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Deconstructing Autonomous Agents in Crypto
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Agent Fundamentals

Lead · Agent Fundamentals

Why Your Agent's Output Looks Right But Isn't: The Reliability Gap Between Format and Truth

Format correctness makes people let their guard down — that's exactly what makes it most dangerous. A rambling, incoherent piece of free text, a reader spots at a glance; a neatly formatted JSON object holding the exact same hallucination, almost nobody looks twice.
Most Agent developers, when a system first launches, focus first on 'is the output format correct' — missing fields, JSON syntax errors, whether schema validation passes. This is a reasonable first step and a relatively easy problem to solve (through mechanisms like Structured Output, format error rates can be pushed close to zero). But once format reliability is solved, a more concealed,...
Agent Fundamentals
How AI Agents Use LLMs for Planning: Four Planning Strategies, Failure Modes, and Dynamic Replanning Design
Four Agent planning failure patterns: plan drift (long Context dilutes plan...
Agent Fundamentals
AI Agent Context Window Management: Why Your Agent Forgets Things, and Four Solutions
An AI Agent 'forgetting things' isn't a bug — the Context Window is full....
Agent Fundamentals
What Is the Agentic Loop: How AI Agents Keep Running — A Complete Breakdown of the Perceive, Plan, Execute, Observe Cycle
AI Agents don't just answer once — they work autonomously in a continuous...
"Format correctness makes people let their guard down — that's exactly what makes it most dangerous. A rambling, incoherent piece of free text, a reader spots at a glance; a neatly formatted JSON object holding the exact same hallucination, almost nobody looks twice."
— AI Agent Bible
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