1 min read
Agent Design Notes: designing fallback behavior before launch
I worked on smoothing the handoff between data engineering and AI teams—standardizing feature contracts, embedding validation, and adding lightweight…
Agents
37 articles
1 min read
Where Agent Systems Break: state handling patterns that reduce agent confusion
I turned implicit processes into explicit operating rules—defining owners, acceptance tests, and lightweight runbooks so teams can move confidently and…
1 min read
Where Agent Systems Break: tool access policies that improve reliability
I worked on smoothing the handoff between data engineering and AI teams—standardizing feature contracts, embedding validation, and adding lightweight…
1 min read
Building Useful AI Agents: tool access policies that improve reliability
I focused on making delivery decisions auditable and repeatable—documenting intent, success criteria, and rollback paths to reduce tribal knowledge.
1 min read
Agent Workflows in Practice: state handling patterns that reduce agent confusion
I tightened system boundaries so quality checks trigger earlier, catching regressions before downstream systems consume bad data.
1 min read
Building Useful AI Agents: tool access policies that improve reliability
I worked on smoothing the handoff between data engineering and AI teams—standardizing feature contracts, embedding validation, and adding lightweight…
6 min read
The Invisible Tax: Why the Future of AI Is About Transitions, Not Tasks
The highest-cost gap in knowledge work is the transition between commitments. Transition intelligence is where proactive AI can create compounding value.
3 min read
The Microsoft Agent Framework: What You Need to Know
It's Microsoft's opinionated framework for building production AI agents. Not just chatbots. Agents that reason, plan, use tools, and collaborate with other…
3 min read
The Microsoft Agent Framework: What You Need to Know
It's Microsoft's opinionated framework for building production AI agents. Not just chatbots. Agents that reason, plan, use tools, and collaborate with other…
2 min read
AI Agents vs Workflows: Choosing the Right Pattern
Workflow: Predefined steps. AI handles specific tasks within a fixed pipeline. Deterministic flow.
2 min read
Semantic Kernel: Building Production AI Agents
After building agents with LangChain, AutoGen, and custom solutions, I finally gave Semantic Kernel a proper try. Here's what I learned building production…
3 min read
AI Agents: Reality vs Hype in 2026
The tech itself isn't revolutionary—it's the orchestration that's interesting. Code review automation. Agents can catch obvious issues, suggest…
1 min read
2025 AI Year in Review: The Year Agents Became Real
The most significant shift this year was the maturation of autonomous AI agents. What started as experimental frameworks evolved into production-ready…
1 min read
Agentic Workflows: Designing Autonomous AI Systems
Safe agentic workflows balance autonomy with appropriate controls.
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Tool Orchestration: Managing Complex Tool Interactions
Robust tool orchestration enables complex, reliable AI workflows.
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Agent Memory Systems: Building Persistent AI Memory
Sophisticated memory systems enable agents to learn and improve over time.
1 min read
Advanced Agent Patterns: Complex Multi-Agent Systems
Choose the right execution pattern based on task complexity and agent capabilities.
1 min read
Azure AI Foundry Agents: Building Production AI Agents
Azure AI Foundry simplifies the path from agent prototype to production deployment.
1 min read
AI Orchestration Frameworks: Building Complex AI Workflows
Choose orchestration frameworks based on workflow complexity and team expertise.
1 min read
Agent Safety Patterns: Building Trustworthy AI Systems
Safety in AI agents is not optional - it's foundational. Build safety in from the start, and your agents will be both powerful and trustworthy.
1 min read
Memory Consolidation for AI Agents: From Short-Term to Long-Term
1. Set appropriate thresholds : Not everything needs to be remembered 2. Consolidate regularly : Don't let short term memory overflow 3. Abstract…
1 min read
Procedural Memory for AI Agents: Learning How To Do Things
Procedural memory captures: Action sequences : Steps to accomplish tasks Conditions : When procedures apply Parameters : Variables in the process Success…
1 min read
Semantic Memory for AI Agents: Knowledge Representation
Aspect Semantic Memory Episodic Memory Content Facts, concepts, relationships Events, experiences Context Context free Time and place specific Example…
1 min read
Episodic Memory for AI Agents: Learning from Experiences
Unlike semantic memory (facts) or procedural memory (how to), episodic memory captures: Events : What happened Context : When and where Outcomes : Results…
1 min read
Long-Term Agent Memory: Persistent Knowledge Storage
1. Categorize memories : Different types need different handling 2. Extract automatically : Don't rely on explicit save commands 3. Maintain regularly :…
2 min read
Short-Term Agent Memory: Context Window Management
Sounds like a lot, but it fills up quickly with conversation history, system prompts, tool outputs, and retrieved documents.
1 min read
Agent Memory Patterns: Beyond Simple Context
Periodically consolidate memories for efficiency: 1. Layer your memory : Different types for different purposes 2. Manage capacity : Always have eviction…
1 min read
Human-in-the-Loop AI Agents: Building Trust Through Oversight
Irreversible actions : Deletions, payments, deployments High cost operations : Expensive API calls, resource provisioning Sensitive data : PII handling,…
1 min read
Cycles in Agent Graphs: Iterative Refinement Patterns
Real tasks often require iteration: Refinement : Improve output quality through multiple passes Retry : Handle failures with backoff strategies Search :…
1 min read
Conditional Edges in LangGraph: Dynamic Agent Flows
Route based on multiple state attributes: Sometimes you don't know all routes ahead of time: Multiple decision points in sequence: Route with randomization…
1 min read
Stateful AI Agents: Managing Context and Memory
All require state management beyond simple request-response.
1 min read
Graph-Based AI Agents: Design Patterns and Architecture
Think of your agent as a state machine: Nodes : Processing steps (functions that transform state) Edges : Transitions between steps State : Accumulated…
1 min read
LangGraph Introduction: Building Stateful AI Agents
LangGraph provides these capabilities through a graph-based execution model.
1 min read
Building AI Agents: From Chatbots to Autonomous Systems
AI agents represent the next evolution of AI systems. By combining planning, tool use, and memory, they can autonomously accomplish complex goals while…
1 min read
Self-Hosted Agents in Azure DevOps
Self-hosted agents provide flexibility for specialized build requirements and secure access to internal resources.
1 min read
Azure DevOps Agent Pools
Agent pools provide flexible compute resources for diverse build requirements.
1 min read
Azure Monitor Agent: The Future of Azure Monitoring
Azure Monitor Agent provides a unified, secure, and flexible foundation for all monitoring needs.