> ## Documentation Index > Fetch the complete documentation index at: https://open-index.io/llms.txt > Use this file to discover all available pages before exploring further. # Building autonomous agents > A practical guide to the failure modes of autonomous agents and the context-engineering practices that fix them. Most agent demos work. Most agents in production stall — they drift off task, need a human to steer them past the hard step, or confidently act on stale context nobody can trace. This guide is about the gap between the two, and specifically about the **context layer**, which is where most of that gap lives. This guide is vendor-neutral on the harness but grounded in a real system. Where a practice maps onto a concrete capability, we point at how [Open Index](/why-open-index) implements it — Open Index is the open-source context engine we extracted from doing this work at scale. ## The two halves of an agent An autonomous agent is a loop over two things: 1. **A harness** — the control flow, gates, retries, sub-agents, and evals that keep the loop honest. See [The harness](/guide/the-harness). 2. **A context layer** — how the agent finds the right knowledge, keeps it current, and cites it. This is where the rest of this guide focuses. Get the harness right and a wrong context layer still produces confident nonsense. Get the context layer right and a thin harness suddenly goes a lot further without a human in the loop. ## What breaks, and where it's covered The agent picks up unrelated instructions and drifts. Fix it at the data model, not with more folders. Retrieval that returns plausible-but-wrong context. Make discovery the agent's job, with navigation. Knowledge that self-contradicts as it grows. Structure updates per concept. Users can't trust what they can't trace. Attach a source to every fact. The autonomy tax. What steering is, why it happens, and how to reduce it. Same input, different output. Where to push variance out of the loop. Agents that get better with use by writing back what they learn. Soft gates, critic sub-agents, and in-session evals around the context layer. ## The one idea underneath all of it If there's a single thread through this guide, it's this: > **Don't feed your agent context. Give it structured, searchable, attributable > context and make discovery its job.** Everything else — less poisoning, less steering, more determinism, real provenance — follows from that shift. The next pages break it down failure mode by failure mode.