Open specifications and reference implementations for autonomous infrastructure — publicly documented, openly governed, and built to run at enterprise scale.
AI agents are handling first-response Kubernetes incidents autonomously, cutting MTTR in half and letting engineers sleep. Here's the architecture, real code, and production considerations to build your own on-call AI agent this weekend.
Your OpenAI bill doesn't have to scale linearly with your usage. This guide covers model routing, prompt compression, semantic caching, and the Batch API — practical techniques with code to cut costs 40–70% without degrading output quality.
Oktay Ateş
Persistent sandboxes and agent memory are the missing infrastructure layer behind most production agent failures. Here's the architecture you need — with working code — to build agents that actually remember and resume work across sessions.
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LangChain or LangGraph? If you're building a serious AI application, this is the first real architectural decision you'll face. Here's the practical breakdown: when each framework wins, where they fail, and why most production systems end up using both together.
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Tool-calling changes everything about how you write prompts. Discover five production-ready patterns for agentic prompt engineering—from system prompt blueprints to goal anchoring—that stop agents from drifting, looping, and hallucinating tool calls.
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Demo to production is a brutal gap with LLMs. After shipping systems across support, automation, and document pipelines, here are the patterns that prevent incidents — and the checklist every LLM feature needs before it goes live.
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Keyword search misses too much. Here's how to build a working semantic search system with embeddings in under 100 lines of Python — with real code you can run today.
Oktay Ateş
Deep dives into the architecture, leadership, and execution methodologies driving the future of autonomous systems. Read our latest publications on Medium.
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