Vibe Coding in Practice
We build a production-grade AI dashboard together using Codex, ship it in your GitHub, and leave you with the workflow to keep building.
Outcome: You leave with a deployed dashboard, a GitHub repo, $200 of OpenAI credits covered by me for the build, and the ability to keep shipping without waiting on freelancers.
Point of view: This is the offer for when you want more than advice. You want the product in your hands, deployed, and explained well enough that you can keep building on it yourself.
Includes: 4-week build sprint
Includes: 5 live build hours each week
Includes: $200 OpenAI credit budget covered by me so you can build the app
Includes: Production-grade AI dashboard architecture and implementation
Includes: GitHub, deployment, and builder workflow handoff
Deliverable: A scoped dashboard plan with the sharpest first version defined
Deliverable: A working production-grade AI dashboard built in your GitHub repo
Deliverable: A deployed app with the right auth, data, and AI workflow boundaries
Deliverable: $200 of OpenAI credits included free from my side for Codex-assisted implementation
Deliverable: A walkthrough of the architecture, stack, prompts, and tradeoffs
Deliverable: A repeatable vibe coding workflow you can keep using after the sprint
Best fit: You have an AI dashboard or internal tool idea but no engineering team.
Best fit: You are tired of no-code tools breaking when you need real functionality.
Best fit: You want to learn by shipping your product, not by watching tutorials.
Best fit: You can commit to decisions, feedback, and five focused hours each week.
Not the fit: You need a fully staffed engineering agency.
Not the fit: You want a passive course with prerecorded lessons.
Not the fit: You are still deciding whether the problem matters.
Not the fit: You cannot make weekly decisions during the sprint.
Week 1: Scope the dashboard
Summary: We turn the idea into a tight dashboard spec, choose the stack, set up the repo, and define what production-grade means for this first version.
Session work: Map the user, core workflow, dashboard screens, and the first must-ship outcome.
Session work: Choose the stack, hosting path, database shape, and AI boundaries before coding.
Session work: Set up GitHub, project structure, environment variables, and the Codex working loop.
Session work: Create the build checklist so every session has a clear output.
Deliverable: Product brief, repo setup, technical shape, and first build tickets.
Week 2: Build the core
Summary: We build the main dashboard surface, connect the first real data path, and use Codex to move from blank repo to working product quickly.
Session work: Implement the core dashboard layout, navigation, and primary interaction flow.
Session work: Add the first database/API integration or structured mock path if real data is not ready.
Session work: Use the $200 OpenAI credit budget I include free from my side for Codex-assisted implementation and iteration.
Session work: Review every major code decision so you understand the system, not just the result.
Deliverable: Working dashboard core with the main user path running locally.
Week 3: Make it production-grade
Summary: We harden the dashboard: auth, persistence, error states, responsive UX, and the pieces that make it safe enough to show real users.
Session work: Add auth, permissions, persistence, loading states, and failure paths where needed.
Session work: Polish the dashboard UX so it feels like a product, not a demo shell.
Session work: Tighten prompts, model calls, data validation, and human review boundaries.
Session work: Prepare deployment configuration and the production environment checklist.
Deliverable: Production-ready dashboard build with deployment path and edge cases handled.
Week 4: Ship and hand off
Summary: We deploy, clean the repo, document the system, and make sure you know how to keep building with Codex after the sprint ends.
Session work: Deploy the dashboard and verify the live production path.
Session work: Write the handoff notes: architecture, commands, environment variables, and next tickets.
Session work: Record the builder workflow: how to prompt Codex, review changes, and ship updates.
Session work: Define the next roadmap so you can continue without losing momentum.
Deliverable: Live dashboard, documented repo, handoff walkthrough, and next-build roadmap.
Harshith Vaddiparthy works with founders, operators, and teams on practical AI products, workflows, advisory, training, and mentorship. This no-JavaScript version preserves the page's core information and navigation.