For teams

Everyone is using AI. Nobody can see anyone else’s.

For agencies, product teams and operations groups: the same knowledge, the same standards and one shared surface, instead of a dozen private conversations nobody else will ever read.

Start a project Why not just ChatGPT?
ΛLogos ΣSophia Live /drafts/round-2/
Northfield — Stage 3
Layers
Contexts
Research
Drafts
Review
Delivery
scope-note.md
fee-proposal.docxShared
Fee proposal — Northfield Stage 3Scope: mechanical & electrical commissioning to AS 5342.Excluded: Part L calculations, tenant fit-out.Basis: our commissioning handover protocol, rev 4.
risk-register.xlsx
compliance-check.pdfPublic
options-comparison.pdf

The problem isn’t adoption any more

Your team already uses AI every day. What you don’t have is any way for that use to add up: to a shared standard, a shared memory, or work a colleague can pick up.

01

The same context, over and over

Five people explain the same client, the same tone, the same constraints to five separate assistants every week. None of that explaining is ever reused.

02

Quality that swings by author

Your strongest operator gets excellent output; someone else gets something plausible and thin. The difference is the prompt, and it’s invisible until review.

03

Work nobody else can see

Good output stays buried in a transcript. When someone is away, on leave, or has left, so has everything they figured out.

What changes

Your team keeps working the way it works. What moves is where the knowledge and the standard live.

TodayWith Drafted
Context is re-explained by every person, every sessionIt’s written once, and the agent must read it before it starts
Your best operator’s method lives in their headIt’s a skill the whole team’s agents are held to
You find out what AI produced when someone shares a screenshotYou watch it appear on a surface, and comment on it in place

Why the tenth project costs less than the first

Any one project could be done in a chat window. The reason to use a surface is what the tenth project costs.

Step 1

It reads your Wiki

Before an agent may touch the work it has to search your organisation’s knowledge: your standards, your client history, the decisions you already made.

Step 2

It loads your Skills

Your procedure for this kind of work: the checklist, the evidence bar, the house style. Not loaded means the write is refused.

Step 3

It works on the Surface

The output lands as frames your team watches appear, compares side by side, and reviews before anyone signs anything.

Step 4

You correct it once

What you fix goes back into the Wiki and the Skill, so it’s already fixed for every future job and everyone who runs one.

Every project makes the next one cheaper.

Work is signed off by a professional? Read this instead

Make one person’s good session everyone’s baseline.

Free to start. Bring the AI tools your team already uses.

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