The journal

How the context layer is built.

Benchmarks, retrieval architecture and the engineering behind indexing a codebase once and serving it to every tool that asks.

All 109 Customers 20 Engineering 89

41–50 of 89 · page 5 of 9

Mar 31, 2026 context rotAI degradationlost in the middle

Why Your AI Gets Dumber the Longer You Talk to It

You're not imagining it. Research tested 18 frontier models and every single one degrades as the conversation gets longer. Here's the science behind it.

Mar 31, 2026 NIAHRULERMRCR

Benchmarking Context Windows: NIAH, RULER, MRCR, and What They Actually Measure

Needle in a Haystack tests one thing. RULER tests another. MRCR tests yet another. Here's what each benchmark actually measures and what it misses.

Mar 31, 2026 API coststoken pricingmulti-turn cost

The Cost Curve: How Context Length Affects Your API Bill (With Formulas)

A 20-turn conversation costs quadratically more than you'd expect. Here are the exact formulas for multi-turn conversation costs across providers.

Mar 31, 2026 context windowAI basicsLLM fundamentals

What Is a Context Window? The Simple Explanation Everyone Gets Wrong

The context window is your AI's short-term memory. It's not storage — it's a fixed-size desk. Everything the AI is thinking about right now must fit on this desk.

Mar 31, 2026 training datacontext windowparametric memory

Context Window vs. Training Data: Two Completely Different Things

Training data is everything the model learned. The context window is what it's thinking about right now. Here's why the distinction matters.

Mar 31, 2026 Flash AttentionGPU optimizationSRAM

Flash Attention: How One Paper Made Long Context Possible

Flash Attention never materializes the full n×n attention matrix. Instead, it computes in tiles using fast GPU SRAM. Here's how it works and why it's 2-4× faster.

Mar 31, 2026 future of AIstate space modelsMamba

The Future: Will Context Windows Grow Forever? (Ring Attention, SSMs, Retrieval-Augmented Everything)

Three competing paradigms: grow context via hardware, replace attention with O(n) alternatives like Mamba, or build external memory systems. Which will win?

Mar 31, 2026 GPU memorymemory wallVRAM requirements

The Quadratic Memory Wall: A Precise Analysis of GPU Memory Requirements per Context Length

Total GPU memory = model weights + KV cache + activations + workspace. Here's the exact formula to compute maximum context length for any GPU configuration.

Mar 31, 2026 Infini-Attentioncompressive memoryinfinite context

Infini-Attention and Compressive Memory: Unbounded Context with Bounded Memory

Google's Infini-Attention combines standard attention with a compressive memory that persists across segments — enabling theoretically infinite context at O(1) memory.

Mar 31, 2026 information theoryShannonchannel capacity

The Information-Theoretic Limits of Context Windows

There are fundamental limits on how much information a fixed-width attention mechanism can extract from n tokens. Here's the math from Shannon's channel capacity to attention bounds.