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About Lance

Backend Engineer • AI Infrastructure

Lance Rogers
I'm Lance Rogers, a backend engineer with 11+ years shipping production systems across fintech, security, blockchain, and developer tooling. Today I build AI execution infrastructure: LLM orchestration, MCP, multi-agent systems, and evaluation tooling. I bring the same craft to your team.

What I do

Production AI infrastructure. I built and ship Festival, the camp and fest CLIs that organize agent workflows. The stack is in daily use coordinating 27+ projects in one shared execution environment, with 90%+ token reduction versus unstructured agent runs. I also wrote claude-code-go, the first full-featured Go SDK for Anthropic's Claude Code, shipped within days of API availability.

Open-source Go developer tooling. Beyond Festival and Claude Code Go I've released a steady stream of small Go tools for working with AI and code: tcount (token counter for files and directories, also wired into a Neovim plugin), tree2scaffold (build project layouts from an ASCII tree), gomod-rename (refactor Go module paths cleanly), and algo-scales (open-source CLI for algorithm interview prep with AI tutoring, plus a companion Vim plugin).

Multi-agent and agentic systems. At ETHDenver 2026 I shipped the Obey Agent Economy: five autonomous agents coordinating across Hedera, 0G, and Base. Includes a Go inference agent on 0G's decentralized GPU network with ERC-7857 iNFTs, an autonomous DeFi agent on Base, settlement contracts, and a co-authored HIP-1215 ReputationDecay standard for agent reputation.

Backend at scale. I build production Go and Python backends that handle real load: OTC crypto trading platforms with KYC and compliance workflows, NFT marketplaces handling 15M+ on-chain transactions per month (at Mythical Games) with 100% finality, and custodial wallet services that let non-crypto-native users hold and trade assets without ever seeing a seed phrase.

Modernization in high-control environments. Inside Bank of America's Global Security group I rebuilt a 15-year-old codebase and shipped a CI/CD pipeline that cut deploy cycles from months to hours, reclaiming roughly six developer-months of productivity every year inside one of the most restricted enterprise environments in finance.

How I work

1. Plan first, code once. I spend real time on planning so the v1 deliverable is the right thing built well, not a fast first draft your team has to throw away. Most of the AI tooling I write enforces the same discipline on agents.

2. Systems thinking. I trace features to revenue, latency to user experience, and compliance to risk. That map guides architecture decisions long before any code gets written.

3. Knowledge transfer is part of the job. Clean commits, working docs, and team walkthroughs ship with every engagement. The goal is for your team to keep moving after I leave, not to keep me on retainer.

If your team is paying for AI tools but output is inconsistent, or you have hard backend, blockchain, or AI-infrastructure problems and want a senior engineer who has shipped them before, send a note. I bring engineers, not slide decks.

Experience & Projects

AI

AI & Machine Learning

Festival (fest.build)
Obey Agent Economy
CRE Risk Router
Brainyard
Anywr.ai
Guild Framework
Claude Code Go SDK
YouTube Summarizer
AlgoScales
Bank of America Internal ML Automation
SSI Schaefer Warehouse Optimization
Blockchain

Blockchain & Web3

Shrapnel (Neon Machine)
Investifi
Mythical Games
Dragonchain
Blocksnap
ShinySwap
Swapblocks
Charlotte Blockheads
FinTech

FinTech & Enterprise

Bank of America
PNC Bank
Global Payments
Shutterfly
Festival (fest.build)
Obey Agent Economy
CRE Risk Router
Brainyard
Anywr.ai
Guild Framework
Claude Code Go SDK
YouTube Summarizer
AlgoScales
Bank of America Internal ML Automation
SSI Schaefer Warehouse Optimization
Shrapnel (Neon Machine)
Investifi
Mythical Games
Dragonchain
Blocksnap
ShinySwap
Swapblocks
Charlotte Blockheads
Bank of America
PNC Bank
Global Payments
Shutterfly

Latest Technical Insights

4 min read

I Ran a Manager-Worker Agent Team on Real Work. A Single Session Beats It.

I ran a manager-worker agent team on 67 real tasks. A single session would have done the work better. The failure modes are structural.

AI ai-agents multi-agent-systems agent-orchestration software-engineering
4 min read

Your Agent's Memory Should Be Files in Git, Not Rows in a Vendor's Database

Agent memory should be files in git, next to the work they describe, not rows in a vendor database.

AI ai-agents context-engineering developer-tools software-engineering
5 min read

Quality Gates for Agent Work: Decisions, Not Formalities

A gate an agent waves itself through is not a gate. Quality gates for agent work have to be decisions against artifacts.

AI ai-agents quality-assurance agent-workflows software-engineering

Ready to Build Something Great?

Let's discuss how my experience can help accelerate your project.