ABOUT
I'm Danny Nakhla.
Forward-deployed AI architect and systems engineer based in Philadelphia and New York. I work from commercial discovery and product design through production architecture: data, cost, integration, ownership, and the systems people operate every day.
WHO THIS IS
Architecture depth across the entire AI lifecycle.
AI writes code, but architecture and operational judgment decide whether a system survives in production. I embed directly with leadership and engineering teams as a forward-deployed architect: discovering the business problem, scoping the product workflow, writing the production code, and ensuring the internal team owns the system.
Standing up an AI system that works once in a notebook is straightforward. Building one that survives bad inputs, respects hard cost boundaries, keeps its context clean, and operates reliably inside an enterprise stack is the real work.
I focus on production agent loops, multimodal retrieval, evaluation harnesses, and human-in-the-loop control gates. The opinions on this site are my own.
HOW I WORK
The forward-deployed model
A direct, high-touch process from commercial discovery through full team ownership.
Commercial discovery & problem framing
We start with executive leadership. We map the operational bottleneck, verify the economic ROI, and align on what modern models and systems can reliably deliver before writing code.
Product design & workflow scoping
I shadow users and design the actual product workflow. We establish human-in-the-loop review gates, fallback boundaries, and interface ergonomics that match how your team actually works.
Forward-deployed production build
I write the production code directly inside your infrastructure. We build the model harnesses, data pipelines, and evaluation suites against real, messy enterprise data, meeting daily to navigate tradeoffs.
Operational handover & team ownership
I write the runbooks, establish monitoring for drift and failure modes, and train your internal engineering and operations teams so they own and run the system completely after deployment.
HOW I GOT HERE
Nearly twenty years of pre-AI engineering and applied systems.
AI writes the code, but architecture and operational judgment come from decades of building infrastructure that had to survive in the real world.
High-concurrency systems
Built distributed web infrastructure, caching layers, and high-concurrency platforms where traffic spikes broke fragile systems. Engineered Jerry Seinfeld's web properties with Sony and Crackle, including their Super Bowl broadcast launch. Scaled flash-sale infrastructure for JackThreads and Thrillist, published Foreign Affairs and cfr.org at the Council on Foreign Relations, and led international engineering teams through 27 product launches across 11 countries at Hearst Magazines (Cosmopolitan, ELLE).
Fifteen years of shipping
Shipped independent software products since 2009, starting with ClosetBank (covered by The New York Times), and later Prolo, a retailer locator SaaS used by consumer brands including Sweet'N Low. Owning systems from initial commit through production creates the practical discipline needed to keep modern AI architectures grounded.
Production models & enterprise routing
Shipped live machine-learning systems into enterprise ERP workflows by 2020, then moved to production LLMs and agent loops in 2022. Advising leadership across financial services, healthcare, and media on model routing, agent boundaries, context hygiene, evaluation harnesses, and human-in-the-loop control gates.
SIDE PROJECTS
Built for fun
Working side projects and systems I build for fun, exploring new ideas, tooling, and architectures in the open.
PennyAn AI agent that connects Telegram, calendar, mail, phone, markets, and publishing through one command per capability.
LetMeCheckThatBotA group-chat agent that reads the thread, its media, and its links, then answers in context when called.
CertArenaAn AI certification exam simulator and benchmark with Pearson VUE timing, Kokoro speech synthesis, and cited documentation.
BlockReportPhiladelphia's open property data resolved into one layer and served three ways: crawlable reports, a browser map, and a research agent that cites its records.
KTraderTrading algorithms proven on a paper account, run live where they hold up. The research never sees a price, the code owns position sizes, and every record is immutable.
ScooScoo.homesAn address list goes in, house portraits on mugs and cards come out. Each address is a paid job that parks when the imagery is uncertain.
Read the complete build records and architecture diagrams in Side Projects →
PRODUCTS BEFORE THESE
Retained build records
I have been shipping products of my own since 2009. ClosetBank, a virtual closet The New York Times wrote about, grew to thousands of daily users. Prolo, a product-finder SaaS, served consumer brands including Sweet'N Low. FrameIQ read short-form video frame by frame to find where clips held or lost attention. When a product has run its course, I retain the build record and the architectural decisions behind it.
WORK WITH ME
Let's talk about how I can help.
We can start with an executive discovery session to map the bottleneck and evaluate what is possible. If you have an operational workflow, a proprietary data asset, or an AI system that needs to survive in production, let's talk.