Portfolio

Recent work led by our founder, Anthony Michaelson, before and since Atenelli — production systems across commerce, AI, and decentralized finance. Each role is noted on the case study. These are the systems behind the methods on our How we build page. Each was architected, not just assembled.

Tekel — a mobile multi-platform barter economy

Co-founder & CTO · mobile multi-platform marketplace (iOS, Android, web)

Screenshots

ChallengeBarter breaks down the moment two parties value a trade differently — someone always comes up short, and the deal dies. Solving that normally means reintroducing a central currency and the dependencies that come with it. The goal was a marketplace where unequal trades still settle fairly, without a bank in the middle.

ApproachTekel is a mobile multi-platform application — one marketplace shipped to iOS, Android, and web, plus merchant and admin surfaces. We designed the economic mechanism, not just the screens: a token that absorbs the imbalance in any trade, priced by an oracle built from the network's own trade data, with credit limits and a non-inflationary treasury funded by transaction fees rather than printing supply. On top of that protocol we built the full marketplace end to end — Stripe Marketplace for credit card processing and merchant payouts, escrowed payments, multi-party dispute resolution, milestone and time-and-materials billing, and five fulfillment models.

ResultA complete multi-sided commerce platform run by a one-person engineering org, on edge infrastructure at near-zero fixed cost — the trust mechanics (escrow, disputes, phased payments) that normally require dedicated payments and operations teams, delivered as a single coherent system across mobile and web.

Mobile multi-platform

Economic mechanism design

Edge-native

TypeScript

Stripe

Goes deep:

Architecture

·Type-safe contracts

·Error handling

Masterypath — rebuilt for the AI era

Founder · AI-native learning platform

Screenshots

ChallengeA learning platform built in 2020 — mind maps reinforced by spaced repetition — was sound in concept but carried the operational weight of a self-managed Kubernetes stack, and predated the tools that would let AI do real work inside it. The question was not how to patch it; it was whether to rebuild it.

ApproachWe made the harder call: a ground-up rewrite. The self-managed cluster was retired for a serverless edge architecture that eliminated nearly all fixed infrastructure cost and operational burden. AI was built in as a content-creation engine rather than a bolted-on chatbot — organization-scoped agents with private knowledge bases, retrieval-augmented answers that cite their sources, and pipelines that turn raw documents into structured lessons and auto-generated flashcards. The mind-mapping engine was extracted as a standalone, independently published library.

ResultA second-generation product that does more at a fraction of the running cost of the first — and a reusable visualization library with its own release lifecycle, an asset beyond the application itself. A demonstration that the right architectural decision is sometimes to discard your own prior work when the economics change.

RAG

AI agents

Serverless/edge

Reusable libraries

TypeScript

Goes deep:

Type-safe contracts

·Automated delivery

·Documented decisions

Municipal AI assistant — answers and acts

Principal Engineer (contract) · multi-tenant RAG platform for municipalities

Screenshots

ChallengeLocal governments field the same citizen questions endlessly, and the answers live scattered across their own websites and PDFs. A municipal SaaS provider needed a white-label AI assistant each city could brand and deploy against its own content — accurate enough for government use, and able to do more than just answer.

ApproachWe built the core product end to end. The retrieval layer ingests a municipality's sites and documents, chunks and embeds them, and answers questions with citations back to the source — tuned for public-sector accuracy, with a debug pipeline that traces every answer to its origin. Then we took it past Q&A: a function-calling agent that files 311-style service requests conversationally, integrating with each city's existing systems, with autonomy configurable from fully automated to human-confirmed. The platform was engineered for SaaS economics — per-tenant isolation, token budgets, and admin tooling so non-engineers can onboard new tenants.

ResultA deployed multi-tenant platform that became the client's core offering — assistants that do not just inform citizens but complete transactions for them, reducing support load while keeping every answer auditable back to its source.

RAG

Function-calling agents

Multi-tenancy

AWS

Vector search

Goes deep:

Architecture

·Error handling

·Testing

Lucra — a stablecoin that never liquidates

Co-founder · audited DeFi protocol on SolanaTry the live demo

Screenshots

ChallengeMost collateralized stablecoins protect their peg by liquidating users' collateral when markets move — punishing the very people who back the system. The goal was a fully decentralized, over-collateralized stablecoin that holds its peg without ever seizing customer collateral, in difficult market conditions, with no room for error in the math.

ApproachCo-leading a five-person team, we designed the protocol's economics from first principles — custom on-chain oracle, bond, and lending systems, with protocol-driven arbitrage doing the peg enforcement that liquidation usually does. Eighteen months of research, mathematical modeling, and rigorous testing produced the full stack: audited smart contracts, the on-chain programs, a typed Web3 SDK, a React interface, and CLI tooling.

ResultIndependently audited contracts delivered — a 300%-collateralized stablecoin with no liquidation of customer collateral, the harder and more user-aligned design, shipped despite a hostile market.

Smart contracts

Solana/Rust

Protocol design

Oracles

Web3 SDK

Goes deep:

Architecture

·Documented decisions

Our founder's earlier work — two decades of shipping at scale.

Enterprise AI & automationAt Amelia, built ML classification for client event analysis tied to $27M in new revenue and configuration management that let a handful of engineers operate 100K+ production devices for Fortune 500 clients including The Home Depot. At Cisco, led ten engineers raising autonomic incident remediation to ~80%, saving $8.8M annually.

IPncm — large-scale network configuration managementAt IPsoft, designed IPncm after a managed-services SOW required upgrading every IOS device in a customer production environment within 4 hours of any reported security vulnerability — a bar set using the Cisco vulnerability detection framework I had already built. The platform upgraded 30,000+ Cisco IOS devices inside that window with network-test rollback guarantees, peaked at 200,000+ devices under management over a nine-year run, and expanded to all major network vendors plus Linux over SSH. Small teams used it to replace 15–50 FTEs depending on the year; it anchored a $75M annual contract that ran for five years. Source on GitHub.

Mission-critical systems under pressureAs a U.S. Army Warrant Officer, deployed tactical communications across 150+ sites in Afghanistan — command and control for 75% of U.S. Army tactical operations in-country, with 3,000+ routing devices and 25,000 users under RC South. Shipped custom web-based IP management software under sustained combat conditions. Bronze Star for meritorious service.

First company, founder to exitCo-founded Solern from self-taught web development into a market leader in two categories of hospitality and gaming software — casino surveillance, encrypted communications, facial recognition, and HRIS/ATS with a job board that reached 500K members. Grew the business to 400+ corporate clients, 500K+ users, and $1.5M annual revenue, culminating in a successful IP sale.