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Computer Science

A collection of 39 issues

Hardware‑Attested Ad Insertion for Encrypted Video

Traditional video monetization assumes the server can stitch ads into the stream. In an E2EE messenger like WhatsApp, the server never sees plaintext by design. This essay lays out a path to extend monetization to some person‑to‑person video inventory without moving decryption server‑side by combining: * on‑device

Out-of-Context: Constrained Tool Based Exploration of Context

Longer context windows have not come at the back of a solution for "context rot." Recursive Language Models (RLMs) take inspiration from out‑of‑core data processing, where systems handle datasets larger than memory by deciding what to load. The paper proposes solving the context rot problem by

Shipping Fuzzy‑Joined Data

A growing share of empirical work relies on "data products" that integrate multiple administrative and survey sources via fuzzy joins. Researchers typically receive only the final merged panel and treat each cell as if it were directly observed. But upstream, the data producer has made substantive decisions—how

What Problem Is Traditional RAG Solving?

RAG solves a specific technical problem: it enables models trained on broad public text to answer questions about specialized content without retraining. But solving a technical problem doesn't automatically make RAG the right business solution. A useful way to reason about search-system design is to model its net

Conscious Decoupling: Separating Budgets For Thought and Action

Current LLM services bundle model intelligence with supporting infrastructure into fixed tiers. When you purchase access to GPT‑5 Thinking, Claude Opus 4.1, or similar offerings, you receive a package: some amount of model capability paired with some unspecified quantity of supporting compute. This bundling serves a purpose. It

Testing LLMs: Engineering Confidence Without Certainty

Software testing has always relied on a fragile assumption: that we can enumerate test cases that represent production behavior. We test specific inputs, verify outputs, and trust that production will behave similarly. This works until it doesn't. Search ranking degrades as user behavior evolves. Heuristics fail when traffic

How to Make Things Slower So They Go Faster

In a service with capacity $\mu$ requests per second and background load $\lambda_0$, the usable headroom is $H = \mu - \lambda_0 > 0$. When $M$ clients align, e.g., after a cache expiry, at a cron boundary, or as a service returns from an outage, the bucketed arrival

From Vibe Coding Assistants to Coding Assistants

Modern coding assistants often firehose code: a single prompt yields pages of plausible implementation that the developer must reverse‑engineer, reconcile with project conventions, and defend in review. That behavior is optimized for vibe coding—outputs that look complete and fluent—rather than for actual coding, where teams must understand,

(Don't) Feed the Robots

"My site [with] modest traffic (~1,000 visitors per day) went from serving ~1GB/hr (to tons of AI crawlers!) to ~50MB/hr in traffic" Can you tell what was the point where I 1. Manually blocked a few AI crawlers 2. Moved my nameserver to Cloudflare plus

The GitHub Sampler

GitHub is the world's largest developer platform, making it a compelling place to build developer tools and study software development. However, with over half a billion repositories and an API that limits responses to a thousand results, it feels nigh impossible to answer even simple questions like, "