YarnAI is how Loomery teams put senior product, design and engineering judgement in charge of AI agents, end to end, so clients get speed without losing control of what ships.
Everyone's using AI. Almost nobody's changed how they work.
YarnAI is Loomery's method for running AI agents across a whole project, not just inside a code editor, putting senior judgement in charge of what agents draft so clients get speed without losing control of what ships. Six parts make up the stack; Warp, Heddle and Bobbin, named after parts of a loom, are the core of it.
WarpEvery project's real documentation, decisions, constraints and code, pulled into one shared, version-controlled place, so agents and people work from the same source.
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HeddleWhere verified, reusable AI skills live, so a good pattern on one project shows up on the next instead of being reinvented from scratch.
BobbinPuts Loomery's hard-won knowledge and standards a question away, so the method holds even when the person running a project is new to the team.
Every project's real documentation, decisions, constraints and code, pulled into one shared, version-controlled place, so agents and people work from the same source.
Find out more →Where verified, reusable AI skills live, so a good pattern on one project shows up on the next instead of being reinvented from scratch.
Puts Loomery's hard-won knowledge and standards a question away, so the method holds even when the person running a project is new to the team.
A growing library inside Heddle covering discovery standards, delivery fundamentals and engineering patterns, for use by people and agents, ready to adapt to your organisational context.
A set of rules and steps we've codified for how people and agents work together: always name an owner, always show the reasoning, never ship what nobody reviewed.
Prompt libraries, architecture scaffolds, test templates and decision frameworks, so that we can quickly spin up agents, plus the watchouts we've learned the hard way: where agents overreach and where review can't be skipped.
A closer look at how Warp turns scattered tools into one shared, working context, kept current automatically.
See Warp in action >Warp stays current as a side-effect of working, not a doc someone has to remember to maintain.
AI accelerates the first 70% of the work. Craft and judgement own the last 30%, the part a model can't bring.
Tests, CI and static analysis come before agent freedom. We review the commits, not the summary, and bin mediocre work rather than ship it.
Standards and decisions get written down as machine-readable context, so agents and teammates act on them reliably instead of everyone re-explaining from scratch.
We validate with real evals, not gut feel, treat agents as a genuine trust and security surface, and stay cost-aware about what's earning its keep.
We use this framework across Loomery to make sure YarnAI stays embedded as capability grows, whatever stage a team is starting from. We help clients apply the same framework to their own teams.
YarnAI runs through every stage of a project, not just when the code gets written. At each stage, agents produce the first version of a thing and a Loomer owns the decision to put it live.
YarnAI changes the shape of a delivery team, not just its tools.
Get to making, fast.
Specialist judgement on call.
For the product and the org.
Smaller headcount, lower fees.
Three ways in, depending on what you need.
A product engineer and a strategic designer join your existing team as a full-time pair, directing AI agents inside your codebase and your organisation.
Loomery sets up YarnAI, the tool stack and the methodology, inside your organisation, and trains your team to run it themselves.
A full Loomery team, product counsel, multiple product pairs, and a 24/7 agent fleet, runs YarnAI end to end: strategy, design, build, and launch.
Rebuilt the channel-partner portal with AI-native delivery: a working demo in a day, live product in a week, roughly three times the pace of a traditional build.
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A university-wide agent platform on AWS with reusable templates and single sign-on, cutting the time to launch a new agent from months of development to days of configuration.
Rebuilt an AI orchestration platform for structural engineers, taking a rough-and-ready alpha to revenue-ready software in twelve weeks.
