Agentic AI Best Practices & Coding Guidelines

Checklist:-

1. Architecture & Design

• Define agent roles clearly (one responsibility per agent).

• Use an orchestration layer (Power Automate, LangChain, Semantic Kernel).

• Design with Human-in-the-Loop (HITL) for critical decisions.

• Separate decision logic (AI) from execution logic (API/RPA).

2. Prompt Engineering & LLM Safety

• Use standardized prompt templates (system + role + context).

• Validate inputs before sending to LLM (e.g., JSON schema).

• Enforce structured outputs (JSON/YAML) instead of free-text.

• Use a Retrieval-Augmented Generation (RAG) layer for enterprise knowledge.

3. Coding & Implementation

• Implement error handling and safe fallbacks (escalation).

• Add timeouts & retries with exponential backoff.

• Log prompts, responses, and agent decisions for audit.

• Keep prompts and configs external (YAML/JSON).

• Version control prompts & orchestration flows (Git).

4. Security & Governance

• Minimize sensitive data sent to LLM (data minimization).

• Mask PII when using external LLM APIs.

• Ensure compliance (SOC2, GDPR, HIPAA, etc.).

• Use least-privilege access for API/service accounts.

5. Testing & Evaluation

• Unit test agents with mocked LLM responses.

• Use evaluation frameworks (Promptfoo, Ragas, Azure AI evals).

• Perform adversarial testing for prompt injection attacks.

• Continuously monitor agent performance (accuracy, latency, cost).