Read the product.

AI coding assistants are good at writing code. They are bad at remembering yours.

cix is project-context infrastructure for AI coding assistants.

The honest version of what AI coding assistants do today: they generate plausible code that may or may not fit the project they are working in.

cix has three moving parts. None of them are clever in isolation. The combination is what makes the assistant behave better.

cix's surface is intentionally narrow. Each feature exists because, without it, the AI assistant would have to either guess or read its way to an answer. Together they replace a large chunk of the manual exploration work that happens silently in every coding session today.

The first turn of any AI-assisted coding session sets the tone for everything that follows. If the assistant doesn't understand the basics — what framework you're using, where the code lives, what the major directories are — it spends the rest of the session compensating with file reads, guesses, and clarifying questions.

The single most common failure mode of an AI coding assistant is duplicating something that already exists. A helper called formatcurrency gets reborn as formatMoney. A useUserProfile hook gets reinvented as useCurrentUser. A MemberCard component gets re-implemented as UserCard two folders away.

When an AI assistant writes a database query, a model, or a migration without seeing the actual schema, three things tend to happen:

The most expensive class of AI-assisted code change is the one where the assistant looks confident, makes a small edit, and quietly breaks something three modules away. The change compiles. The local tests pass. Production breaks two hours later because some downstream caller wasn't covered.

Most teams have an opinion about where files belong and what they should be called. Few teams have a way to enforce those opinions consistently — especially against an AI assistant that has no memory of last week's PR review.

Features describe what the system can do. Workflows describe how those features fit together when you actually work on something.

You just joined a project. Or you're returning to one after months away. Or you inherited it from a contractor whose CONTRIBUTING.md is a single sentence and a winking emoji.

Most AI-assisted coding is feature work. Add an endpoint. Add a model field. Add a UI component that lists the new thing. Add the test that covers it. This is bread-and-butter work, and it's where the difference between a context-aware assistant and a context-free one shows up most clearly.

Renames, signature changes, module moves — refactoring is the work AI assistants are most prone to doing badly without context. The change itself is small. The blast radius is what matters. And without an index, the assistant has no efficient way to see the blast radius.

Marketing copy is easy to produce. Measured behavior on real codebases is harder. This section is the harder kind.

Codebase: Laravel 12 API + Vue 3 SPA, ~300 indexed files

This is the most important page on this site. If cix worked beautifully on a couple of demo projects but fell apart on real codebases, the demo projects wouldn't matter. So we ran it on twenty-five real codebases and scored every run on a fixed rubric.

Airflow is one of the most demanding projects in the 25-repo benchmark. It is a Python monorepo with:

Every product page on this site tries to be useful. This one tries to be the most useful — because honest documentation of what doesn't work is what makes the rest of the documentation trustworthy.

A dedicated, current view of which languages and project shapes cix handles, broken into three honest tiers. If your project's primary language isn't on the Full list, read the rest of the page before deciding whether cix is worth your time.

You manage or lead an engineering team that uses AI coding assistants. You also approve the spend, or report on the budget that does. You like that productivity is up. You are uncomfortable with how inconsistent the output is — across people, across sessions, occasionally on the same task on consecutive days.

You are a technical decision-maker — staff engineer, principal, eng lead, or CTO at a smaller org — and you've been asked to assess whether cix is worth adopting on a real codebase. You want concrete evidence, a defensible evaluation method, and an honest read of the limits before committing budget or attention.