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Field notes on agent behavior.

Teardowns of real failures, what the traces showed, and what we learned building observability for agents in production.

Engineering

How to detect agent drift in production

Agent drift is the failure mode every AI team talks about and nobody measures. Here is how to detect it, which signals matter, and how structured memory stops it.

Apr 10, 2026 · 10 min
Engineering

How to integrate Flowlines in 5 minutes

Add behavioral observability and structured memory to any Python AI agent. Install the SDK, init before your LLM client, wrap calls in context, and retrieve memory. Works with OpenAI, Anthropic, and any agent framework.

Mar 15, 2026 · 5 min
Opinion

Flowlines vs. Mem0: why memory needs observability

Comparing Flowlines and Mem0 for AI agent memory. Mem0 is a write API. Flowlines builds memory from observed behavior. Here is when each one makes sense.

Mar 8, 2026 · 7 min
Architecture

Intent engineering requires memory

Intent detection treats every message as isolated. But real users have evolving goals. Without AI agent memory, intent resets every turn. Structured memory changes that.

Feb 27, 2026 · 6 min
Architecture

LLMs are stateless. Systems shouldn't be.

LLMs are stateless by design. Every API call starts from zero. But production AI agents need continuity and structured memory. That gap is an infrastructure problem.

Feb 23, 2026 · 7 min
Engineering

The silent failure problem in AI agents

Most AI failures don't crash. The agent returns a plausible answer and moves on. Without observability and structured memory, these silent failures repeat forever.

Feb 2, 2026 · 8 min
Opinion

Why AI agents don't learn in production

Production AI agents look intelligent in demos. But they don't get better over time. Every session starts from zero. The missing piece is AI memory infrastructure.

Jan 25, 2026 · 9 min

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