Context: how too much of a good thing can be bad.
The intuitive thing is to give the agent everything you have. The full corpus, every related document, the complete history of decisions, all of it. The agent must surely do better with more.
That's not what happens. Beyond a certain point, more context degrades the output — the agent loses focus, attends to the wrong things, repeats itself, contradicts material it saw two pages ago. Anthropic's own engineering team calls this context rot: as the number of tokens in the context window increases, the model's ability to accurately recall information from that context decreases. Context, they argue, must be treated as a finite resource with diminishing marginal returns. Their full piece is worth reading.
Altabric assembles context the other way around. For each task, the engine selects which documents to include, at what level of detail. The selection depends on the kind of task being run. The same document might be present in full for one task, in summary for another, and absent altogether for a third.
Five levels of detail. Each task gets the level that fits.
Documents flow into agent context at one of five compression levels. The level is chosen per document, per task — based on how central that document is to the work at hand.
The ladder is applied per document, per task. A document that's central to one task may be omitted entirely from another.
What's in the context. What's not. Visible per task.
Every agent invocation comes with a context preview. You see which documents were loaded, at what compression, what was deliberately omitted, and why. No black box. No guessing what the agent was looking at when it made a call.
A real context preview from the engine. Each section names what was loaded, at what compression, and what was excluded. The token count is reported for visibility; the budget indicator alongside it is configurable and serves as a guide, not a hard limit.
What an agent actually sees.
One task. A precise selection of context.
An agent is reviewing a Story for the cutover plan workstream. The task is refinement and review, so the engine assembles the context accordingly.
The agent receives the full text of the parent Epic's Solution Design (the design it must align to) and the full text of the Story itself (the thing being reviewed). It receives the rich summary of the Theme PID one level up — enough to know the strategic frame without spending budget on it. It receives the short summary of two adjacent Stories that link in.
It does not receive the data migration architecture document, the change communications pack, or the test scripts. Those exist in the library, but they are not relevant to reviewing a cutover Story. The agent reads them when it is doing work where they matter — and only then.
Tailored context. Controlled costs. Better output.
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