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Lost in the middle is a ranking problem you own

Every founder treats lost-in-the-middle as an LLM limitation they cannot control. Wrong frame. It is a ranking problem you own, and the fix has nothing to do with waiting for a better model.

Design my context layer →

Never assemble a flat pile of chunks

The mistake is dumping a flat list of retrieved chunks into the context window and hoping the model reads the important one. Position matters, so leaving position to chance is the bug. The fix is to never build that pile in the first place.

Build a context assembly layer

We structure retrieved chunks into typed slots before they reach the LLM. The model reads a structured brief, not a heap of text. Because you decide which fact sits in which slot, you control position deliberately.

The four slots

Slot 1

The most recent relevant event

What just happened, anchored by its timestamp.

Slot 2

The strongest causal factor

The event that best explains the outcome.

Slot 3

The historical baseline

The normal pattern to compare against.

Slot 4

The anomaly or exception

The outlier the model must not miss.

Position is now a decision, not an accident

Each slot has a job, and the brief reads the same way every time. You stop praying the model finds the key fact, because you placed it yourself.

Why this is worth building

This is not hard to build. It is just not glamorous, so teams skip it and then blame the model. A structured brief lifts answer quality with no model change, and you own the outcome instead of waiting on a vendor.

What changes for your users

For your users, the difference is answers that stop missing the obvious. The key fact is no longer buried at position seven of a flat list. It sits in the slot built to hold it, every single time.

For your team, debugging gets concrete. When an answer is wrong, you inspect which slot failed instead of rereading a vague prompt. You fix a ranking rule, not a feeling.

Common questions

Does this lock me to one model?

No. Typed slots are model-agnostic. Swap models freely and the brief structure holds, which is exactly the point.

Isn't four slots too rigid?

Slots are per-domain configuration. Four is the common shape; you tune the set to the questions your users actually ask.

Map your slots in 20 minutes

We define the typed brief your LLM should read for your top questions, so position stops being an accident.

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