Pillar · 04: Teach

Your team has AI tools. They need a system.

Most teams get mediocre results from Claude because they skipped the architecture around the model. We set that up — the folder systems, context files, and workflows that make outputs reliable and specific. No custom software. No engineering team.

The problem

What most teams experience
What the system delivers
Inconsistent outputs. Same question, different answer every time.
Structured context means Claude knows your project before you type a word.
Every session starts from zero. Repeating the same background constantly.
CLAUDE.md and workspace context files load automatically. No pasting, no re-explaining.
Generic outputs that don't match the voice, format, or standards you need.
Context-specific outputs that match your conventions, audience, and process.
A $200K custom tool that a platform update rendered obsolete overnight.
A folder architecture you own, built on tools you already pay for.
The framework

Production AI systems are 60% structure, 30% prompting, 10% model calls.

Most teams invest almost entirely in the 10% — writing better prompts — and get diminishing returns. The 90% underneath is what makes outputs reliable: the folder architecture that gives Claude context, the workspace routing that loads the right information for each task, and the conventions that make behavior predictable.

We teach teams to build and maintain that 90%. Not with code. Not with custom software. With folders, markdown files, and Claude Code — tools that work today, with the subscriptions they already have.

Workshop

Half-day or full-day
team training.

Group training for teams of 4–20. Covers the core framework, folder architecture, and Claude Code in practice. Every participant leaves with a working CLAUDE.md file for their own project or role.

Investment · $2,500–$7,500

Pre-session AI audit

A short intake mapping how the team currently uses Claude, where the friction is, and what a working system looks like in your context.

The foundation framework

Why AI outputs are inconsistent, what the 60/30/10 architecture looks like in practice, and the three questions to ask about any AI tool.

Folder architecture + Claude Code

The three-layer routing system built live: CLAUDE.md, workspace context files, and task routing. Every participant sets one up for their own work during the session.

Written reference guide

A session-specific reference document each participant keeps: the framework, naming conventions, and a starting template for their own system.

Workflow Build

One workflow.
Built and documented.

We build the folder architecture and CLAUDE.md system for one specific business context: client intake, content production, operations, research, proposals, reporting. Delivered as a working system, with handoff documentation.

Investment · $1,500–$3,000

Discovery session

A focused conversation mapping the workflow: what language-heavy tasks it contains, how pieces connect, and where AI can absorb work without adding risk.

Three-layer build

CLAUDE.md, workspace context files, naming conventions, and routing logic built for your specific work — not a generic template.

Handoff walkthrough

A 30-minute recorded walkthrough of the system. How to use it, how to update it, and how to expand it as the workflow evolves.

30-day edit window

One round of refinements after you have used the system in practice. Fixes what the first version got wrong based on actual use.

Implementation Sprint

Full adoption.
Across a team or department.

For organizations that want AI adoption done properly. Workflow audit, architecture build, team training, and 30 days of refinement. Documented for internal handoff or ongoing use without a vendor dependency.

Investment · $5,000–$12,000

Workflow audit

A structured review of language-heavy work across the team or department. Separates tasks AI can absorb from tasks that require judgment, relationships, or institutional knowledge.

Architecture build

The full folder system built for the organization's context: multiple workspaces, routing tables, naming conventions, and workspace-specific context files.

Team training

Workshop-format training for the team. Everyone understands the system, knows how to use it, and knows how to update it when the work changes.

30-day refinement

Check-ins and adjustments over the first month of use. The system gets tuned to how the team actually works, not how we assumed it would.

Why this approach

No upsell to custom software. That's the point.

What you already have

Tools you own

The system runs on Claude subscriptions, VS Code, and markdown files. No new platforms, no new vendors, no new monthly costs beyond what you already pay.

What we actually do

We use this ourselves

New Ark Digital runs on the same folder architecture we teach. Client work, proposals, internal operations — all of it. We are not teaching a framework we read about.

What you walk away with

A system you can maintain

Everything is documented, transferable, and editable by anyone on your team. The goal is to not need us after the engagement ends.

AI workflow consulting · New Ark Digital

Ready to stop getting generic outputs?

Most engagements begin with a 20–30 minute conversation. We figure out where the friction is, which offering fits, and whether it makes sense to move forward. No pitch, no prep required.