10+ years building ML data tooling, drone operations software, and full-stack products. I combine product judgment with hands-on ownership of architecture, implementation, and release.
Lead UI Developer · Jan 2016 – May 2018
Led UI engineering for Siri’s internal ML data platform across multiple locales. Built training-data and evaluation workflows, including complex ontology navigation and labeling, with ML engineers.
Owned UI architecture, code reviews, testing, and deployment; mentored contributors as development expanded across teams.
UX Developer · Jan 2019 – Mar 2020
Delivered airspace-management software used by the Australian government, replacing a JavaScript proof of concept with a production Angular application.
Built drone telemetry and fleet-management interfaces with flight operations and flight-test teams, translating safety-critical requirements into operator tools.
AI integration · Theory of Constraints
AI can help one team produce more while the organization delivers less. More proposals, code, or content can flood a bottleneck with review requests, rework, and coordination—consuming the capacity that determines end-to-end throughput.
I apply the Theory of Constraints to find where AI can relieve that pressure and increase what actually gets delivered.
Read the full essayThe Theory of Constraints as Applied to AI IntegrationWork with me
I build AI products end to end and help teams integrate AI where it actually raises throughput. Based in Shanghai, U.S. citizen, working in English and Mandarin. Email dj@theory-a.com with a short description of the problem.
Taking an AI product idea from problem framing to a working prototype and first deployment. Full-stack ownership: architecture, implementation, evaluation, and release.
Designing and building internal AI tooling that relieves a real organizational bottleneck instead of flooding it. Informed by the Theory of Constraints.
Hands-on sessions that help teams and individuals use AI agents and LLM tools with judgment: what to delegate, how to verify, where it breaks.
Practical one-on-one AI lessons for adults and parents near Zhongshan Park, Shanghai. Taught in English or Mandarin. No programming experience needed.
Founder · Mar 2020 – Present
I founded and built Theory A to make the relationship between business performance and market expectations visible.
I own the product from customer research through implementation and deployment: custom charts, statistical analysis jobs, database migrations, and data-provider integrations.
Explore Theory A
Agent workflows & memory
Hermes is a personal AI workspace for turning research and recurring tasks into reusable agent workflows. It carries context across sessions, records decisions, and packages useful methods as skills so agents can pick up work and improve over time.
On-device computer vision
Scores Go boards from images using local computer vision and WebAssembly. Processing stays in the browser.
Embeddings & visualization
Built an interactive 3D explorer of GloVe word embeddings, turning semantic relationships between words into a visual interface.
ML education
Built a visual explainer of MNIST neural-network training, making core ML concepts easier to inspect and communicate.
Model comparison
Compares how AI models draw the same prompt, with generation times alongside the results.
Quick answers
David Jiang is a software engineer and founder of Theory A LLC. He previously worked at Apple (lead UI developer on Siri's internal machine-learning data platform) and Google (UX developer on Wing / X drone operations software). He holds an M.S. in Computer Science from Cornell University and is a co-inventor on U.S. patent 10,700,950 (filed as Wei Jiang).
AI products and research tools (Hermes agent workflows, Komi Count on-device computer vision, GloVe Galaxy, Doodle Bench), financial visualization (Theory A, options chain and Kelly criterion tools), and bilingual English/Chinese writing and philosophy projects (A Casual Dao De Jing, Meowmeow & Woofwoof, Harmonious Rites).
Yes. David is open to AI product discovery and prototyping, internal tools and workflow integration, technical mentorship, and organizational AI literacy work. Email dj@theory-a.com with a short description of the problem.
Yes. David gives in-person, practical AI lessons for adults and parents near Zhongshan Park in Shanghai, in English or Mandarin. No programming experience is needed. Details are at dj.theory-a.com/services?lang=en.
David lives between Shanghai, China and San Mateo, California, and is a U.S. citizen. He works in English and Mandarin Chinese and treats the gap between the two information ecosystems as a source of signal.
Email dj@theory-a.com. You can also find him on LinkedIn (david-jiang-74618251) and GitHub (dlwjiang). His writing lives at dj.theory-a.com/writing and his idea garden at garden.theory-a.com.
Across code and writing he tries to make hidden structure visible: in markets, in language, and in the self-deceptions organizations and people run on. Recurring concerns are self-deception, embodied emotion as suppressed intelligence, and structure over character. He works deliberately across Daoist, Confucian, Gestalt, somatic, and probabilistic frames, and has coined the frameworks Neural Annealing, Mask and Daemon, Weaponized Taste, Pattern Integrity, and Fluid Plurality.
AI product discovery and prototyping. Internal tools and workflow integration. Technical mentorship and organizational AI literacy.
dj@theory-a.com