Product builder · iOS tinkerer · AI workflow maker

I build useful apps, agent demos, and product experiments.

I am Matthew Coelho, a product builder with 11+ years in software and AI-driven workflow systems. I have shipped enterprise AI at Walmart scale, solo-built iOS apps, and turned agent ideas into working demos people can actually try.

iOS apps AI agents Workflow automation Interactive prototypes Enterprise AI platforms
Abstract AI workflow dashboards and app surfaces

Experience

Experience behind the builds.

The side projects are hands-on, but the operating background is enterprise scale: AI workflow architecture, human-in-the-loop systems, evaluation design, and platform adoption across complex teams.

100M+

Annual interactions

Designed AI workflow architecture for Walmart's enterprise care platform, including LLM interpretation and deterministic policy execution.

8,000+

Internal operators

Built workflow infrastructure and guided tools used by operators across e-commerce, grocery, pharmacy, marketplace, and delivery.

30%

Efficiency lift

Shipped AI co-pilot capabilities that reduced operator task completion time at launch, with rework and trace data as guardrails.

8

Apps and demos shipped

Solo-built iOS apps, AI workflow tools, agent demos, and small browser games that people can open, test, and use.

Selected work

Selected work.

A mix of shipped apps, AI prototypes, and experiments. Each project is chosen because it shows a different muscle: product thinking, interface craft, automation logic, or fast learning.

App Store

Apps on the App Store.

The Team Diogo app family includes a social photo app plus two playful apps designed for children and families.

About

How I work.

I like products that can be touched quickly: an app, a prototype, a running demo, or a workflow that makes the idea concrete. The through-line is practical iteration, clear user value, and enough craft that the thing feels real.

At enterprise scale, that means deciding what the model owns, what deterministic systems must enforce, and where humans stay in command. In personal projects, it means shipping the smallest working version and learning from the real thing.

Toolkit

Current toolkit.

The projects here pull from native iOS, React, Python, Streamlit, Flask, Supabase, LangChain, LangGraph, Groq, Gemini, and static site deployment. The platform work adds eval design, trace analysis, deterministic policy execution, and human-in-the-loop workflows.

React + Vite Python + Streamlit LangGraph agents iOS apps Eval pipelines Workflow platforms

Contact

Let’s build the next one.

For product conversations, AI workflow ideas, or collaboration, LinkedIn is the cleanest place to start.