Linear's CI reworked for the speed of AI coding
This is a concrete engineering account of what breaks first when AI accelerates output, useful as a checklist for your own Next.js/Supabase pipeline.
Warp's software factory orchestrates AI agents from idea to merged PR with LLM-as-judge scoring
Lloyd's detail on LLM-as-judge scoring and where human review still bottlenecks gives you a working model for trusting (or not trusting) agent output at volume.
Jev reasoning model designed for agents and tool use, not chat
Almeida's pitch for structured, non-chat model output is a genuinely different shape of tool worth testing against the classification and scoring tasks buried in your own apps.
Odds Studio,skincare identity grounded in science and restraint
Odds' restraint in a category that rewards visual noise is a direct reference point for applying Swiss minimalism to a client brief that resists it.
Open source software now treated with suspicion over its production methods
As someone visibly embedded with corporate clients while building open tools, this essay names a tension in your own position that's worth sitting with rather than dismissing.
Designers vs. The Designless what AI actually changed about design work
The framing that AI expands who attempts design without changing what design requires is a sharper way to pitch Kraftwrk's strategic value than the usual AI-threat narrative.
Pinned-value goods why some products cost the same used as new
The resale-value argument gives you a sharper vocabulary for pitching durable, well-made products to clients as an economic case, not just an aesthetic one.
Model Context Protocol still valuable for controlled, auditable agent systems
Willison's distinction between auditable, permissioned agent systems and unrestricted 'wild' agents matters directly if you're designing agent UX that clients will actually trust.
Gil Huybrecht Site of the Day: minimal portfolio crafted
A high-scoring two-color portfolio is five minutes of direct study in the restrained aesthetic you already admire in Rauno Freiberg and Emil Kowalski's work.
Linear's CI reworked for the speed of AI coding
This is a concrete engineering account of what breaks first when AI accelerates output, useful as a checklist for your own Next.js/Supabase pipeline.
Read Linear's CI post and ask where your own Next.js/Supabase pipeline would buckle first if your AI-assisted commit rate quadrupled tomorrow.