Running AI agents in production without an MLOps team means one bad prompt, a runaway token bill, or a silent failure can take down something customers depend on. This playbook gives technical founders and indie developers the operator-grade patterns needed to keep 1–10 production agents reliable and economical – without hiring a dedicated ops function. Seven in-depth sections cover the decisions that actually break small-scale agent deployments: which memory tier to use and when, how to enforce context budgets before costs spiral, what guardrail policies to put in place, how to track token spend at the agent level, how to orchestrate a small fleet without overengineering it, what a minimum viable observability stack looks like, and how to triage incidents when something goes wrong at 2am.
What's included
- A memory tier architecture guide that maps working memory, episodic memory, and external retrieval to specific agent use cases so you choose the right storage pattern before you build, not after you debug
- A context budget management system with concrete approaches for tracking, capping, and reclaiming context window space so agents don't silently degrade or blow up as conversations grow
- Guardrail policy blueprints covering input validation, output filtering, and policy enforcement patterns – updated for 2026 indirect injection attack surfaces – that you can adapt to your agents' specific risk profile
- A token-cost accounting system – the longest section at 2,600+ words – that shows how to attribute spend to individual agents, surface cost anomalies, and make economic decisions about model selection and call frequency
- Orchestration patterns for small fleets of 1–10 agents, including sequential, parallel, and supervisor-worker coordination approaches that add reliability without the complexity overhead built for teams ten times your size
- A minimum viable observability stack scoped to solo operators and small teams, covering what to instrument, what to skip, and how to get signal without building a monitoring platform
- Seven incident runbooks and triage playbooks that give you a structured response path for the failure modes most likely to hit production agents – cost spikes, hallucination at scale, prompt injection, API outages, agent degradation, context overflow, and multi-agent cascade failures
