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JamDev0/README.md

Hi, I'm Juan Garcia

LinkedIn WakaTime

Full-stack engineer in constant growth — I focus on reliable APIs, validation-first backends, and modern React/Node apps. I like to ship things that are safe to change and easy to run.


About

I build and maintain backend and frontend systems with an emphasis on clarity, validation, and maintainability. My work centers on TypeScript, Node, React, and related tooling so that apps and APIs stay consistent and predictable.


Table of contents


Work at Future Secure AI

I contributed as a full-stack engineer across the Future Secure AI platform (Sep 2025 – Feb 2026), focusing on reliability, security, and validation so that systems are safer to run and easier to release. All work product and intellectual property from this engagement are the sole property of Future Secure AI.

Impact at a glance

Metric Value
Signal commits 579
Pull requests 226
Merged PRs 192
Acceptance rate ~85%
Repositories 5 core products

Contribution by project

Project Role Focus
flowx Major driver Platform stability, integration reliability, test coverage, security hardening, CI/Docker
fsaiosapi Major driver (backend) Request/schema validation, API security constraints, auth and token flows
fsaiosapp Major contributor API-doc proxy, secure gateway, auth alignment with backend
ai-flow Major contributor Validation middleware, Swagger/config hardening, dependency and container hygiene
langfuse-fsai Major contributor Iframe auth compliance, test stability, input validation

Areas of impact

  • Reliability: Fixes and refactors across integration-heavy systems to reduce production risk and support load.
  • Security: Dependency and image remediation, input validation, and auth/token consistency across services.
  • Quality: Expanded test coverage and validation patterns so releases are safer and rollbacks rarer.
  • Delivery: CI/workflow and pipeline updates for more confident shipping.

PR stats above were gathered with scripts/github-pr-stats-gh.sh (gh CLI + jq). Commit metrics are from local workspace analysis.


Personal projects

Side projects I build and maintain — mostly Next.js, React, and TypeScript, with a focus on clear specs and offline-first or self-hosted use.

Project Description
cc-feedback In-product feedback capture: overlay UI, SDK (core + web), and API contract for issue and capability reports with optional text, voice, and screenshot. Monorepo with React overlay, multipart submit, and mock API for local dev.
cc-mobile-practice Mobile web app for PDF-based exams: tap-to-place answer markers, assign tokens (A–E), import a gabarito (answer key), and review/grade attempts. Offline-first, no account; IndexedDB + react-pdf. Integrates cc-feedback for in-app feedback.
idle-page Desktop-first ambient app: rotating media (images, GIFs, videos, quote cards) plus a TODO checklist from a local markdown file. Darkroom visual identity (red safe-light, film grain, vignette). File watcher, prefetch, optional Docker; settings in localStorage.
speed-reading Mobile-first RSVP (Rapid Serial Visual Presentation) speed-reading web app. Next.js App Router, Web Worker tokenizer, calibration and onboarding flows. Vitest + Playwright; spec-driven implementation.

Tech & tools

Languages & runtime

TypeScript Node.js

Frontend

React Next.js Vue.js Tailwind CSS

Backend & APIs

NestJS Express OpenAPI/Swagger

Data & auth

PostgreSQL TypeORM Prisma Supabase

Tooling & DevOps

pnpm Docker GitHub Actions Git Jest ESLint

How I work with AI agents

I use AI coding agents as a force multiplier in my daily work — not to replace thinking, but to extend it with clear instructions and guardrails.

What I do Why it matters
Structure tasks in phases I break work into numbered steps (e.g. "0a. gather data; 1. produce report") so the agent has a clear sequence and I can refine one phase without redoing everything.
Ask for evidence-based outputs I prefer results grounded in the codebase (commits, dependencies, lockfiles) so reports, tech stacks, and impact summaries are defensible for reviews and leadership.
Inject context via skills and plans I attach skills (e.g. OS context, conventions) and reference plans or specs so the agent follows my environment and standards instead of guessing.
Choose the right tool for the job I explicitly say when to use the browser, the shell, or the repo (e.g. "use the browser" for live UX analysis) so outputs match the task.
Iterate until value is clear I don't stop at the first draft: I ask "does this make my contribution clear?" and request refinements (ownership matrix, noise filtering, value-by-project) until the artifact is usable.
Reuse one evidence chain The same data (e.g. commit analysis) feeds contribution reports, tech stack lists, LinkedIn title, and this README — one source of truth, consistent story.
Design then implement For bigger efforts I use the agent to brainstorm and document a plan (with options and trade-offs), then hand off the plan for implementation with todos and tests (including "how do I test in isolation?").

I also create skills and rules (e.g. OS-context discovery, browser-priority rules, project conventions) so agents behave consistently across sessions and workspaces. To stay current, I follow AI/tech trends mainly on X (Twitter) — I was an early adopter of Ralph loops and similar agentic patterns, and I keep an eye on emerging coding-agent workflows so I can evaluate and then adopt and adapt quickly.

In short: I treat agents as reliable teammates — I specify scope, provide context, ask for evidence and iteration, and reuse outputs across docs and automation so my profile and deliverables stay aligned with what I actually ship.


Stats

Most used languages (WakaTime)

WakaTime languages

GitHub stats

GitHub stats

Recently watched (YouTube)

Full history: youtube-watch-history.md

Last synced: 05/03/2026, 08:09 (Brasília) · Next sync: ~05/03/2026, 22:00 (Brasília)

Title Author
thumb Inside America's Top Hackathon Soon
thumb 🚨🚨 PEWDIEPIE DOES IT AGAIN... -- Then Standup -- Casey Presents NotePad++ 🚨🚨 The PrimeTime
thumb Making a ridiculously heavy tungsten suit (it broke my body) NileBlue
thumb The World's Best Watch Is Only $20 Hunter Wears Things
thumb A IA Quebrou o Modelo do GitHub Augusto Galego

Get in touch

Email LinkedIn

Pinned Loading

  1. DtMoney2 DtMoney2 Public

    TypeScript 1

  2. coffe coffe Public

    Um e-commerce de cafés

    TypeScript 1

  3. Pomodoro Pomodoro Public

    TypeScript 1

  4. dtmoney dtmoney Public

    Site para monitorar suas finanças

    TypeScript 1

  5. To-Do-Do-Do To-Do-Do-Do Public

    Site para registrar suas tarefas. Fruto do desafio do curso da Rocketseat

    TypeScript 1

  6. IgniteFeed-Typescript IgniteFeed-Typescript Public

    Site que emula um feed de rede social

    TypeScript 1 1