Picking The Right Tool for the Right Job

A Second Look at V0 and Replix

Context: Why This Matters 📚

Building good software isn't about picking the "best" tool. It's about picking the right tool for the job at hand.
After a week spent building real architectures—reusable auth, storage components, and monorepos—with Augment, Codex CLI, and Claude, I turned this weekend toward two "quick projects" and stress-tested two rising AI dev tools: V0 and Replix.

The results? Picking the right tool still matters. Both tools are getting better, but still struggle with the last mile—in different areas.

Two Weekend Projects, Two Different Needs 🛠️

• Project 1: Build a simple knowledge bot for a travel agent client.

• Project 2: Replace my band's Squarespace site with something leaner (and cheaper).

Both needed speed, flexibility, and low overhead. Both turned into a revealing snapshot of where V0 and Replix actually stand today.

First Up: V0 and the Streaming Chatbot 🤖

Started with V0, aiming for a basic streaming chatbot UI.

Wins:

• Got the initial chat interface built quickly.

• Correctly used server routes, not just client-side calls.

Misses:

• Defaulted to direct OpenAI API calls, without even using OpenAI's own SDK.

• Never suggested Vercel's AI SDK, which would have been a better fit for a Vercel-hosted app.

• Struggled heavily with OpenAI's Assistants API and streaming responses.

After multiple attempts to re-steer it—server-side streaming, Assistants thread management—it became clear V0 wasn't there yet for complex API behaviors.

Verdict:

• Fine for front-end scaffolding.

• Still needs heavy hand-holding for non-trivial back-end logic.

[Technical Note:] SDKs like Vercel's AI SDK or OpenAI's SDK aren't just wrappers—they handle retries, error normalization, streaming parsing, and authentication edge cases cleanly.
Skipping the SDK and calling APIs directly often works for simple demos but almost always blows up at scale or under streaming pressure.

Next Up: Replix Gets Serious 🚀

Switched to Replix to rebuild the same chatbot.

Improvements:

• Much sharper model.

• Understood Next.js + TypeScript instructions without too much drama.

• After a few rounds, agreed to:

  • Use the real OpenAI SDK.

  • Stream responses properly.

  • Stick to current APIs instead of falling back to outdated behavior.

Verdict:

• Replix delivered a clean, working chatbot, including streaming assistants output, in a few hours.

• Much improved over a month ago. Worth a second look for bigger projects.

V0's Redemption: Band Website Rebuild 🎸

Before writing off V0, it had a second chance: rebuilding my band's website.

Problem: Squarespace is great—if you're a business, with non-technical editors and the need for polished templates.
But for a hobby band? $40/month is overkill—especially when the "big asks" were simple:

• We wanted a custom domain.

• We needed basic form submissions (like gig inquiries).

Nothing massive, but it pushed us into a higher pricing tier fast.

We already used Google Drive for media and gig schedules. The question:
Could V0 build a simple, auto-updating site pulling from Drive?

Outcome:

• V0 copied the Squarespace design well enough.

• Converted the project into a single-page scroller for speed.

• Integrated Google Drive and Sheets APIs surprisingly smoothly.

• Handled form submissions to Sheets, and even recommended using Google Forms endpoint submissions instead of direct writes—catching a design flaw I missed.

Hidden Gotchas: Next.js 15 Compatibility and TypeScript Mess ⚠️

Here's what doubled my time on the band project:

V0 still scaffolds against outdated Next.js 14-era configurations.

The major problems:

• Still uses deprecated fields like experimental.serverComponentsExternalPackages and experimental.runtime, both removed in Next.js 15.

• Requires manual fixes:

  • Move serverComponentsExternalPackages into the top-level config.

  • Declare runtimes per-page, not globally.

• Native modules like sharp now require explicit approvals.

• No type-checking scripts (tsc --noEmit) scaffolded by default.

• Worse: the generated code was littered with TypeScript errors—missing types, bad imports, broken component props.

You don't just have to fix configurations. You have to tighten and correct the typing everywhere yourself.
This isn't "launch-ready" code. It's half a project.

There's no version targeting in V0 yet. No formal warnings either.

Bottom line: Treat V0's output as a first draft, not production code. Audit and refactor before shipping anything serious.

Bonus Insight: Google Drive as a CMS 📂

One thing that stood out:

Using Google Drive as a lightweight CMS worked brilliantly.

For a small, informal group like a band, it's unbeatable:

• Gig dates in a Google Sheet.

• Photos, videos, and logos in Drive folders.

• Minimal web maintenance needed.

Honestly, this could work for a lot of small teams, clubs, or side projects who don't want to mess with WordPress, Webflow, or bloated CMSes.

There's a product idea lurking here. Hmmm...

Final Reality Check: The Last 20% Is Still Hard 🛤️

After all that? Here's the coda:

Turns out Replix couldn't get OpenAI's streaming API fully functional either.
I gave Augment a try—same story.
Finally turned to Codex, which is cranking away now... ...thinks it has an answer...but as of writing, no working solution yet.

Bottom line:

• Two relatively simple projects.

• 80% done very quickly.

• The last 20%? Painful.

It took four different agentic coders (V0, Replix, Augment, Codex) just to get across the finish line.

That's where we are in 2025.

Fast prototyping? ✅
Solid, production-grade AI-integrated apps? Still a slog.
Tooling is evolving. But "fully hands-off" still isn't real yet. Not when you actually care about it working.

That's not surprising.
That's what real engineering always looked like.

Key Takeaways 📋

• V0 is fast at UI-first prototyping, but needs serious post-generation hardening to be production viable.

• Expect TypeScript errors, broken configs, and outdated Next.js usage if you target modern stacks.

• Replix has matured into a credible tool for full-stack AI-driven scaffolding, especially around newer streaming architectures.

• Speed of iteration matters—but so does quality of output.

• Leveraging existing ecosystems like Google Drive can create fast, scalable "just enough CMS" solutions for lightweight projects.

Closing Thought ✨

AI dev tools are getting better. Fast.
But they're still just that: tools.

If you want to ship real products?
You still have to drive.

And that's still the fun part.

Additional Coda

One more lesson from the trenches:

Claude ended up saving me after I wasted far too long debugging a systemic environment variable bug V0 introduced. Meanwhile, Replit threw together a rough chat UI using the older API version — not perfect, but good enough to get moving. And I did what I should have at the start, use a package (botpress) to build the chat UI.

And that’s the real point: Agentic coding isn’t about perfection. It’s about getting to “good enough” fast—and then handing it off to real engineers to finish the job.

If you’re waiting for the tools to be flawless, you’re missing the opportunity. Speed to prototype still wins.