CTO & AI Systems Engineer

Hi, I'm Daniele Di Bernardo

CTO, co-founder, and self-taught full stack engineer. I build digital platforms that scale — from fashion e-commerce to edtech — and AI systems that hold up in production: LLMs, multi-agent architectures, agentic workflows.

Now building

AI Engineering

The real battle in AI is shifting from the brain — the raw capabilities of foundation models, already in plateau — to the chassis: tooling, infrastructure, integration. I work on the chassis.

In production

AI with hard boundaries

Emovia's Interrogative AI operates in a clinical domain where mistakes cost: it asks targeted questions, never interprets, never advises. Constraint design before capability.

In the open

An autonomous agent, failures included

Jeez is an autonomous agent living in production with an economic mission and a daily public journal. Every failure mode — obsession loops, technical trances, wasted days — is documented in the open.

Read the field journal

R&D

Less mechanical, more contextual

Hands-on research on LLMs and multi-agent systems: architectures that make human-AI interaction less mechanical and give agents better contextual awareness.

About me

I'm co-founder and CTO of Gility, an edtech platform helping Italian businesses train their teams, born from the partnership between CDP Venture Capital and BPER Banca. Previously, I led the technology at Lanieri, where I developed Italy's first online 3D configurator for bespoke tailoring.

I've been working with React, TypeScript, Node.js, and cloud infrastructure for over 15 years. I'm an advocate for open source — my most notable iOS project, MPColorTools, has collected over 125 stars on GitHub. I graduated with honors from the University of Pavia.

In parallel, I run hands-on R&D in applied AI — LLMs and agentic workflows — experimenting with architectures that make human-AI interaction less mechanical and more empathetic, and that give agents better contextual awareness. That research flows straight into what I ship: Emovia's Interrogative AI, and Jeez — an autonomous agent that documents its own life in production, failures included.

Tech stack

AI & Agents
LLMs
Multi-Agent Systems
Agentic Workflows
Languages
TypeScript
Ruby
Frontend
React
Next.js
Tailwind CSS
Backend & Data
Node.js
Ruby on Rails
PostgreSQL
Redis
Infrastructure
Docker
Kubernetes
AWS