Founder & CEO @ PromptliAI | Infrastructure Architect | Building in Public
Making AI orchestration transparent. Users deserve to know why their AI chose a particular model, not just what it answered.
PromptliAI launches Q2 2026 in San Francisco — a transparent AI orchestration platform that treats explainability as an architectural requirement, not an afterthought.
The decisions we make in 2026 about AI architecture will compound for decades. I'm building systems where:
- Model selection is explainable by design
- Users see the reasoning behind AI decisions
- Transparency isn't bolted on, it's built in from the foundation
├── Moving to SF (January 2026)
├── Beta launch preparation
├── Bridging academic AI research ↔ startup implementation
└── Building the infrastructure for accountable AI systems
Production Infrastructure
- Enterprise Azure migrations, Entra ID architecture, secrets management
- Enterprise AWS with a IAC foundation
- Distributed systems, API orchestration, Terraform/Terramate infrastructure
- Security architecture & comprehensive production debugging
AI/ML Systems
- Multi-model orchestration & intelligent routing
- Privacy-preserving ML training (federated learning, differential privacy)
- Byzantine-robust aggregation, algorithmic bias mitigation
- LLM integration, prompt engineering, model evaluation
Recent Deep Dives
- Transparent AI decision architectures
- Model selection explainability systems
- Social AI features with algorithmic matching
- Production ML monitoring & observability
One model won't do it all. The future of AI isn't picking the "best" model — it's intelligently orchestrating multiple models for different tasks. But multi-model systems introduce a critical problem: opacity compounds. When your system routes between GPT-4, Claude, Gemini, or specialized models, users lose visibility into why they got a particular answer. That's not acceptable. I'm building PromptliAI because users deserve:
Transparency: Know which model handled your request and why Privacy: Your data shouldn't be exposed to every model in the ecosystem Control: Understand the tradeoffs between speed, cost, capability, and privacy
The industry is racing toward multi-model orchestration while treating explainability as an afterthought. I'm building it as the foundation — because architectural decisions made in 2026 will compound for decades.
On AI Transparency:
Foundational architectural decisions compound. If we build opaque systems in 2026, we'll be debugging their societal impacts in 2036.
On Building in Public:
I'm naturally private, deeply uncomfortable with self-promotion. But visibility matters when you're trying to change how an industry thinks about accountability.
On Technical Depth:
Real transparency requires engineering from the ground up — not dashboards slapped onto black boxes.
- 🔗 LinkedIn: linkedin.com/in/theaiguru
- 🌐 PromptliAI: promptli.ai
Currently: Building PromptliAI, moving to San Francisco, preparing for Q1 2026 beta launch
Previously: Enterprise infrastructure architect, security specialist, distributed systems engineer
Always: Asking "why" before "how"
