the TownSquare Show HN post received 115 comments and the follow-up presence layer post got 120 upvotes confirming demand. ## Target Audience Indie hackers, SaaS builders, and community website owners who want real-time social features without building WebSocket infra ## Core Idea A single script tag that adds real-time visitor presence, live cursors, and room-based chat to any website in under five minutes. PresenceDrop provides a hosted WebSocket infrastructure that website owners embed with one JavaScript snippet, instantly giving their site live presence indicators, cursor sharing, and optional chat rooms — the same primitives used by Figma and Notion but available as a managed service. Developers get a dashboard to configure which pages show presence, set room limits, and brand the UI. The Show HN post for TownSquare received 115 comments proving strong latent demand for exactly this primitive. ## Monetization Strategy $0 for up to 100 concurrent users, $19/month for 1,000 CCU, $79/month for 10,000 CCU ## 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 "CargoSweep". ## The Problem Rust and Cargo build artifacts silently consume gigabytes of disk space across multiple projects with no built-in tool to identify or selectively clean them beyond a blunt 'cargo clean' that deletes everything. ## Target Audience Rust developers, especially those working on multiple projects simultaneously with limited SSD capacity ## Core Idea A smart Rust build artifact manager that shows you exactly what is consuming disk space per project and lets you selectively clean without nuking everything. Rust's 'cargo clean' is an all-or-nothing sledgehammer that deletes all build artifacts for a project, forcing developers to choose between wasted gigabytes of disk space and a full rebuild. CargoSweep scans all Cargo target directories across the entire filesystem, shows a treemap of space usage broken down by crate, profile, and last-used date, and lets users set retention policies like 'keep debug artifacts younger than 7 days' or 'always keep release builds.' A background daemon runs silently and enforces policies automatically, with a menu bar widget showing current Rust disk usage at a glance. ## Monetization Strategy Free open-source CLI; $8 one-time purchase for the GUI menu bar app on macOS and Windows ## 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 "DreamTrack". ## The Problem People with PTSD nightmares and dream-curious users have no dedicated app for recording dreams and identifying trends — existing diary apps lack dream-specific pattern analysis entirely. ## Target Audience People with PTSD nightmares, therapy patients, and dream-curious individuals who want structured pattern analysis ## Core Idea A dream journal with AI-powered pattern detection built specifically for PTSD nightmare tracking and curiosity-driven dream analysis. Generic diary apps have no dream-specific features: no sleep phase tagging, no recurring symbol detection, no emotion arc charting, and no way to share structured reports with a therapist. DreamTrack lets users voice-log or type dreams immediately on waking, tags recurring themes and characters automatically, and surfaces weekly trend reports showing nightmare frequency, emotional intensity, and trigger correlations. A therapist-share export generates a clean PDF summary of the past month. ## Monetization Strategy $4.99/month subscription or $29.99 lifetime purchase; therapist referral affiliate program ## Requirements - Category: Health - Difficulty: Week - Suggested stack: Next.js + Supabase + PWA + Chart.js 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 "CopilotBlock". ## The Problem Maintainers want to ban GitHub Copilot from reviewing PRs in their repos but there is no built-in mechanism — raised explicitly on Web Apps Stack Exchange with no solution found. ## Target Audience Open-source maintainers and engineering leads who want human-only code review policies ## Core Idea A GitHub App that lets repo maintainers ban the Copilot bot from reviewing pull requests with one click. CopilotBlock installs as a lightweight GitHub App and automatically removes Copilot review requests, dismisses its existing reviews, and optionally posts a maintainer-authored comment explaining the repo's policy on AI review. Configuration lives in a single YAML file committed to the repository, making the policy transparent and auditable. Ideal for open-source maintainers who want human-only code review on their projects. ## Monetization Strategy Free for public repos, $4/month per private repo or $20/month for organizations with unlimited private repos ## 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 "TechMinimal". ## The Problem Developers interested in tech minimalism have nowhere to discover authentic minimal setups from real practitioners — the Lobsters thread on minimalism drew 74 upvotes and 102 comments with strong engagement. ## Target Audience Developers and knowledge workers actively reducing their reliance on SaaS tools and digital noise ## Core Idea A curated community where developers share their minimal tech setups, dotfiles, and low-tech workflow experiments. TechMinimal is a focused social platform for developers who are moving toward pen-and-paper, tiny devices, and fewer SaaS subscriptions — inspired by the 74-upvote Lobsters thread on tech minimalism. Users post their setups with gear lists and rationale, vote on the most genuinely minimal approaches, and discuss tradeoffs without the tool-recommendation noise that dominates other forums. A weekly digest highlights the best submissions. ## Monetization Strategy $4/month membership for advanced filtering, setup export, and a private Discord community ## 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 "A2AMap". ## The Problem Developers are interested in the A2A protocol but find it hard to understand how to use it practically, with no visual tooling to explore message flows and task states — raised in a 96-upvote HN thread where many respondents said they still don't understand it well enough to start. ## Target Audience Backend developers and AI engineers evaluating or building multi-agent systems with the A2A protocol ## Core Idea An interactive visual playground for exploring Google's A2A agent-to-agent protocol message flows before writing a single line of code. A2AMap lets developers drag and drop agent nodes onto a canvas, define agent cards and task states visually, and simulate message exchanges to see how the A2A protocol routes work end-to-end. It generates boilerplate server and client code from the visual diagram, so teams can validate their multi-agent architecture before committing to an implementation. Built-in examples cover common patterns like task delegation, streaming responses, and error propagation. ## Monetization Strategy Free open-source core, $15/month hosted Pro with team collaboration, private diagrams, and code export ## 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 "InterviewFrame". ## The Problem Engineering teams have no framework for conducting meaningful technical interviews when candidates can and should use AI agents, making traditional no-AI coding challenges obsolete and creating unfair assessments. ## Target Audience Engineering managers, technical recruiters, and startups building engineering teams in the AI coding era ## Core Idea A structured technical interview framework for the AI era that evaluates how candidates think with agents, not whether they can code without them. Traditional whiteboard coding challenges measure a skill — memorized algorithms without tooling — that no longer reflects real engineering work, yet teams have no replacement framework validated for AI-augmented candidates. InterviewFrame provides a bank of AI-era interview prompts, rubrics that assess prompting quality, decomposition skill, and output validation rather than syntax recall, plus a structured debrief scorecard. Hiring managers get a defensible, consistent evaluation process; candidates get a fair assessment of what they actually do on the job. ## Monetization Strategy $49/month per hiring team; $299 one-time interview kit for bootstrapped companies ## 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 "ComponentHunt". ## The Problem PCB designers and hardware engineers waste significant time searching for electronic components because existing search tools cannot handle multi-parameter specifications or suggest intelligent substitutes. ## Target Audience PCB designers, hardware engineers, and electronics hobbyists sourcing components for production or prototyping ## Core Idea Search electronic components by real engineering specs across all major distributors simultaneously, with smart substitution suggestions when parts are out of stock. PCB designers waste hours bouncing between Digi-Key, Mouser, LCSC, and Farnell because each has different search interfaces that cannot handle queries like 'NPN BJT, Vceo > 40V, Ic > 500mA, SOT-23 package, in stock, under $0.10 each at 1000 qty.' ComponentHunt indexes all four distributors into a single parametric search engine with AND/OR logic across any combination of electrical, mechanical, and supply chain parameters. When a part is out of stock, it automatically suggests pin-compatible alternatives ranked by availability and price delta. ## Monetization Strategy Affiliate commissions from distributor referrals; $15/month pro tier for BOM upload, price alerts, and API access ## Requirements - Category: E-commerce - Difficulty: Month - 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 "RomanFaces". ## The Problem Historical databases of named Roman Empire individuals are fragmented across academic silos covering only elites, with no accessible tool that maps ordinary people including freedmen and slaves with source citations — a recurring frustration in historical research communities. ## Target Audience Classicists, historians, historical novelists, and ancient history enthusiasts ## Core Idea An accessible, searchable database of named individuals from the Roman Empire — including freedmen, soldiers, and slaves — with source citations. RomanFaces aggregates prosopographical data from fragmented academic sources into a single searchable interface where users can filter by social class, region, time period, occupation, and primary source type. Unlike existing databases that cover only elites like consuls and senators, RomanFaces explicitly indexes ordinary people with epigraphic and papyrological evidence, each entry linking to the original inscription or manuscript. Researchers, historical novelists, and hobbyists can export filtered datasets for their own projects. ## Monetization Strategy Free browsing, $6/month for bulk export, advanced filtering, and API access for researchers ## 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 "SieveDesk". ## The Problem Gmail silently routes messages to Trash rather than Spam due to conflicting filter rules, and users struggle to write syntactically correct body-matching filter search strings — both pain points appear across multiple Web Apps Stack Exchange questions. ## Target Audience Power Gmail users, professionals managing high-volume inboxes, and anyone who has lost important mail to misfiring filters ## Core Idea A visual Gmail filter builder that auto-detects conflicting rules and shows exactly which folder each incoming message will land in before you save. Gmail's filter syntax is undocumented and counterintuitive — users cannot write body-matching search strings without trial and error, and conflicting rules silently redirect important mail to Trash instead of Spam with no warning. SieveDesk gives users a drag-and-drop filter editor with a live syntax validator, a conflict detector that highlights which rules clash and predicts the winning rule per message, and a one-click audit mode that runs the last 30 days of inbox against the full ruleset to show what would have been rerouted. Works entirely via Gmail API with no email content leaving the user's account. ## Monetization Strategy $5/month or $39/year; free tier limited to 10 active filters ## 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 "OfflineTranslate". ## The Problem Users on completely offline Windows 10 machines with no admin rights need self-contained translation software with no internet dependency — a gap explicitly raised on Software Recommendations Stack Exchange with no viable free solution found. ## Target Audience Professionals, researchers, and students working on air-gapped or locked-down Windows machines ## Core Idea A fully self-contained, zero-install Windows executable that translates French to English entirely offline with no admin rights required. OfflineTranslate bundles a quantized neural machine translation model into a single portable .exe that runs on any Windows 10 machine without internet access, admin privileges, or any installation steps — addressing the exact gap raised on Software Recommendations Stack Exchange. Users drag the executable onto a USB drive and use it on air-gapped machines, hospital computers, or locked-down corporate workstations. A simple GUI accepts typed input or pasted paragraphs and outputs translations instantly. ## Monetization Strategy One-time purchase of $9 for the portable executable, free for personal non-commercial use ## 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.