OpenAI Agents Handoff Design: Role Switching
Handoff criteria must be explicit so quality remains stable across specialist agents.
- Explicit handoff rules
- Role switch quality
- Unified ops standards
Agentic AI Blog
About 41 posts, organized by date, typically 1–3 per day.
Hugging Face MCP Connections: Agent Hubs
Hub-based agent ecosystems improve reuse but require clear connection policies.
- MCP connections
- Hub-based tooling
- Ecosystem reuse
Agent Builder Governance: Security, Identity, Observability
Vertex AI Agent Builder treats identity, security, and observability as governance fundamentals.
- Identity controls
- Audit-ready observability
- Security-first design
LlamaIndex Agentic Strategies: Routing, Planning, Decisions
Routing and planning strategies are the fastest way to improve agent quality without changing models.
- Routing strategy
- Query transforms
- Plan-first execution
LangMem Long-Term Memory: Learning Loops for Agents
LangMem shifts memory from short-term context to long-term operational learning.
- Hot-path memory
- Background refinement
- Long-term learning
AutoGen Bench: Agent Evaluation at Scale
AutoGen Bench shows why benchmarks and regression tests are now mandatory for agent releases.
- Benchmark baselines
- Regression suites
- Metric-driven improvement
LlamaIndex Workflows: Event-Driven Agent Design
Event-driven workflows make agent behavior more predictable and easier to recover.
- Event-driven structure
- Clear step contracts
- Observability by design
Foundry Governance: Trust, Security, Observability
Foundry demonstrates how governance, security, and observability should be built into the runtime.
- Policy + security integration
- Audit-ready telemetry
- Enterprise trust
Agent Engine Observability: Tracing, Logging, Evaluation
Observability is a design problem first. Agent Engine makes tracing and evaluation foundational.
- Structured traces
- Actionable logs
- Evaluation loops
LangGraph Human-in-the-Loop: Approval Design
Human-in-the-loop is an operational safety net—LangGraph makes it a first-class control mechanism.
- Approval checkpoints
- Stop-and-recover flows
- Risk reduction
Claude Computer Use: Desktop Automation Trends
Computer-use agents bring powerful desktop automation—but require isolation and approval safeguards.
- Screen + mouse control
- Desktop automation
- Security safeguards
Anthropic Tool Use: Schema-First Design
Tool-call quality depends on schemas. Anthropic’s guidance makes schema-first design the standard.
- Schema clarity
- Input validation
- Retry rules
LlamaIndex Agent Workflows: Collaboration Patterns
LlamaIndex provides multiple collaboration patterns—choose the one that matches your control needs.
- AgentWorkflow pattern
- Orchestrator control
- Custom planner options
Hugging Face smolagents: The Lightweight Agent Trend
smolagents highlights the lightweight agent trend—fast to prototype, but still needs production controls.
- Lightweight code agents
- ToolCallingAgent support
- Fast prototyping
CrewAI Production Crews: Roles, Flow, Observability
CrewAI’s crew model shines when roles, execution flow, and observability are defined up front.
- Role clarity
- Flow-driven execution
- Built-in observability
Vertex AI Agent Builder: Design, Scale, Governance
Vertex AI Agent Builder is a platform-first approach that ties design, scale, and governance into one system.
- Platform-first design
- ADK multi-agent support
- Governance baked in
Azure AI Foundry Agent Service: Enterprise-Grade Operations
Foundry Agent Service unifies orchestration, observability, and governance—ideal for enterprise agent operations.
- Unified ops + observability
- Tool orchestration
- Enterprise governance
AutoGen Multi-Agent Ecosystem: Collaboration by Design
AutoGen emphasizes role separation and message contracts to keep multi-agent collaboration reliable.
- Role-based collaboration
- Message contracts
- Scalable coordination
OpenAI Agents SDK Orchestration: Handoffs and Tool Flows
A practical guide to structuring OpenAI Agents SDK handoffs and tool-call flows so multi-step automation remains reliable in production.
- Clear handoff ownership
- Tool contracts and tracing
- Metrics-driven iteration
LangGraph Control Plane: State, Checkpoints, Human Review
LangGraph turns complex agent flows into controllable graphs with checkpoints and human review so long-running tasks stay reliable.
- State-graph control
- Checkpointed recovery
- Human review gates
Amazon Bedrock Agents: Guardrails for Safe Automation
A field guide to using Bedrock Agents guardrails to prevent policy violations and keep automation safe.
- Pre/post guardrails
- Policy enforcement
- Risk-contained automation
OpenAI Agents: A Practical Workflow Design Guide
Practical design principles that connect tool calls, state storage, failure recovery, and operational metrics.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Anthropic Effective Agents: Start Small, Scale Smart
A step-by-step method for productizing agents while controlling complexity and improving performance.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
LangChain Agents Playbook: Practical Tool Orchestration
Production patterns for agent loops, tool routing, fallbacks, and observability.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
AutoGen Multi-Agent Patterns: Role-Based Collaboration Design
Design state and responsibilities so multiple role agents collaborate without conflict.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
CrewAI Production Checklist: Pre-Launch Review Items
The essential stability, observability, and cost checks before launch.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
LangGraph State Machine Design: Coding Branches and Recovery
Model complex agent flows as graph state transitions to improve maintainability.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
RAG Agent Evaluation Basics: Metrics Beyond Accuracy
Quality metrics and test set design for retrieval-augmented agents.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Tool Calling Schema Design: Interfaces That Reduce Failures
Define function-call schemas to prevent miscalls and omissions.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Agent Memory Strategy: Separate Session, Task, and Long-Term Memory
Segment memory tiers to balance cost and accuracy.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Agent Observability Metrics: What to Monitor
A monitoring system focused on traces, latency, and success rates.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Guardrails and Policy Layers: Essentials for Safe Agents
Design multi-layer guardrails to prevent policy violations and risky actions.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Human-in-the-Loop Approvals: Balancing Automation and Control
Add human approvals for high-risk actions to build trust.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Prompt Routing and Planning: Execution Strategies by Request Type
Classify requests and route them to the best execution path.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Agent Cost Optimization: Call Budgets and Token Strategy
Reduce model spend while maintaining quality.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Failure Recovery Patterns: Retries, Fallbacks, Safe Stops
Recovery scenarios that prevent cascading failures.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Benchmarks and Regression Tests: Locking Release Quality
Build automated evaluation to prevent performance regressions.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Multi-Tenant Agent Architecture: Isolation and Scale
Design data isolation and operational standards for multiple customers.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Secrets and Permissions: Secure Agent Operations
Manage API keys, permissions, and audit logs safely.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
API Rate Limit Strategy: Queues, Backoff, Priority
Maintain throughput under external API constraints.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use
Agent Service Release Playbook: From Deploy to Rollback
Define deployment, monitoring, and rollback criteria to reduce operational risk.
- Key takeaways for real-world implementation
- Common failure patterns to watch
- Operational checklists you can use