Цена ошибки AI-агента: выбор первой automation, опасность overall accuracy, shutdown conditions, human-in-the-loop и момент, когда действительно нужен SDK или внутренняя платформа агентов.
Чем на самом деле занимается Forward Deployed Engineer: adoption engineering, две оси диагностики (AI maturity и SDLC shape) и scaffolding перед запуском автономных агентов.
Why the Kubernetes community built the safety lock for autonomous AI agents. Deep dive into CRDs, warm pools, VM-grade isolation, and production adoption.
A comprehensive guide covering harness engineering, caching strategies, KV cache management, speculative decoding, structured outputs, evals, cost attribution, agent guardrails, observability, model routing, and fine-tuning decisions.
How to receive notifications when your AI agent finishes work, using hooks and custom TypeScript plugins.
Pre-defined commands for explain-code, code-review, onboarding-plan, commit-message, and PR description.
A practical look at balancing reuse and simplicity in Terraform. When to avoid abstraction frameworks and keep things flat.
The evolution of AI development: from spontaneous vibe coding to specification-driven processes with Memory Bank and Kiro IDE.