A breakdown of how provider routing, prompt caching, and request batching determine whether headline LLM price cuts actually reduce production inference costs.
A hands-on benchmark of Atria Dawn’s long-context API across 128K, 256K, and 512K windows, measuring multi-hop retrieval accuracy and p95 latency for production engineering decisions.
Prompt-level guardrails can't stop dangerous tool calls in TypeScript agent loops because risk emerges across multi-step trajectories, so developers need runtime monitoring of agent actions like the trajectory-based detection approach Snowflake researchers propose.
A practical guide for developers on the essential security, reliability, and quality tests to run before integrating an LLM into your product.
DeepSeek’s permanent 75% price cut on V4 Pro makes 1M-context AI dramatically cheaper, changing the cost calculus for solo builders who need long-context workflows, agentic tooling, and high-volume token usage.
An in-depth look at how DeepSeek V4 Pro's 1M context performs in real-world retrieval workflows, maintaining relevance, and handling edge cases.
This post explores how to identify authorization gaps in LLM agent tool use and reduce the risk of unauthorized actions.
A practical guide to building a coding agent using DeepSeek V4's new 1M token context, with real-world performance insights and implementation challenges.
Explores strategies to fortify LLM-powered agents against malicious prompt injection attacks that could manipulate tool usage.
Explore how applying zero-trust security principles to LLM pipelines mitigates risks by distrusting every input and ensuring robust, secure AI architectures.
A guide to building a prompt firewall that uses deterministic rules to filter and sanitize user inputs, enhancing security and reliability in AI interactions.
An in-depth exploration of prompt injection attacks, detailing how attackers progress from data exfiltration to achieving remote code execution on vulnerable AI systems.
Learn how to use local LLMs to identify secrets in commit messages before they are pushed to help prevent accidental credential exposure.