engineer · builder · security tinkerer

I build things to understand how they work.

Software engineer exploring the edges of AI, full-stack systems, and security. I build production grade systems for the curiosity of it and to learn what the demo never shows.

— usually with a half-finished idea and too much coffee.

See what I'm building Download résumé (PDF)

building

Parley — self-hosted voice AI agent

in progress

A voice agent that answers real phone calls and holds a natural conversation built to replace a rented platform (Retell) with a voice layer that lives inside my own Spring application. Twilio handles the telephony; Parley owns everything from the words onward: interpreting the caller, running the LLM, and deciding what to say or do, with direct access to the backend. An experiment in owning the latency and turn taking that managed platforms hide.

  • Spring AI
  • Twilio
  • LLM
  • Java
  • voice

IntelligentOldMan — agentic email intelligence

in progress

An event-driven system that turns a live inbox into a searchable, classified knowledge base. It subscribes to new mail through Microsoft Graph, classifies intent with a local LLM, validates the result, and stores everything for RAG-powered agents that can reason over the whole mailbox cloud-native on Azure, provisioned with infrastructure-as-code. A study in how much judgment you can safely hand to an autonomous system.

  • Spring AI
  • RAG · pgvector
  • Azure
  • Terraform
  • Java

PokePitchShop — commerce storefront I build & run

live

A live, collector owned trading card business Pokémon, sports, and Magic: The Gathering. I build the storefront: a discovery first Next.js site with catalog browse and product pages, its inventory synced live from the eBay Trading API behind a cached read path. It's also the real product my AI experiments plug into.

  • Next.js
  • React
  • eBay API
  • SEO
  • performance

also explored

iOS, from scratch

Real-time messaging and persistence apps built from the ground up to understand the architecture behind production collaboration tools — sockets, concurrency, and local data not tutorial follow-alongs.

  • Swift
  • sockets
  • Core Data

what I'm into

Applied AI

  • LLM integration
  • RAG
  • agent frameworks
  • voice agents
  • API orchestration

Full-stack

  • Java
  • Spring Boot
  • Next.js
  • React
  • Node.js
  • Python

Infrastructure

  • Azure
  • AWS
  • Terraform
  • Docker
  • CI/CD
  • microservices

Integrations

  • Microsoft Graph
  • Twilio
  • eBay API

Security

  • penetration testing
  • DNS security
  • network hardening

writing

blog

July 2026 · Meta

Welcome to the tommarler.com blog

A markdown-first blog for technical articles — built at deploy time so Draftsmith can publish on-domain without hand-editing HTML.

All writing · Blog · Cross-posts on Medium use a canonical URL back to tommarler.com.

about

I'm a software engineer who rarely stays in one lane long enough to stop being curious about the others. My background sits at an unusual intersection iOS, distributed cloud systems, and hands on security research and that overlap is intentional.

The most interesting problems live at the edges between disciplines. Understanding the security layer makes you a better architect; understanding the product layer makes you a better engineer. Right now most of my curiosity is pointed at applied AI what it takes to make an autonomous system reliable enough to trust.

faq

What are you building right now?

I'm working on Parley, a self-hosted voice agent where I own the LLM layer inside my own Spring app; IntelligentOldMan, an experiment in turning a live inbox into something agents can reason over; and PokePitchShop, a live storefront where a lot of my AI ideas get tested against real traffic.

Why rebuild voice AI yourself instead of using a managed platform?

Managed platforms hide latency, turn-taking, and backend access. I wanted to see what it feels like to own those decisions — Twilio handles the phone call; everything from the words onward lives in my application.

What is IntelligentOldMan?

An event-driven system that classifies incoming mail with a local LLM and stores it for RAG-powered agents. The interesting part isn't the stack — it's how much judgment you can safely hand to an autonomous system.

What has you most curious about AI lately?

The gap between a convincing demo and a system you'd trust in production: agent loops that know when to stop, RAG that retrieves the right context, and voice agents where you own latency end to end. I learn by building, not by collecting buzzwords.

Where are you based?

Columbia, Missouri. My background spans iOS, distributed systems, and security research — I tend to follow problems to whatever lane they lead.