I find broken signal layers and rebuild them as infrastructure. Three years on OM. Ten years pattern-matching.
Revenue systems break because the signal layer is broken. I rebuild the signal layer.
Three case studies, three facets of the same operator credential. Cisco is the diagnostic muscle — find what's actually broken, not what management thinks is broken. Mesh-AI is the productization move — convert what you build internally into what gets sold externally. OM is the synthesis — apply both moves to an entire category instead of a company. The pattern accumulates across the three; reading all of them is the argument.
The same operator move at category scope — diagnose the broken signal layer underneath modern GTM, build the platform every AI-native company is currently rebuilding in-house, badly. 88K jobs from 1,667 source boards, 186-node skill graph, sub-$1/day LLM spend. Solo.
Read case study→ Or jump to the system design→Internal infrastructure became the product surface. Twelve dashboards built for executive reviews became the demo, then the wedge that converted bespoke consulting into reusable software. $0 → $10M ARR in twelve months as employee #13.
Read case study→The brief was "build more dashboards." I diagnosed the actual bottleneck — compile latency, not analyst capacity — and architected the solution that the brief, taken literally, would have made worse. $10M+ annual productivity, 1,000+ AEs across 47 countries.
Read case study→Complexity is the enemy of execution.
I'm a systems thinker who believes elegant solutions emerge from deep understanding of the problem. Every layer of complexity should justify its existence. This is the lens behind everything I build — from analytics platforms at Cisco and Mesh-AI to OM today.
Grew up in a Bulgarian village. Studied at UCL. Now building in San Francisco. Three countries, one philosophy: find what's broken, rebuild it simpler.
Open to conversations on GTM infrastructure, AI-native B2B, or whatever you're trying to make less broken.