01Plan
Strategy
Agent Strategy & Use Case Identification
Start with business problems, classify opportunities, and prioritize them with impact, feasibility, and weighted scoring.
Explore guideAI Agent Engineering · Visual Knowledge Series
Build agents that can earn trust in production.
A connected collection of ten visual guides covering the full journey from selecting the right use case to designing, evaluating, governing, deploying, observing, and operating AI agents at scale.
10connected visual guides
6lifecycle stages
3control layers
1production operating model
The integrated model
From an idea to a governed production system.
Production agent engineering is not a single prompt, model, or framework. It is a closed operating loop. Teams first identify valuable problems, choose the right architecture, evaluate behavior and trajectories, add human and policy controls, release changes gradually, and then use production evidence to improve the next version.
Strategy→Build→Test→Control→Deploy→Operate↻
The complete collection
Ten guides. One production discipline.
Read in sequence for an end-to-end framework, or jump directly to the capability your team is designing now.
01Plan
02Plan
Lifecycle
Agentic Development Lifecycle
Use a closed-loop framework to plan, build, test, deploy, operate, and continuously improve production agents.
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03Build
Architecture
Multi-Agent Systems
Choose when specialized agents, parallel execution, or independent critique justify orchestration complexity.
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04Test
Quality
Agent Testing & Evaluation
Evaluate outcomes, trajectories, and components across task completion, accuracy, hallucination, cost, and reliability.
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05Control
Safety
Human in the Loop
Design approval gates and escalation tiers so agents act independently where safe and pause where judgment matters.
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06Control
Security
Agent Security
Defend against prompt injection, excessive permissions, unsafe tool use, and MCP-related risks with layered controls.
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07Control
Governance
Agent Governance
Create bounded autonomy, explainability, audit trails, accountability, and continuous oversight proportional to risk.
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08Deploy
Release
Agent Deployment
Move changes through shadow, canary, percentage, and full rollout stages with measurable promotion and rollback gates.
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09Operate
Visibility
Agent Observability
Trace model calls, tools, memory, orchestration, and handoffs as structured spans that can be inspected and replayed.
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10Operate
Reliability
Agent Operations
Run production agents with SLOs, incident response, on-call practices, runbooks, and cost and capacity controls.
Explore guideWhat ties the collection together
Four principles for production agents
Autonomy must be bounded
Permissions, policies, approval gates, and rollback paths define what an agent may do before it acts.
Quality includes the path
A correct answer is not enough; teams must evaluate tool choices, intermediate steps, cost, latency, and reliability.
Every action needs evidence
Structured traces, audit records, and named ownership make agent behavior inspectable and accountable.
Production closes the loop
Incidents, user outcomes, drift, and operational data should continuously improve prompts, tools, policies, and tests.