Weekly Recap #4: The Art of Stress Testing and The Feedback Loop

Building in a vacuum is the silent killer of engineering projects. You can write the cleanest TypeScript, optimize your vector embeddings to perfection, and architect a beautiful micro-services pattern, but if it doesn't solve a problem for a human being, it’s just digital dust.

Welcome to Week 4. This was the "Montage Week."

If you've been following the previous dev logs, you know we've moved from ideation to architecture, and then to rapid prototyping. But this week, I stopped building new features. I stopped pushing commits to main blindly. Instead, I shifted gears to Proof and Refinement.

I asked for feedback. I looked at the ugly analytics. And I made a plan to finish strong.

The Build Montage: What’s Actually Running?

Before we dive into the feedback, let’s look at the snapshot of the system as it stands today. We aren't dealing with localhost dreams anymore; this is live infrastructure.

• The Core: A Multi-Agent RAG system built on LangChain and OpenAI’s GPT-4o.
• The Database: Supabase (PostgreSQL) with pgvector for semantic search.
• The Frontend: Next.js 14 (App Router) deployed on Vercel.
• The Glue: Custom serverless functions handling the webhook events between Stripe and the user dashboard.

This week, I wired these isolated components into a cohesive flow. The goal was to see if a user could go from Landing Page -> Auth -> First Agent Interaction without hitting a 500 error.

The "Ask Feedback" Strategy

Most developers wait until the product is perfect to ask for feedback. That is a mistake. I deployed a "beta" tag and went hunting for criticism.

Where I went for signal:

1. Twitter/X Engineering Circles: I didn't post generic "marketing" fluff. I posted architecture diagrams and specific code snippets regarding token optimization. This attracted other builders, not bots.
2. Discord Communities: I dropped the repo link in specialized AI dev Discords, specifically asking for a security roast.
3. Cold DMs: I reached out to 5 users who starred the repo on GitHub and asked them one question: "Where did the documentation fail you?"

The Analytics: Hard Truths

Feelings don't scale. Data does. I hooked up PostHog to track event conversion, and the results were humbling.

The Funnel Breakdown

• Unique Visitors: 1,240 (Week 4 spike due to X thread)
• Sign-ups (Auth): 180 (~14.5% conversion)
• First Agent Execution: 45 (~25% of signed-up users)

The Insight: My sign-up conversion is decent, but the drop-off between Sign-up and Using the Tool is massive (75% churn immediately). Why?

The Feedback: Based on the DMs, the onboarding UI was too complex. Users didn't know they needed to bring their own API key for the initial tier. I assumed they read the README. They didn't.

Git Metrics

• Repo Stars: +42 this week
• Forks: 8
• Issues Opened: 5 (3 of which were critical bugs regarding environment variables)

What I’d Do Differently

Looking at the montage of the last 30 days, hindsight provides 20/20 vision. If I were restarting this sprint today, here is what I would change:

1. Documentation First, Code Second

I spent 40% of Week 4 fixing bugs that were actually just misunderstandings of how to configure the .env file. If I had written a robust documentation site (using Mintlify or similar) during Week 2, I would have saved hours of support time.

2. The "Configuration Hell"

I over-engineered the agent customization. I gave users 20 knobs to turn (temperature, chunk size, overlap, K-value). In reality, users want a "Magic Button." I should have hard-coded reasonable defaults and hidden the complexity behind an "Advanced" toggle.

3. Observability

I added logging too late. Debugging a hallucinatory agent in production without tracing (using LangSmith or Helicone) is a nightmare. I spent Monday just digging through Vercel logs trying to find why a specific prompt chain failed.

The Pivot: Reaction to Feedback

Based on the feedback loop, I pushed three critical hotfixes this week:

1. The Onboarding Wizard: I ripped out the static dashboard and replaced it with a 3-step wizard that guides the user to input their keys and set up their first agent.
2. Error Handling: Instead of a generic "Something went wrong," the UI now parses the OpenAI error object and tells the user if it's a Rate Limit, a Context Length Exceeded, or an Invalid Key error.
3. Streamlined UI: I removed the "Vector Database Settings" panel entirely. It's now managed automatically in the backend. Users don't care about vector dimensions; they care about answers.

The Final Push: The Plan for Week 5

We are in the endgame now. The features are locked. No new agents. No new integrations. The remaining days are about Polish and Distribution.

The Checklist

• Performance Audit: Run Lighthouse scores and optimize the Next.js bundle size.
• SEO Pass: Ensure every page has dynamic OpenGraph images and proper meta tags.
• The "Launch" Video: I’m recording a 60-second Loom/Screen Studio demo that cuts straight to the value proposition. No fluff.
• Readme Overhaul: The GitHub Readme will be rewritten to focus on "How to start in 5 minutes."

Conclusion

Week 4 taught me that code is only as good as the feedback loop that refines it. You cannot automate empathy. You have to talk to users, look at the brutal charts, and be willing to delete features you spent days building.

Next week is the finale. We ship the final version. I’ll share the full breakdown of the stack, the final costs, and the revenue (if any).

Let’s build.