engblogs

Proposes Krites, an asynchronous, LLM-judged caching policy for tiered LLM architectures that expands static cache coverage by validating near-threshold prompts with an LLM and promoting verified matches into the dynamic cache, boosting static hits without increasing critical-path latency.

Shows how Agentforce replaced fine-tuned models with a constrained, multi-stage DSL to deliver deterministic, high-accuracy Flow generation at scale across 461 billion monthly executions, with validation at every stage and metadata discipline.

Combines Anthropic Claude Code with Amazon Bedrock in AWS GovCloud (US) to enable compliant, agentic AI-assisted coding workflows for regulated workloads.

Eight frontier models are analyzed for how they recover from errors in agentic coding tasks, showing that recovery, not perfection, is the differentiator and outlining actionable patterns and fixes to boost resilience in automated agents.

GPU-accelerated serving of two-tower models enables lightweight ads engagement prediction.

Guidance on configuring AgentCore Browser for AI agents with proxy routing, persistent browser profiles, and Chrome extensions to enable secure, stateful, enterprise web automation.

Analyzes error patterns and recovery dynamics across eight frontier models on the Agentic Coding benchmark to reveal how resilience, not perfection, separates success from failure.

A concise, technical guide to scaling social science research by applying scalable data collection, analysis, and workflow methods to large datasets.

GPT-5.2 derives a novel result in theoretical physics, highlighting AI-assisted approach and its implications for future research.

A practical guide to scaling access to Codex and Sora beyond rate limits, outlining high-throughput API patterns and resilient access strategies.

Technical overview of Lockdown Mode and Elevated Risk labels in ChatGPT, detailing the security controls and risk-aware behavioral changes.

Cadmus is a small-scale autoregressive program-synthesis system with an integer VM and a DSL, enabling controlled experimentation to study inductive reasoning, training-distribution control, and affordable, transparent model analysis.