Maincode Blog

Learning to be Maincode

Why operationalizing discovery is the hardest and most important challenge ahead

The Language of Computer Control Agents

The current focus of frontier AI research is on Computer Control Agents (CCA). The goal of this research is the automation of workflows in web browsers and operating systems on computers and mobile devices. In our previous post, we discussed that most CCAs operate by employing large language models (LLM)

Methodological Gaps in AI User Experience Research

Understanding Our Emerging Relationships with AI

Wayfinders: Operationalising UX for AI Interfaces

As generative AI gets woven into everything from writing tools to CRMs, there’s a growing problem: most products still rely on a blank textbox and a blinking cursor. That’s not UX — that’s an open loop. At Maincode, where we build applied AI systems in production, we see

Moving Beyond Static AI: The Need for Dynamic Personalisation and Where We Go Next

Why the one-size-fits-all approach to interaction modelling falls short and why we need to re-think the role of the human expert.

Product & Design

Interfaces Are Never Neutral

How we redesigned Maincode.com as an interface-level expression of our culture

Co-discovery: Humans in Automated Scientific Discovery

Why end-to-end automation of scientific discovery is probably not where the biggest opportunity lies right now.

The Polymath-Human Collider

A New Pathway for Applied AI Research

AI & Engineering

The Future of Computer Control Agents

The current frontier in the fast-paced world of AI research is Computer Control Agents or CCA. OpenAI released Operator and Anthropic its computer use capability. Large language models (LLM) that interact with websites and the apps on our phones like humans do. Vision is enabled via screen captures and actions

AI & Engineering

The fuzzy cutting edge is our playground

At Maincode, we don’t just explore AI - we ship it. That means staying ahead of the curve and turning ideas into real, shippable things. To do that, we’ve had to rethink how we approach research in a world where the edge moves at an insane speed. If