What this is

Mindent is a space for exploring AI systems, orchestration patterns, and agentic workflows. It is where I experiment with ideas that may or may not become products.

The focus is on understanding how to build reliable systems with AI components — not demos, but actual working software that handles edge cases and fails gracefully.

Why it exists

The current wave of AI tooling is exciting but often shallow. Most tutorials and examples show happy paths. Few address what happens when models hallucinate, when context windows overflow, or when orchestration logic becomes a tangled mess.

I wanted a dedicated space to work through these problems slowly and carefully, without the pressure to ship something immediately. Mindent is that space.

What problem it is trying to solve

There is a gap between AI research and AI engineering. Research produces impressive papers and demos. Engineering requires handling the unglamorous details — retries, fallbacks, validation, observability, cost management.

Mindent is my attempt to develop practical knowledge about building AI systems that actually work in production conditions. The learning is the point.

Current state

Mindent is mostly internal right now. I have built several experimental tools and workflows that I use personally. None of them are polished enough to share publicly.

The work includes experiments with multi-agent orchestration, tool-use patterns, and hybrid systems that combine LLMs with traditional software. Some of it may eventually become open source or products. Some of it will remain notes and prototypes.

How I think about its future

I have no specific goals for what Mindent should produce. It might generate research, products, or nothing public at all. The value is in the exploration.

If something useful emerges, I will share it. If nothing does, the knowledge still transfers to other work. Mindent is structured as an investment in understanding, not a commitment to output.

Technologies: LangChain, AI Agents, RAG Systems, Python, FastAPI

Related Projects: Sparrow Intelligence | RepoEngine