Open source context systems for AI-pilled builders
Everyone wants to
build.
Almost nobody knows how to
harness the agent properly.
Your model is smarter than the results you get from it. Our context systems close that gap: one open source repo per job, with everything your agent needs to do that job well.
And the one thing it never takes
What the work has to mean, and whether it is any good. that stays yours
What we solve
Your agent is missing everything you know.
What good looks like here. Which facts are true on this project. What you settled last month. Today you type all of it from memory, a little differently every session.
The balance
Engineered to exactly what the job needs.
Pile on rules and process ceremony and even a frontier model starts turning out careful, obedient, mediocre work.
So our systems pin down only the things that should never vary: what good looks like here, which facts are true, what you already settled. The reasoning, the argument and the invention stay wide open.
The model keeps
at full range
- Which option is stronger, and why the obvious one falls short
- The argument against the thing you brought in
- Approaches nobody wrote down, to problems it has never seen
- Everything creative, uncapped
The system holds
so it is the same every time
- What good looks like on this project
- Facts, with a source you can open
- Decisions already made, so they stay made
- Checks that catch the mistake before you do
You keep
the judgement calls
- Taste. Which of these is right, and whether right is the point
- Money. What this is worth and what you will spend
- Legal exposure. What you are prepared to defend
- Meaning. What the work has to say, which no system can know
Every one of our systems is built to that line. And because none of it is tuned to one model's quirks, a better model tomorrow makes the same system produce better work.
Built to push back
An agent that tells you no.
Propose something mediocre and most agents will help you build it faster. Ours argues first, and shows you what it is arguing with.
Go with the one on the left. I like it.
Hold on. That one came with six mockups and the other two sent a single file each, so right now you are picking the better presentation. Let me finish all three to the same standard and judge them with the names off.
Say we support forty connectors.
Where does forty come from? You told this same analyst a different number last year, and nothing you gave me this cycle backs it up. Point me at a source and I will use it.
Your maker and your critic, in the trenches with you. Disagreeing with it costs one re-run.
How it works
Lightweight and local by design.
A context system runs on your machine, so your work stays private. It carries only what the job needs, and there is nothing to install.
Rules it always follows
The standards for your project, loaded before you type a word, so you stop repeating yourself every session.
Know-how, on demand
Deep method for each stage of the work, pulled in only when the task reaches it. Thorough without being heavy.
Facts it can cite
Your sources of truth, in the system. Every claim comes back with somewhere you can go and check it.
Work it produces
Real deliverables, generated by code the system owns. Change your mind, re-run, and the whole set comes back right.
Checks that hold the line
Standards go vague over months. These catch it the moment the work drifts, so quality holds a year from now.
Each system carries only the pieces its work calls for. No bloat.