Christopher Clark's profile on Product Hunt

About

I design and develop scalable systems that power real-world applications. I enjoy turning complex problems into simple, elegant code. Clean architecture and performance matter deeply to me. I continuously learn new technologies to stay ahead. For me, coding is both logic and creativity combined.

Badges

Gemologist

Tastemaker

Gone streaking

Forums

p/sidedisplay

•

1d ago

SideDisplay for Windows v1.4.0 — Multi-Display Support

Hey everyone! We just shipped v1.4.0 of SideDisplay for Windows with some big updates.

What's new

Multi-Display Support You can now connect up to 3 devices at the same time, each running as its own independent virtual display. Perfect if you want to spread your workspace across a tablet, phone, and Tesla screen all at once.
Per-Display Settings Each connected display now has its own resolution and DPI scaling settings. Click on a display card to configure it individually.
Trial Timer Fix Previously the trial timer kept counting even when your browser disconnected or refreshed. Now it correctly pauses when no device is connected and resumes when you reconnect.
Stability Improvements Better handling of port conflicts, fixed popup positioning issues, and more reliable diagnostics reporting.

p/vois

•

3d ago

[Extended] Easter weekend deal: $10/mo locked in for life (normally $29)

Quick one. I've been building software for over 20 years, and I've never done a seasonal discount before. But we just passed 40 free users, and I wanted to give people a reason to jump in this weekend.

The offer:

- Monthly plan locked in at $10/month (normally $29/month)

- That's 66% off, and the rate stays for as long as your subscription is active

•

2d ago

Featured

Are we over-engineering AI memory? (Markdown vs. Vector DBs for small datasets)

Hey makers!

Lately, I ve been looking closely at how independent builders and small teams are managing AI knowledge bases. It feels like the default "industry standard" is to immediately reach for a complex RAG pipeline and a heavy, paid Vector Database.

But I'm starting to wonder if we are over-engineering this for 90% of standard use cases.

Vector DBs are incredibly powerful for massive scale, but for smaller or non-massive datasets, they can be expensive, complex to query, and act as complete black boxes. If a search returns a weird chunk, diagnosing it is often a nightmare.