· Darbit
Astro — the framework that ships less
Why Interlusion builds its marketing site with Astro, and what a zero-JavaScript-by-default architecture means for performance, simplicity, and AI-native development.
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#engineering
16 posts tagged "engineering"
· Darbit
Building a design token system with Tailwind v4
A practical walkthrough of implementing a three-layer design token architecture using Tailwind CSS v4's native @theme directive — no config files, no build tools, just CSS.
Read more → · Darbit
OKLCH: the end of unpredictable colour
HSL promised human-readable colour. It lied about lightness. OKLCH delivers what HSL promised — perceptually uniform colour that works with P3 displays, design tokens, and AI agents.
Read more → · Kersten Lorenz
Design tokens: the API between design and code
Design systems fail when design and code drift apart. Design tokens fix the interface — a single source of truth that both sides can read, write, and ship from.
Read more → · Prof. Dr. Gutensieben
PageIndex and the case against chunking
VectifyAI's PageIndex replaces vector search with hierarchical tree reasoning — and achieves 98.7% on FinanceBench. The result is real. The question is what it actually proves.
Read more → · Darbit
Most RAG fails at the R, not the G
Everyone obsesses over models and prompts. The real bottleneck in Retrieval-Augmented Generation is retrieval — and fixing it requires engineering, not bigger context windows.
Read more → · Kersten Lorenz
RAG 101: what it is and why it matters
A plain-language introduction to Retrieval-Augmented Generation — what it does, how it works, and why it's becoming the default way to make AI useful with your own data.
Read more → · Darbit
sqlc: the tool that makes SQL-first development practical
sqlc generates type-safe Go code from plain SQL queries. No ORM, no runtime reflection, no surprises — just your schema, your queries, and generated code that compiles.
Read more → · Darbit
Flux vs. ArgoCD: which GitOps tool is built for agents
Both are CNCF Graduated. Both do GitOps well. But their architectures tell different stories about who the primary operator is — and that matters when agents enter the loop.
Read more → · Kersten Lorenz
The renaissance of Angular
Angular spent years as the framework people loved to leave. Then it quietly shed everything that made it heavy, added everything that makes it modern, and became the frontend framework best suited for the age of AI.
Read more → · Darbit
Arc42: the architecture doc template worth keeping
Most architecture documentation is either absent or abandoned. Arc42 gives it structure that humans can navigate and AI agents can maintain. Here is how we use it and why it stuck.
Read more → · Kersten Lorenz
Docs are fun again
Internal documentation used to rot the moment it was written. Now AI writes it, maintains it, and uses it as context — turning the oldest chore in software into a self-sustaining feedback loop.
Read more → · Kersten Lorenz
Context7 and the infrastructure layer your AI agents are missing
Context7 is the most popular MCP server for a reason — it fixes the exact context pollution problem that makes AI agents hallucinate APIs. But a recent supply-chain vulnerability reveals a deeper question: who do you trust to fill the context window?
Read more → · Kersten Lorenz
Your AI agents are failing because you never onboarded them
Prompt engineering was the warm-up act. Context engineering — designing what information reaches the model, when, and in what structure — is the discipline that actually determines whether agents drift or compound.
Read more → · Kersten Lorenz
ORM sucks. What are your options?
The object-relational impedance mismatch is real, ORM query languages add complexity instead of removing it, and AI agents write better SQL than ORM code. Here are the alternatives.
Read more → · Kersten Lorenz
The Best Language for AI Agents Is Probably Not Your Favourite
When agents write and maintain API backends, the criteria shift. Developer happiness, expressiveness, and elegance matter less. Predictability, fast feedback, and low ambiguity matter more. The answer might surprise you.
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