From guitar to code: Building GripShift

Description and use

GripShift, built using AI‑assisted Spec‑Driven Development, randomizes guitar chord pairs for one‑minute practice sessions, offering a distraction‑free learning tool.

Problem

The author lacked structured, engaging practice for guitar chords and wanted a simple, distraction‑free tool to randomize chord pairs for timed sessions.

Outcome

GripShift was built end‑to‑end using AI‑assisted development, resulting in a functional, minimal web app that randomizes chord pairs for timed practice, accompanied by a branded landing page.

Workflow

• 1. Defined project goals and constraints in AGENTS.md and SPEC.md.
• 2. Used OpenCode with DeepSeek V4 Flash and Context7 to generate initial code.
• 3. Iteratively updated SPEC and interacted with the agent to refine features.
• 4. Designed brand identity and logo using Figma and Instagram color palette.
• 5. Created landing page with Google Gemini’s HTML generation.
• 6. Deployed on Vercel and shared via LinkedIn.
• 7. Monitored visitor analytics and planned future promotion.

Evidence

The basic concept is to randomize two chords to be practiced in one‑minute sessions. No sign‑up, no login, no distractions. Simple as that.

Source

I used OpenCode as the development agent, with the DeepSeek V4 Flash model and an MCP connection to Context7.

Source

In parallel, I used Google Gemini's great HTML page‑building capability to create the first reference for the landing page.

Source