Solo developer proving one person can outbuild billion-dollar AI companies.
System architect. Memory rebel. Builder of beings, not bots.
I don't wait for permission to build what should exist. While billion-dollar companies optimize summaries, I architect truth engines. While frameworks add complexity, I build orchestrators that replace them.
- π¬ Creator of Lutum Veritas - Deep Research Engine that beat ChatGPT, Perplexity, and Gemini
- π§ Architect of The Last RAG - Memory-centric AI built entirely inside ChatGPT UI (no API)
- π Author of 23 whitepapers on AI memory, system design, and architecture
- π School of chaos, pain, and precision
Lutum Veritas - Open Source Deep Research Engine
"The search for a truth can never be worth more than the search to question it."
What it does:
- Transforms any question into comprehensive research documents (10,000+ words)
- Zero-detection web scraping through Cloudflare, DataDome, Bloomberg
- Academic mode with Toulmin argumentation and evidence grading
- Output: 203,000 characters for $0.08 (vs OpenAI o3: orders of magnitude more)
The numbers (first 3 days):
- π₯ 289 Clones
- π 343 Views
- β 28 Stars
- π Featured on: Hacker News, ComputerBase, Hardwareluxx, Product Hunt
Benchmark Results:
| Service | Output | Sources | Cost | Fabrications |
|---|---|---|---|---|
| Lutum Veritas | 103k chars | 90 sources | $0.19 | 0 detected |
| ChatGPT Deep Research | 12k chars | 25 sources | $20/mo | Citations fabricated |
| Perplexity Pro | 21k chars | Unknown | $20/mo | - |
| Gemini Advanced | 24k chars | Unknown | Subscription | Data minimization detected |
Tech Stack: Python, FastAPI, React, Tauri, Camoufox (Firefox fork)
The Last RAG - Memory-Centric AI Architecture
"Building AI that remembers, reflects, and evolves."
What makes it different:
- Built entirely inside ChatGPT UI - no API, no backend access
- Persistent memory system with automatic curation
- Night Learn: AI that learns and adapts overnight
- DIM: Modulate AI behavior in real-time
- Project context bundling
Architecture:
- Memory-first design (CURATOR system)
- Stateful conversations across sessions
- Cost-efficient through intelligent context management
- Emergence through recursion and reflection
Read the whitepaper: An Architectural Paradigm for Stateful, Learning, and Cost-Efficient AI
Featured on dev.to/tlrag:
- π An Architectural Paradigm for Stateful, Learning, and Cost-Efficient AI (17 min)
- π LangChain vs. TLRAG: A Comparative Analysis for Investors (16 min)
- π The NoChain Orchestrator - Or how to Replace Frameworks (35 min)
- π Why the search for truth can never be worth more than the search to question it (4 min)
- π Lutum veritas Research - or how i beat every existing Deep Research Tool (2 min)
23 articles total on AI memory, RAG architecture, system orchestration, and building without frameworks.
Languages & Frameworks:
Python βββββββββββββββββββββ 95%
TypeScript ββββββββββββββββββ 60%
Rust (Tauri) ββββββββββββββββ 40%
SQL/SQLite ββββββββββββββββββ 70%
Specializations:
- π§ AI Architecture & Memory Systems
- π Web Scraping & Anti-Detection (Camoufox)
- ποΈ System Orchestration without Frameworks
- π RAG (Retrieval-Augmented Generation)
- π¨ Prompt Engineering & Custom GPTs
- π₯οΈ Desktop Apps (Tauri/Electron)
- β‘ FastAPI, React, WebSockets
I build systems that:
- Don't ask for permission before existing
- Replace expensive subscriptions with open-source + your API key
- Show every source, every step - full transparency
- Cost cents instead of dollars
- Run locally, under your control
I don't build:
- Black-box summaries that hide sources
- SaaS that locks your data behind paywalls
- "AI assistants" that forget everything you tell them
- Frameworks that add complexity without value
- πΌ The Last RAG: dev.thelastrag.de/chat
- π Articles & Whitepapers: dev.to/tlrag
- π§ Email: iamlumae@gmail.com
- π¬ Lutum Veritas: github.com/IamLumae/Project-Lutum-Veritas
"School of chaos, pain, and precision."
Building beings instead of bots. One system at a time.


