I Spent 54.6M Tokens Vibe Coding With Gemini 3 Pro | My Thoughts On Its Vibe Coding Capabilities
I ran 54.6M tokens through Gemini 3 Pro in Cursor 2.0 to see how it actually handles vibe coding on real production work. In this session I push ViewCreator’s UI toward a cleaner, responsive redesign, ship a few backend features (like “enhance with AI” for YouTube titles/descriptions/tags), and compare speed, cost, and reliability against my usual stack. If you care about practical vibe coding performance, stable diffs, and where Gemini 3 Pro fits in a day-to-day cursor workflow, this is a clear, candid review.
🌐 Links
ViewCreator (Open Beta): https://www.viewcreator.ai
BridgeMind: https://www.bridgemind.ai
Discord (join the community): https://bridgemind.ai/discord
YouTube: / @bridgemindai
X (Twitter): / bridgemindai
Instagram: / bridgemindai
⏱️ Chapters
00:00 — 54.6M tokens to test Gemini 3 Pro for vibe coding
03:00 — UI wins and responsive cleanup in Cursor 2.0 using Gemini 3 Pro
08:00 — Backend features, cost/speed takeaways, and where Gemini 3 Pro fits
Keywords: vibe coding, Gemini 3 Pro, Cursor 2.0 vibe coding, Gemini 3 Pro review, Gemini 3 Pro UI, Gemini 3 Pro coding, production vibe coding, ViewCreator
#VibeCoding #Gemini3Pro #Cursor #Cursor2 #BuildInPublic #ViewCreator #AICoding #IndieDev #DeveloperTools