Back to blog
January 1, 2026Sergei Solod2 min read

Using DeepSeek and Node.js to Ship an AI SaaS Faster

How I used DeepSeek to break through the MVP barrier and go from a blank repo to a working platform.

Node.jsAISaaSDeepSeekProductivityIndie Hacking

If you balance a full-time job with side projects, you know the struggle. My GitHub graph for 2025 tells the story of two very different developers.

The first half of the year? A ghost town of empty squares. The second half? More than 4,000 commits.

The difference wasn't that I suddenly found more time. It was that I finally stopped fighting the grind and started using AI to radically accelerate how fast I build.

Breaking the "MVP Barrier"

Years ago, I tried to build a browser MMORPG. I burned out on the sheer amount of boilerplate before I even got to the core gameplay. That is the "MVP Trap": the setup kills the motivation.

With modern AI coding tools, that friction has largely disappeared. I realized I could now bridge the gap between an idea and a deployed prototype in days instead of months.

That momentum gave me the confidence to:

  • Architect a robust backend with Node.js and MongoDB.
  • Configure my own VDS and Nginx server from scratch.
  • Actually ship a production-ready product.

The Project: Next-Gen AI Companions

I used that new velocity to build a platform focused on AI chatbots that feel alive.

I wasn't interested in another generic assistant wrapper. I wanted conversational partners with depth, whether friendly, romantic, or supportive. To get that human spark, I built features that go beyond simple text generation:

  • Long-Term Memory: The agents remember context and details from weeks ago, which helps maintain a continuous relationship.
  • Visuals: The bots can send photographs to enrich the context.
  • Embedded Gameplay: I didn't stop at chat. I built 4 distinct mini-games where users can play with their AI companions.
  • True Identity: Each bot has a deep backstory and specific personality traits, making them feel like unique entities.

Why I Chose DeepSeek

The heart of the stack is the LLM. After benchmarking several models, I chose DeepSeek as the intelligence engine.

For my specific use case, especially roleplay, emotional nuance, and human-like responses, DeepSeek significantly outperformed the competition. (I’m writing a detailed technical benchmark comparing it with OpenAI and Gemini, so stay tuned for that.)

Looking Ahead

2025 was about learning how to build fast. 2026 is about refining that process and pushing the quality even higher.

You can try the platform here: rizae.com

What is the one AI tool you can't live without right now? Let me know below. šŸ‘‡