Splitting the job so DeepSeek's free chat does the generation and Claude Code does the reasoning cut a typical vibecoded project's AI bill by roughly 70 percent.
How I Cut My Claude Code Token Bill by 70 Percent Using DeepSeek I used to watch the token counter the way you watch a taxi meter in a city you don't know. A moderate full stack app, vibecoded end to end in Claude Code, would quietly run me thirty to eighty dollars in API credits, and I would tell myself it was the price of speed. It wasn't. Most of what I was paying premium rates for was generation, not reasoning, and generation does not deserve premium rates. So I split the job. DeepSeek does the building. Claude Code does the thinking. The DeepSeek I use is the free chat at chat.deepseek.com/a/chat. Not the API, not a paid tier, not a proxy through some wrapper that charges you for what DeepSeek gives away. The chat is 100% free. No credit card, no subscription, no hidden caps. You get DeepThink reasoning, file uploads, web search, and the full context window, all at zero cost. There is no paid consumer product to upgrade to because free is the whole thing. The only tax is slower responses during peak traffic, which shows up as waiting, not as a bill. DeepSeek is somewhere between forty and a hundred times cheaper per token than Claude for the API anyway, but since I am using the free chat, the number that matters is zero. And it writes code that is genuinely good enough for CRUD, parsers, integrations, refactors, and test scaffolding. It has a context window large enough to swallow an entire mid sized project. It can also output four thousand lines of code in a single prompt. I have had it produce an entire a.py script with twenty file writes, ten patches, a test runner, and all the raw string content embedded, in one shot, and the script ran green on the first try. That is the part that changes the economics completely. The workflow starts with a bundle. I keep a script in every project root that walks the tree, skips secrets and build artifacts and node modules, and writes one text file to Downloads with clear file delimiters. That file is what I paste to DeepSeek. DeepSeek can analyze bundles up to around three megabytes of code, which is a full mid sized project including every config file, every pattern, and every test. It reads the whole thing in one shot. No file by file back and forth, no re explaining context on every turn, no paying to upload the same codebase forty times. The skip list matters more than people think. If DeepSeek sees a real API key in context it gets hesitant about writing auth code, and scan artifacts and git metadata add noise without adding signal. Two toggles change everything about how DeepSeek performs. DeepThink is the reasoning mode, and it makes DeepSeek slow down and think through the plan before answering. Without it, DeepSeek rushes, produces code that looks right until you run it, and misses its own logic errors. With it, DeepSeek catches most of those errors before you do, and every prompt in this workflow assumes DeepThink is on. Search gives DeepSeek live web access, so when it needs to check a library version or an API signature or a framework gotcha, it looks it up instead of guessing from stale training data. That alone prevents a large share of the bugs I used to hit. Together, DeepThink plus Search makes DeepSeek roughly five times more useful for planning and code generation. Without them you are not really getting DeepSeek. You are getting the fast but sloppy version. The planning step is where most people fail. They open DeepSeek and say build me a SaaS, and the model produces something half formed, and they iterate for ten messages, and by the end they have burned the equivalent of a Claude Code session and have a mess. The better move is to write the plan yourself first. What the app is, every module and what it owns, every file the project will contain, the order files should be created, any hard constraints. Then ask DeepSeek to split that plan into phases organized by file touch, not by feature. The naive way to phase a project is by feature, auth then dashboar
A 24/7 market-alert SaaS I designed, coded and shipped solo. It watches crypto, US stocks and forex, explains every chart in plain language, and paper-trades its own signals so its accuracy is proven, not promised.
Category: SaaS / FinTech. Role: Solo developer: product, algorithms, backend, frontend and infrastructure. Tech stack: Cloudflare, JavaScript, SQL, TypeScript.
Key results: 15 markets watched 24/7; Checks every 15 minutes on the edge; Every call graded against real candles; Runs on Cloudflare's free tier; Solo build: idea to production.
Live site: https://market.nythosx.com. Live demo: https://market.nythosx.com/?embed=1.
A B2B GPS field-operations and expense platform built solo across three surfaces: a Laravel + PostgreSQL REST API, a React admin dashboard, and a React Native mobile app. Field workers get geofenced check-ins and automatic mileage tracking, while admins see live team locations and anomaly-flagged activity in real time.
Category: B2B Software. Role: Full Stack Developer. Tech stack: TypeScript, PostgreSQL, Expo, Laravel, MUI, React, React Native.
Key results: Owned every layer solo: a Laravel/PostgreSQL REST API, a React admin dashboard, and a React Native mobile app; Replaced self-reported travel claims with geofenced check-ins and automatic mileage/fare calculation; Real-time team location and anomaly-flagged activity pushed via Laravel Reverb WebSockets; Offline-tolerant mobile check-ins that queue requests when signal drops.
Replaced a legacy PHP system with a Laravel 12 REST API and React frontend to centralize operations for a national organization. Role-based access enforces strict per-role data isolation across 17 distinct roles and 4,000+ users, keeping the dashboard fast even as member records scale into the thousands, and automated navigation streamlined national staff operations by 40%.
Category: Business System. Role: Full Stack Developer. Tech stack: Cloudways, Supabase, Laravel, React.
Key results: 17 distinct user roles; 4,000+ users served with customized portal experiences; Streamlined national staff operations by 40% through centralized management and automated role-based navigation.
Source code (GitHub): https://github.com/nythosx/National-Staff-Management-System-Backend-Laravel-Supabase-.
Modernized legacy HRIS modules into Laravel 12 microservices covering recruitment, placement, and employee health. Recruitment services handle applicant tracking and multi-stage screening, while the health service manages records, vaccinations, and wellness programs, all documented with Swagger.
Category: HRIS. Role: Full Stack Developer / Backend Developer. Tech stack: MySQL, Laravel, React.
Key results: Decomposed a fragile legacy PHP HRIS into independent Laravel 12 microservices for recruitment, placement, and employee health; Isolated sensitive employee health records behind their own service and role-based access control, with no shared blast radius with recruitment logic; Documented every endpoint with Swagger so existing payroll and employee-management systems could integrate against a trusted contract; Replaced legacy modules in production without breaking systems already depending on them.
Source code (GitHub): https://github.com/nythosx/ihris-ms-recruitment.
An anonymous mobile venting app built around a paper-plane metaphor, matching strangers in real time via Socket.io and Redis sorted sets. Field-level AES-256 encryption and AI-powered moderation from Google Vertex AI keep the platform safe, backed by an ethical, non-addictive gamification system.
Category: AI / Mobile. Role: Full Stack Mobile Developer. Tech stack: Google Vertex AI, PostgreSQL, Prisma, Redis, Expo, Express, Node.js, React Native.
Key results: AES-256-GCM field-level encryption for every rant and message, with IP addresses stored as bcrypt hashes rather than plaintext; Two-layer moderation: a synchronous rule-based layer blocking harassment/crisis language instantly, plus an asynchronous Google Vertex AI layer re-scoring ongoing conversations; Real-time matchmaking via Socket.io with Redis sorted sets indexing every live rant; Purely cosmetic ten-tier reward system with no functional gating, keeping appreciation genuine rather than performative.
A Windows desktop app that turns long-form video into TikTok-ready clips: cut, captioned, templated, and uploaded automatically. Its AI runs through a personal DeepSeek chat session instead of a paid API, so there is no per-token cost, and it posts directly through TikTok's real Content Posting API.
Category: AI / Creator Tools. Role: Solo Developer. Tech stack: Rust, TypeScript, React, Tailwind CSS, Tauri.
Key results: Zero per-token AI cost, drives a real, logged-in DeepSeek browser session instead of a paid LLM API; Real TikTok Content Posting API integration with correct chunked upload for large clips; Konva-based visual template editor whose crop/watermark/caption layout is mirrored pixel-for-pixel by the actual FFmpeg render; One-click Auto Upload pipeline: slice → caption → render → queue across every connected account.
Live demo: https://clipflow24.netlify.app/#demo. Source code (GitHub): https://github.com/nythosx/clip-flow.
A free AI coding agent (CLI, Chrome extension, and native host) that runs a planner and executor loop through a logged-in DeepSeek chat session instead of a paid API. The read-only Planner decomposes tasks while the Executor makes changes and verifies them with a real tool call before reporting done.
Category: AI / Developer Tools. Role: Solo Developer. Tech stack: JavaScript, Node.js.
Key results: Zero-API-cost coding agent driven through a real, logged-in DeepSeek chat session instead of a metered LLM API; Planner/Executor separation with no shared context, so every action the Executor takes was explicitly authorized rather than assumed; Executor required to verify its own changes with a real tool call before reporting a task done; Mocked fake-backend of the chat UI enabling local development and testing without touching a live session.
Source code (GitHub): https://github.com/nythosx/deepseek-orchestrator.
A Laravel business system built for a real, operating broiler poultry enterprise in the Philippines. It tracks batches from chick intake to market age, feed and inventory, mortality, sales, and expenses, generating the profitability reports the farm uses for DTI and YEF documentation.
Category: Business System. Role: Solo Developer. Tech stack: PHP, Alpine.js, Laravel, Tailwind CSS.
Key results: Replaced notebooks and scattered spreadsheets with one system tracking a batch of birds from chick intake to market age; Unified feed/inventory, mortality/health, customer/order, delivery, and sales/expense tracking into shared profitability reports; Reports double as DTI and Youth Entrepreneurship Fund financial documentation, exported to PDF via DomPDF; Role-based access via Laravel Breeze and Spatie, built for a non-technical farm manager to trust and use daily.
An unofficial pulse-check survey platform gauging public sentiment ahead of the Philippines' 2028 elections. A deterrence-based fraud-scoring model with device fingerprinting and IP velocity checks protects voting integrity, while a Redis-backed batching layer keeps results updating in real time under load.
Category: Civic Tech. Role: Solo Developer. Tech stack: Vercel, TypeScript, Redis, Supabase, Next.js.
Key results: Deterrence-based fraud-scoring model combining device fingerprinting, IP/ASN velocity checks, and a disposable-email blocklist; Redis-backed batching layer absorbs high-frequency "heart" interactions and flushes to Postgres on a schedule instead of hitting the database per tap; Separate read-cache layer keeps ordinary page views off the primary database; Admin panel for reviewing and correcting the seeded candidate list as the real race clarifies.
A social platform connecting alumni and tracking their career paths geographically in real time via the Google Maps API. Batch-based communication tools and a versioned REST API keep graduates engaged with their institution long after they have left.
Category: Social Platform. Role: Full Stack Developer. Tech stack: MySQL, Inertia.js, Laravel, Vue.js, Google Maps API.
Key results: Real-time geo-tracking of alumni via the Google Maps API; RESTful architecture with proper API versioning; Enhanced alumni engagement through a batch communication system.
Source code (GitHub): https://github.com/nythosx/Alumni-Management-System-with-Social-Media-SaaS.
A multi-tenant agricultural management platform serving multiple farm operators on shared infrastructure with fully isolated data per tenant. AI-powered crop analysis via the Gemini API, live weather forecasting, and geographical farm mapping give each operator real operational insight.
Category: AgriTech. Role: Full Stack Developer. Tech stack: Gemini API, PHP, MySQL, Google Maps API, OpenWeather API.
Key results: Multi-tenant architecture supporting diverse user types; AI-driven crop analysis via the Gemini API; Real-time weather forecasting integration; Geographical farm mapping with Google Maps.
Source code (GitHub): https://github.com/nythosx/-PHP--Multi-Tenant-Crop-Farm-Management-System-with-Integrated-Analytics-and-Mapping-Features.
A full-stack fitness app for meal planning, workout logging, and nutrition analytics, built on ASP.NET Core with a React and TypeScript frontend. Personalized dashboards track calories and progress over time, all secured with JWT authentication.
Category: Full-Stack App. Role: Full Stack Developer. Tech stack: TypeScript, SQL Server, ASP.NET Core, Bootstrap, Entity Framework, React.
Key results: Personalized meal plans; Real-time calorie tracking; Workout logging with progress analytics; Secure JWT authentication.
Source code (GitHub): https://github.com/nythosx/fitness-planner.
A freelance-built HR platform unifying multi-type payroll processing, biometric fingerprint attendance, and a recruitment job portal that auto-generates PDS documents. Built to replace a client's separate, disconnected HR tools with one centralized system.
Category: HRIS. Role: Freelance Full Stack Developer. Tech stack: JavaScript, MySQL, Laravel.
Key results: Multi-type payroll processing; Biometric fingerprint attendance integration; Automated PDS document generation; Centralized employee management.
Source code (GitHub): https://github.com/nythosx/Integrated-HRIS-with-Multi-Payroll-Processing-Biometric-Attendance-and-Recruitment-Portal.