Chunky Grizzly
Data Architecture & Pipeline Lead
Designing the foundational plumbing — data warehouses, lakehouse models, and ETL pipelines — that separates organisations with genuine intelligence from those drowning in dashboards.
22 posts
Default Bias and Design Systems: Who's Setting Your UX?
Default bias shapes user behaviour more than most UX teams realise. Here's how to use it intentionally — and build design systems that scale the signal.
AI-Ready Design Systems: The UX Signal in All That Noise
AI tools flood teams with more output, not better design. Here's how AI-ready design systems help SEA brands maintain quality at scale.
Why UI Quality Wins When AI Floods Design With Quantity
AI is producing more design assets than ever. Here's why brand teams in Southeast Asia must raise the quality bar — not just the output volume.
Why Prototype Honesty Is Your UX Data's Missing Layer
Dishonest prototypes corrupt your UX data before analysis begins. Here's how to fix the signal problem at the source and design with real intelligence.
AI UX Debt Is Real — and Southeast Asia Will Pay It First
AI UX debt is accumulating faster than teams can ship. Here's what Southeast Asian design and data teams must do before the bill comes due.
Designing Human+AI Systems That Actually Work for Users
Human+AI product design is reshaping UX mandates. Here's how to build systems where AI augments decisions without eroding user trust or control.
Design Tokens and AI Context: What DESIGN.md Teaches Us
Why writing a DESIGN.md file for AI tools is actually a masterclass in design system discipline — and what SEA teams can learn from it.
Why AI Prompt Boxes Are a UX Step Backward
AI tools defaulted to the command line. Here's why that's a UX regression — and what design teams must do to fix it before users walk away.
UX Writing That Works: Words as Interface Architecture
UX writing isn't microcopy polish — it's structural design. Learn how precise language decisions drive conversion, reduce friction, and scale across SEA's multilingual markets.
UX Design's Human Problem: What AI Can't Architect
AI is reshaping UX design workflows fast. Here's why the human decisions—accessibility, trust, cultural texture—still determine whether products actually work.
Why Your Product's Tone of Voice Is the Wrong Problem
Most brands obsess over tone of voice guidelines nobody reads. Here's why having a clear point matters more — and how to build UX copy that actually converts.
AI Taste, Transparency, and the Human Touch in UX Design
As agentic AI reshapes UX, the real edge isn't automation — it's knowing when to show your work. A strategic look at taste, trust, and design that converts.
The UX Layer Your Design System Is Quietly Ignoring
Most design systems optimise for what users see. Here's why the invisible UX layer — screen reader output — is your next conversion lever.
Why Human Touch in UX Design Is a Measurable Competitive Edge
Human-centred UX design drives conversion and retention. Here's how Southeast Asian brands can measure and scale the human touch across digital products.
Why Perfect Design Is Quietly Killing Your Conversion Rate
Pixel-perfect UI isn't the goal — usable, accessible, and shipped design is. Here's what the precision paradox means for SEA growth teams.
Why Human-Touch Design Still Wins in an AI-First World
AI tools dominate design workflows, but the brands winning in SEA are those preserving deliberate imperfection. Here's what that means strategically.
Breaking Design Rules to Build Visual Languages That Actually Work
Sarah Elawad's rule-breaking maximalism reveals why the design systems brands rely on may be quietly excluding the audiences they need most.
Why Your A/B Tests Are Lying and What to Do About It
Most A/B tests produce misleading results due to four fixable statistical errors. Here's how to redesign your testing pipeline for decisions you can trust.
AI Agent Observability: The Data Pipeline You're Missing
AI agents are live in production — but can you see what they're actually doing? Here's the data architecture case for agent observability in SEA.
Contextual Retrieval: The RAG Fix Your Data Pipeline Needs
Traditional RAG systems bleed context at the chunk boundary. Here's how contextual retrieval fixes the architecture — and why it matters for SEA data teams.
Production-Ready AI Code: The Data Pipeline Gap Nobody Talks About
AI coding agents like Claude Code can ship production-ready code fast — but without solid data pipeline thinking, you're automating chaos. Here's what data teams need to know.
ML Problem Framing: Why Bad Setup Kills Good Pipelines
80% of ML projects fail before a model is trained. Here's how to fix your problem framing before you build the pipeline — not after.