YarnAI — the AI-native method for shipping better digital products, faster.
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.
Unstructured AI usage
- ✕
AI gains stay stuck with whoever's using it, they never show up in delivery speed.
- ✕
The plan, the review and the accountability still run on the old operating model.
- ✕
Nobody senior trusts the output enough to skip the old checks anyway.
- ✕
More AI tools, but not a faster or safer team.
With YarnAI
- ✓
Warp and Heddle put the same context and skills in front of the whole team, so gains compound.
- ✓
Senior product, design and engineering judgement directs every agent output, end to end.
- ✓
Guardrails and evaluations earn trust before agents get more autonomy.
- ✓
A team restructured around what agents are good at, with senior makers owning the outcome.
Loomery's proprietary method for AI and agents
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.
A queryable project brain
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.
A centralised home for skills
Where verified, reusable AI skills live, so a good pattern on one project shows up on the next instead of being reinvented from scratch.
Loomery's best-practice agent
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.
Packages of instruction & code
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.
Our AI-native processes & workflow
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.
Re-usable artefacts
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.
Warp · the project brain
A closer look at how Warp turns scattered tools into one shared, working context, kept current automatically.
Ingests from your tools
Context, decisions and what has changed since last time
Connected via MCP to the tools you already use
Kept current as a side-effect of working, not a doc someone has to maintain
A Warp session
Connect a source, like a Slack channel
Ask the project brain a question
Get an answer that cites where it came from
What you get
The principles behind YarnAI
Where YarnAI fits in the SDLC
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.
Discover
Agents create: research synthesis, competitor scans, opportunity maps.
Loomer owns: which problem is actually worth solving.
Design
Agents create: architecture options, prototype variants.
Loomer owns: the trade-offs that decide direction.
Build
Agents create: code, first-pass documentation.
Loomer owns: what actually gets merged.
Test & review
Agents create: test suites, security and quality checks.
Loomer owns: sign-off and accountability.
Ship
Agents create: release notes, deployment checks.
Loomer owns: the call to go, and the fallback.
Learn
Agents create: usage analysis, what changed.
Loomer owns: what happens next, fed back into Warp.
Our AI maturity framework
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.
Co-pilot / chat
- Give context each time
- Use for Q&A
- Discrete tasks
Copilot, Claude etc. · Gemini in Docs, Granola Chat
Repeatable tasks
- Shared, saved context
- Largely Q&A or simple actions
- Discrete tasks
Gems, Skills, Projects · prompt libraries · limited integrations, mostly out-of-the-box
Smart workflows
- Chain of tools with linked context
- Takes actions, not just answers
- Multi-step processes
Claude Co-work/Code, Gemini CLI, Codex · connectors: Slack, Jira, Figma
Autonomous agents
- Proactive workflows
- Agents discover tools you didn't specify
- Parallel agents, co-ordinating
Claude Code, Gemini CLI, Codex · OpenCode, Pi.dev, open models · inter-agent comms
From cross-functional team to product pair with agents
YarnAI changes the shape of a delivery team, not just its tools.
Close the strategy-execution gap
Get to making, fast.
Deep craft, without the big team
Specialist judgement on call.
Context that's built and kept
For the product and the org.
Controlled, predictable investment
Smaller headcount, lower fees.
Product counsel
On call
Specialist craft leaders, supporting and guiding judgement calls.
Counsel supports
Product pair
Full time
Collaborating with you to deliver value at pace.
Pair directs
Agent fleet
24/7
Multiplying impact, supported by Warp, providing an intelligent shared context layer.
Fleet multiplies
How clients engage with YarnAI
Three ways in, depending on what you need.
AI-native product pair
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.
- ✓
Directs the agents drafting inside your codebase, day to day
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Brings senior product and design judgement into your existing team
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Ships alongside your team, inside your systems and your sprints
BEST WHENYou've already got the wider team in place and want the method and the judgement, not extra headcount.
YarnAI enablement
Loomery sets up YarnAI, the tool stack and the methodology, inside your organisation, and trains your team to run it themselves.
- ✓
Stand up the tool stack, workflows and guardrails inside your organisation
- ✓
Train your team to run YarnAI's method themselves
- ✓
Hand over a repeatable way of working, not a one-off project
BEST WHENThe goal is building the capability in-house, not renting it.
Agentic pod
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.
- ✓
End-to-end ownership, strategy through launch, not just a slice of it
- ✓
Multiple product pairs plus a 24/7 agent fleet at your disposal
- ✓
Product counsel on call, guiding the judgement calls throughout
BEST WHENYou need the whole thing built at pace and don't have the team in place yet.
YarnAI helps our clients ship faster
10 days
To ship something and start learning
100 days
To a working Alpha in users’ hands
3x faster
Vorboss
We rebuilt the channel-partner portal for London's business fibre network with AI coding assistance woven through the workflow: kick-off to working demo in a single day and live product in a week.
Team 50% smaller
Bite Engineering
Rebuilding an AI orchestration platform for structural engineers, taking a rough-and-ready alpha to revenue-ready software in twelve weeks.
60 days saved
University Of Exeter
A university-wide agent platform on AWS with reusable templates and single sign-on, cutting time-to-launch for a new agent from months to days of configuration.