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The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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I built Vetra, an AI technical interviewer that makes interviews more structured, adaptive, and realistic.
Vetra conducts real-time voice interviews, explores a candidate’s experience, adapts its questions based on their responses, evaluates performance, and generates structured assessments.
I built the interview orchestration with LangGraph, added real-time voice interaction using Gemini Live, and created a separate evaluation layer for evidence-based scoring.
The goal was to create an AI interview experience that feels more like a real technical conversation than a chatbot.
Jonathan, keeping the evaluation layer separate from the interviewer is a smart choice. When the same model asks and scores, it tends to grade its own questions kindly. How are you handling silence and long pauses on the voice side? That was the hardest part for us on a voice AI build.
Rosso Archive — Gallery Website
Rosso Archive is a website for a contemporary art gallery — a calm, editorial space built around a single idea: twenty-four works.
We kept the interface quiet so the images can speak. Monospaced captions, a soft grey palette and generous white space give the archive the feel of a printed catalogue, while small interactions make it feel alive online.
What's inside:
— Index list view with a live preview of the hovered work
— Grid view with a colour-on-hover state for the active piece
— Work detail page with specs, description and related works
— Seamless zoom-in transitions between artworks and screens
Have a project in mind? Let's talk.
Great work, Dmytro!
I ran a session with my team on how to build a team of AI agents, and how to treat them so they actually deliver.
What we've seen running this setup on client work:
→ Agents running 24/7
→ 3B+ tokens in 6 days
→ A 2-week milestone done in 3 days
The 5 things I taught the team:
Treat agents like teammates, not software.
Give them a clear goal, the right context and tools they're comfortable with.
Tell them the goal, never the solution.
Let the agents propose the options. You make the call.
Talk to one agent, not ten.
A central PM agent takes the goal and coordinates the rest.
Solve today's problem.
Don't build the perfect agent on day one. Start small and let the team grow with the work.
Don't be the bottleneck.
Review at milestones, not every task.
For clients, this changes the pace. My job is understanding the problem and making the decisions. The agents handle the execution.
Highlights from the session 🎥
Building something and want to move faster with an AI-first team? Let's talk.