The OguzHub Blog
Notes from building AI agents.
Engineering write-ups for people shipping LLM-powered software — agents, tool use, retrieval, evals, guardrails, and getting it to production.
LLM agent architecture patterns for production
Concrete patterns for building reliable agents: routing, planning, tool orchestration, and state management. Tradeoffs and failure modes you'll actually encounter.
More from the journal
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AI Agents
How to build an AI agent that actually works
The shape of a real agent system—state management, tool calling, failure handling, and the tradeoffs that matter when you ship to production.
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Enterprise
Enterprise buyers pick the AI agent that can prove it's right
In enterprise deals, the agent that can demonstrate provenance, reproducibility, and policy fit beats the one that feels smarter. Build the evidence pipeline, not just the brain.
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Go To Market
Integrations close deals, not your novel algorithm
Buyers don't pay for clever internals. They pay to make your product disappear into their stack — identity, data, and workflow. Ship the connectors and your conversion moves.
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Security
Seven ways a document can hijack your AI agent
Prompt injection isn't a jailbreak you can patch. It's a consequence of asking a model to both read untrusted text and decide what to do about it — and the fix is architectural, not a longer system prompt.