AI.
Remiam has been shipping AI in production since 2023 — starting with Finding Mastery Bot in the earliest days of the OpenAI API, when LangChain was still pre-1.0 and 'production retrieval' was barely a phrase. The studio's approach is grounded: AI earns its place where it does something humans genuinely can't (or shouldn't, repeatedly) — drafting, summarisation, retrieval over a private corpus, image labelling, content classification. The notes catalogue documents this view in detail across multiple essays, and the work itself spans Finding Mastery's editorial chatbot, the Recruit Pipeline MVP's enrichment layer, the experimental Segment Analyzer (GPT-4 Vision over scraped retail interiors), and several client features that aren't named publicly.
Finding Mastery Bot
An AI chatbot built for Finding Mastery — the Michael Gervais podcast on the psychology of high performance — trained on their entire podcast back-catalogue so their internal editorial team could ask questions, surface guest insights, and write better content. Shipped in 2023 in the earliest days of production OpenAI, and the start of an ongoing research collaboration with Finding Mastery on applied AI.
Recruit Pipeline
A B2B SaaS MVP built end-to-end for a recruitment-tech client. Recruiters log jobs, run hiring campaigns, manage companies and candidates through custom-field workflows, let AI populate routine information, and move candidates through the pipeline — interviews, comms, PDF reports — without leaving the system.
Segment Analyzer
An experimental AI product built for a US strategy client. Type a location and an industry sector — the tool scrapes that location, gathers interior photos, runs them through GPT-4 Vision to label features and surface percentage breakdowns, then lets you compare industries head-to-head on interior-design trends. Replaced weeks of in-person fieldwork with minutes of automated analysis.
- 5 Jul 2026→
When inference is almost free
The price of running a capable model keeps falling by roughly an order of magnitude a year. That does not just make AI features cheaper, it moves the line for where you can put a model in the first place.
- 3 Jul 2026→
What an agent is allowed to touch
Microsoft has put an agent sandbox into Windows itself. The interesting part is not the feature, it is that the question it answers, what is this thing allowed to touch, is the question we have been answering by hand on every AI system we ship.
- 29 Jun 2026→
A sub-1nm chip is a roadmap, not a part.
IBM has put nearly 100 billion transistors below the 1nm line. It is a real milestone and the right kind of news, but it is a roadmap for the decade, not a part you can specify this year.
- 26 Jun 2026→
NVIDIA's RTX Spark and the case for local inference
NVIDIA put 128GB of unified memory in a laptop and called it an AI PC. The interesting part is not the petaflop, it is where inference starts to run.
- 25 Jun 2026→
The AI memory crunch is now a tax on everything you ship.
Memory got expensive in a hurry. DRAM rose around 90 percent in the first quarter of 2026 as the big makers moved their lines to AI memory. If you ship anything with RAM in it, on a device or in the cloud, that is now a number you have to design around.
- 14 Oct 2025→
AI in client systems: building with it, not around it.
Clients in 2025 don't ask us 'should we use AI?'. They ask us where it goes, what it costs to run, and what it can't do safely. Here's the answer we've been giving.