Listen for the friction.
The best product opportunity is often hiding inside a daily annoyance.
01 · beginnings
02 · exploration
03 · usefulness
A practice for new possibilities
I’m Chanoch, an AI and software builder. I enjoy unfamiliar territory: learning a new domain, discovering what matters, and making a useful product from the whole tangled situation.
The best product opportunity is often hiding inside a daily annoyance.
A working first version turns assumptions into better questions.
Feedback, edge cases, and operations are how a product becomes dependable.
Project garden · growing in production
A WhatsApp-first community platform joining live information, local services, portals, and intelligent answers.
Conversational AI · WhatsApp · live dataFast warehouse intake with carrier detection, client assignment, review, and reporting.
Scanning · automation · metricsA shared environment for deals, commitments, inventory, labels, disputes, and payments.
Dashboards · roles · coordinationA mobile-first real estate workspace with voice capture, AI transcription, and one-tap communication.
Voice AI · CRM · mobile-firstA focused private dashboard for orchestrating an AI-assisted music production workflow.
AI workflow · automation · secure accessThe same builder · three different lenses
Keep scrolling. The portfolio moves through two more visual worlds: first the tactile mess of invention, then the precision of a system finding its signal.
world 02 / the maker’s table
Start with what is unfinished.
Turn thought into something testable.
Stay for production, feedback, and the edge cases.
world 03 / the signal room
Most difficult briefs arrive as noise.
Find the useful outcome inside it.
Then connect every layer around that truth.
The builder behind the systems
I’m happiest when the problem is unfamiliar, the path is not obvious, and there is something useful waiting to be discovered.
My work moves across product thinking, experience design, AI, APIs, automation, data, and deployment. I learn what the problem needs, build the connective tissue, and stay responsible for the result.
My practice
I move between product thinking, interface design, APIs, AI workflows, data, and infrastructure. The stack follows the problem. The loop stays the same: learn, make, observe, improve.
What could we grow?