Daniel Pyrathon

Grok Code Fast 1: Vim Energy for AI Pair Programming

Daniel Pyrathon1 min read
Software Engineer at Farcaster • Founder of Bountycaster

Grok Code Fast 1: Vim Energy for AI Pair Programming

Recently, while working on some Farcaster code, I realized something simple but important: if you know what you’re doing, faster models often beat the benchmark champions. This is especially true if you’re using AI as a copilot and not 0‑to‑1 feature coding. Why? Because faster models keep you in flow, focused on the real problem, and less likely to context‑switch.

As someone who really struggles with context switching, I’ve asked myself why I’m often just as fast building features without an agent (GPT‑5 or Claude Code). Even when the agent gets most of the way there, I still have to 1) get back into context 2) review the code 3) fix bugs. Because most of us try to be efficient with our time, it’s second nature to reply to Slack, triage a bug, or answer a DM. That doesn’t bring net positive value. It would be faster—and less mental overhead—to stay locked in and build the feature.

The Vim analogy

I grew up using Vim (MacVim, now Neovim). Switching to full IDEs (for me it happened with TypeScript when I joined 0x) brought plenty of bells and whistles, but I still believe I did my best work in Vim because I never had to context‑switch. My eyes stayed on the code—no distracting panes, no notifications, no code assistants trying to help but getting in the way.

I think of this as similar to using large AI models like GPT‑5 or Opus to implement and review code. These models are multi‑turn thinkers—absolutely incredible and useful—but they can also nudge me into longer loops and more context switching.

My current daily driver: Grok Code Fast 1

Grok Code Fast 1 showed up in Cursor for free, so I tried it. It’s surprisingly good—and fast—and I don’t get the feeling I need to context‑switch. It reminds me a bit of GPT‑4o: useful because it’s responsive. It also feels aligned with my style—no‑bullshit and to the point.

When to use the big models

The largest models—GPT‑5 especially—have saved me an immense amount of time for research and understanding complex codebases, and they’re powerhouses for large multi‑file refactors. In these scenarios, even waiting 30 seconds to 1 minute for the initial prompts is worth it because they save tens of hours. Example: a significant refactor of Farcaster’s mini‑app backend—I used GPT‑5 for research, planning, and implementation. Massive win.

On the other hand, for smaller tasks that require close pairing, faster models like Grok Code Fast 1 are a massive win. They’re faster, they keep you locked into the task at hand, and you’ll doomscroll way less.

Summary

If you also suffer from context switching, give Grok Code Fast 1 a try. It feels more like Vim than a heavyweight IDE: fast, real, and always in your lane. Staying in flow often beats chasing the absolute best benchmark number.