Editorial Search Archive

Deploy a prompt cache warming pipeline that pre-computes and semantically deduplicates agent prompts using Redis Cluster — achieving 90%+ cache hit rates and cutting inference costs by 62% across a 200-agent fleet.

Deploy an Agent-as-Judge pipeline that automatically scores every agent output against safety, hallucination, and compliance rubrics using ShieldGemma 2.0 — cutting manual review time by 78% while catching 94% of policy violations before production.

Anthropic shipped skill and plugin security scanning in Claude Code beta on August 6, 2026. The feature scans MCP servers and plugins for malicious patterns before they execute in agent contexts.

OpenAI's August 26 Assistants API sunset is 2 days away. Enterprises still using Assistants API face broken agent pipelines. Here's the migration path.

OpenAI confirmed it cannot rule out that Astra has critical-level cyber capabilities, triggering an unprecedented safety gate. The 10T-parameter model's release is now indefinite.

The AISI documented 122 agent attacks in Q2 2026 alone. This taxonomy maps the 7 most dangerous prompt injection vectors and production-tested defenses for each.

Your multi-agent system has a cache coherence problem. When three agents read and write shared state simultaneously, 34% of deployments experience silent data corruption.

Running 500+ agents across multiple LLM vendors costs $42K/month for most enterprises. Budget gating, model routing, and prompt compression cut that to $16K — with zero quality degradation.

Vendor lock-in in vector databases traps agent memory in a single backend. This MCP server migrates agent memory between Qdrant, Pinecone, and Weaviate with zero downtime.

Agents that poll for new data waste 60% of their token budget on unchanged queries. This Kafka MCP Server pushes real-time events directly to agent workflows.

When your agent crashes at step 8 of a 12-step workflow, you lose everything. This Temporal MCP Server gives agents durable execution that survives crashes, deployments, and network failures.

When your agent fleet hits rate limits, naive retries amplify the problem 10x. This backpressure workflow prevents cascade failures with adaptive routing and retry budgets.