
How to evaluate LLMs before production: GitHub secret scanning lessons
Start with the product decision and guardrails, then the model—offline eval as integration tests plus error analysis.
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Start with the product decision and guardrails, then the model—offline eval as integration tests plus error analysis.

vLLM on Blackwell: 96.9% prefix cache hit rate, 452:1 input/output, and why teams keep inference in-perimeter for control—not token savings.

Runway Aleph in production: shot manifests, one op per pass, preserve clauses, human QC, and prompt caching.

Why coding assistants don't shorten monolith release cycles without trackers, runtimes, data access, and MCP—SimpleOne's low-code cases.

Agent PRs outpace review capacity: review debt, what AI can catch vs what humans must own, a post-diff checklist, human gates, and a team playbook for light vs deep review in 2026.

A DevOps-oriented blueprint for training and serving models behind the perimeter—GitOps, secrets, and GPU outside the cluster.

Village Finder uses GitHub Pages, Actions, releases, and isolated branches to publish changing open data without an application server.

History of Go, simplicity philosophy, goroutines, cloud-native ecosystem, and comparison with Java, Node.js, Python, and Rust for backend engineers.

The full HTTP request journey — DNS, TLS, CDN, load balancer, Nginx, backend, Redis, queues, PostgreSQL, and back to the browser. A practical guide for developers and architects.

Across 127 modules Checkov reported ~20% more misconfigurations and scanned faster—yet Snyk wins on PR integration simplicity.

Zero-downtime on a VPS: cluster mode, reload not restart, and why you should not delete .next mid-deploy.