Built with Contextium

We’re our own first customer.

Every feature we ship — including this website — is planned, built, and reviewed inside Contextium. If it doesn’t work for us, it doesn’t ship for you.

How we actually build

There’s no separate “internal wiki”

Our code standards, architecture, brand, and decisions live in Contextium as context — not in docs nobody reads. Every feature starts as a workflow: a bundle of the agents, skills, and knowledge needed to build it, with a phase plan the whole team and its AI work through.

Landing Page
workflow · 9 of 10 phases done
Expand the comparison hub (vs CLAUDE.md, Cursor Rules, Mem0…)Done
Launch the editorial engine — /blog + anchor postsDone
Build a public trust & security page (/security)Done
Per-tool integration pages + public changelogDone
Customer proofIn progress
AgentsPlannerBuilderReviewerContextlanding-page-spec.mdlp-ref-positioning.mdlp-ref-techstack.md

Real example, live right now: this workflow shipped the comparison hub, blog, security page, and changelog you can browse on this site — 30+ pages planned as phases and built by AI sessions that were already briefed with our positioning, tech stack, and past decisions. Context, not copy-paste.


What changed for us

The same problem we built it to fix

Before

  • Every AI session started from scratch — context rebuilt by hand.
  • Onboarding took six weeks, and devs still missed our standards.
  • SOPs sat in a wiki nobody read.
  • Good context lived on one person’s laptop, never shared.

After

  • Every AI session opens already briefed on our standards and decisions.
  • New tools connect once and inherit the whole team’s context.
  • Knowledge is context the AI reads on demand — not docs to read.
  • Update once; every teammate and every tool reflects it instantly.

The primitives, in real use

Everything you get, we run ourselves

Workflows

Every feature is a workflow with its own phase plan — from DB migration to UI.

Shared context

Architecture, standards, and brand live once, read by every AI tool we use.

Agents & skills

Planner, Builder, Reviewer — reused across every workflow, customised when needed.

Versioning

Context changes are tracked and restorable, the way Git tracks code.

Event-log governance

Every change is timestamped and attributed, so an owner can manage it all.

Any AI, any tool

Delivered over MCP — the same context reaches whatever model or IDE we’re in.

Build your product the way we build ours

Give your whole team — and every AI tool it uses — one shared context.

Questions people ask

What does "built with Contextium" mean?
It means Contextium is developed inside Contextium. Every feature — including this website — is planned, built, and reviewed as a workflow in the product, using the same shared context, agents, and skills that customers use.
How does Contextium build its own product?
Each feature starts as a workflow: a bundle of the agents, skills, and knowledge needed to build it, with a phase plan the team and its AI work through. Standards and architecture live in Contextium as context, so every AI session is already briefed.
Does Contextium use its own MCP server?
Yes — context is delivered over the Model Context Protocol (MCP), so the same shared context reaches whatever AI model or IDE the team is in. We run on the exact connection methods we ship.
Why does dogfooding matter here?
Because the problem Contextium solves — context collapse across AI tools — is one we lived firsthand. Building the product inside the product means every rough edge is felt internally before it reaches a customer.