Long-reads about the engagement model, the engineering choices behind real projects, and how we think about AI in production. No content-marketing throat-clearing — every post is written by the person who shipped the work.
Most agencies sell deliverables. We sell outcomes — and write the metric into the contract on day zero. Here's how the studio measures, and what it changes about the engagement.
Most AI engagements that land at our door start with the wrong question. Should we use RAG, or fine-tune? Here's the answer that's right 90% of the time, and the rare case where fine-tuning earns its place.
Ecommerce platforms get a bad reputation in modern web circles. But the work isn't building a cart from scratch — it's choosing the right seam between the engine and the storefront. Here's how we cut it for a modest-fashion brand in Dhaka.
Most design system writing comes from teams of sixty. The patterns don't transfer. For a small team, the win isn't a documentation site — it's choosing three primitives that compose into forty screens.
Serverless KV stores, edge databases, vector-only platforms — the data layer has more options than ever. We still pick Postgres for nine out of ten projects. Here's the math.
We say no to roughly one in four discovery calls. Half of the people we turn down come back inside a year — either with a different project or a referral. Here's why disqualifying yourself early is the best agency sales tactic we know.
Most product teams chase visible AI — chat, copilots, generative everything. The features that actually move retention are invisible: better search ranking, automatic deduplication, smarter defaults. Quiet AI compounds; loud AI churns.