Code to Content

Brandon Qin's Code to Content project automates website updates by ingesting GitHub PR data. Using LLMs, it transforms technical code changes into marketing copy and documentation. This AI-native approach ensures real-time updates for products like Email Productivity and Inbound Email Security.

NOTE: Demo visuals use either blurred real data or synthetic placeholders to protect customer privacy.

Brandon Qin

Builder

In this series

10 parts

Part 1

Code to Content - Shipping the Story

Brandon Qin’s Code to Feature Pages MVP turns merged PRs into live website content. The pipeline classifies, validates, and generates marketing copy, enabling product updates to reach customers faster without manual PMM workflows.

Part 2

Code to Content - From Pages to Systems

Brandon Qin’s follow-up demo extends Code to Content into a fully AI-generated website MVP, using shared inputs, memory, and feedback loops to autonomously maintain structure, content quality, and consistency across abnormal.ai.

Part 3

Code to Content - Two Agents, One Court

In this update to the Code to Content series, Brandon Qin shares the next iteration of Abnormal’s autonomous website vision. This update focuses on coordination: how multiple AI agents work together to turn shipped code into complete, customer-ready web experiences.

Part 4

Code to Content - Agent Trio Pipeline

Brandon Qin’s latest Code to Content iteration adds a third agent for visuals and a feedback system that learns from edits, enabling faster, higher-quality AI-generated websites.

Part 5

Code to Content - Self-Learning Intel

This iteration shows Brandon Qin’s Code to Content pipeline: three agents generate site copy, components, and branded video loops, and a Streamlit feedback app captures reviewers' edits and feeds them back into the system for faster, repeatable website iteration.

Part 6

Code to Content - Evals Feedback Layer

Brandon Qin, the builder driving the AI-native website rebuild, returned to AI Demo Hour with Code to Content: the closed-loop production system he and his web marketing stakeholders have stood up, so feedback flows into shipped code without manual handoffs. This week's demo combined a weekly executive sprint update, a new on-page feedback app, an autonomous-agent workflow, and a fresh scroll-animation media type that Brandon is rolling out across more pages.

Part 7

Code to Content - Episode 7

In his second week at Abnormal, Kevin Qi brought a working answer to a problem the new abnormal.ai site had been carrying: lots of structure, not much content. Partnering with Brandon Qin on the AI-native website, Kevin built a pipeline that pulls real customer and company content wherever it lives and enables AI agents to place it on the right page at the right time. This is episode 7 of Code to Content.

Part 8

Code to Content - Episode 8

In Episode 8, Kevin Qi, Brandon Qin, and Mickey Dang walked through the new AI-native abnormal.ai website, taking it from code to content. Three builders showed three parts of a single system: a content pipeline that populates pages, a design workflow that ensures they look right, and a localization agent that ships them in other languages.

Part 9

Code to Content - Enhanced Site Builder

In his third week at Abnormal, Kevin Qi returned to AI Demo Hour with the next iteration of the AI-native abnormal.ai site. Building on the content pipeline from earlier episodes, Kevin extended the Site Builder agent to stand up new industry solutions pages on demand. They added visual patterns that keep partner brands vibrant against Abnormal's dark site. This is episode 9 of Code to Content.

Part 10

Code to Content - Episode 10

Kevin Qi built Code to Content EP 10 around a practical website problem: product resources were starting to come together, but the experience for publishing and presenting them still felt unfinished. Kevin shows how the site becomes easier to browse and easier to maintain.

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Code to Content

In this series

Code to Content - Shipping the Story

Code to Content - From Pages to Systems

Code to Content - Two Agents, One Court

Code to Content - Agent Trio Pipeline

Code to Content - Self-Learning Intel

Code to Content - Evals Feedback Layer

Code to Content - Episode 7

Code to Content - Episode 8

Code to Content - Enhanced Site Builder

Code to Content - Episode 10

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