Engineering Blog

Deep dives on agentic AI

Technical articles on agent architecture, LLM engineering, security, observability, and building production-grade autonomous systems.

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Agentic AI

Architecture patterns and design decisions for autonomous AI agents

All 5

Agentic AI

Single-Agent vs Multi-Agent Architecture: Making the Right Call

When to keep it simple with one agent and when to reach for a full orchestrator-worker topology. A practical guide grounded in real production tradeoffs.

9 min read

May 1, 2026

Agentic AI

Orchestrator and Worker Patterns in Agentic Systems

A deep look at how orchestrators delegate tasks to specialized workers, handle failures, and aggregate results without creating brittle pipelines.

11 min read

May 3, 2026

Agentic AI

Event-Driven vs Request-Driven Agent Loops: A Production Perspective

The architecture decision that shapes how your agent responds to the world. Understanding when polling works and when you need reactive event streams.

8 min read

May 5, 2026

Agentic AI

Stateful vs Stateless Agents: When Each Approach Makes Sense

Stateless agents are easy to scale. Stateful agents remember context. Here is how to choose between them and what hybrid designs actually look like in practice.

10 min read

May 7, 2026

Agentic AI

Human-in-the-Loop Checkpoints and Approval Gates for Autonomous Agents

Not every agent decision should be fully autonomous. Designing approval gates that stop the right actions without turning your agent into a chatbot.

9 min read

May 10, 2026

AI Security

Securing agentic systems against prompt injection, data leakage, and supply chain attacks

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AI Security

Prompt Injection Attacks and Defenses in Agentic AI Systems

Prompt injection is the most dangerous vulnerability in agentic AI today. Learn how attackers exploit it through direct inputs, web content, and tool outputs, and build layered defenses that actually hold.

14 min read

May 15, 2026

AI Security

Secrets Management in Agent Runtimes: Keeping Credentials Out of the Context Window

Agents need API keys, tokens, and passwords to do their work. Here is how to provide those credentials without ever letting them appear in a prompt or log.

10 min read

May 12, 2026

AI Security

Sandboxing and Tool Execution Security for AI Agents

When an agent can run code, every tool call is a potential attack surface. Designing sandbox environments that contain blast radius without hobbling capability.

12 min read

May 8, 2026

AI Security

Agent Identity and Authentication: Who Can an Agent Act As?

As agents take actions on behalf of users, identity becomes a first-class concern. OAuth scopes, service accounts, and least-privilege auth patterns for agentic systems.

11 min read

May 6, 2026

AI Security

Least-Privilege Principles for Agent Tool Access

Giving your agent exactly the permissions it needs and nothing more. Why over-permissioned agents are a liability and how to scope tool access tightly without breaking workflows.

8 min read

May 4, 2026

Multi-Agent Systems

Communication protocols, trust hierarchies, and coordination between agents

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Multi-Agent Systems

Agent-to-Agent Protocols: A2A and MCP Explained for Production Teams

The two emerging standards for agent communication, how they differ, when to use each, and what their limitations mean for your architecture today.

13 min read

May 14, 2026

Multi-Agent Systems

Trust Hierarchies Between Agents: A Framework for Safe Delegation

Not every agent should trust every other agent equally. Designing trust tiers that reflect real-world authorization boundaries in multi-agent pipelines.

10 min read

May 11, 2026

Multi-Agent Systems

Message Schema Design and Versioning in Multi-Agent Systems

How to design agent message contracts that evolve without breaking running workflows, including versioning strategies and backward compatibility patterns.

9 min read

May 9, 2026

Multi-Agent Systems

Avoiding Cascading Failures in Agent Chains

One failing agent should not bring down your entire pipeline. Bulkhead patterns, timeout hierarchies, and circuit breakers designed for chained agent systems.

11 min read

May 7, 2026

Multi-Agent Systems

Shared Context vs Isolated Context in Multi-Agent Architectures

The tradeoff between agents that share a global context and agents that operate in isolation. When coordination overhead outweighs the benefits of shared knowledge.

8 min read

May 5, 2026

LLM Engineering

Model routing, prompt versioning, fine-tuning, and cost optimization

All 5

LLM Engineering

Model Routing in Production: When to Use GPT-4o, Claude Sonnet, or Haiku

Intelligence costs money and latency. A practical routing framework that sends each task to the right model based on complexity, cost, and latency requirements.

12 min read

May 13, 2026

LLM Engineering

Fallback Strategies and Model Degradation in Agentic Pipelines

When your primary model is down, rate-limited, or too slow, you need a plan. Designing fallback chains that degrade gracefully without silently producing bad output.

10 min read

May 10, 2026

LLM Engineering

Fine-Tuning vs Prompting for Agent Personas: What Actually Works

Both approaches can give an agent a consistent personality and domain expertise. Here is the honest comparison of cost, quality, and maintainability for each.

11 min read

May 8, 2026

LLM Engineering

System Prompt Versioning and Management at Scale

System prompts are code. They should be versioned, tested, reviewed, and deployed with the same rigor as the application code around them.

9 min read

May 6, 2026

LLM Engineering

Cost vs Capability: Making Smart LLM Tradeoff Decisions in Production

A framework for deciding when a cheaper model is good enough, when you need the frontier, and how to instrument your system so you can measure the difference.

10 min read

May 4, 2026

AI Observability

Distributed tracing, logging, metrics, and hallucination detection for agent systems

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AI Observability

Distributed Tracing Across Agent Chains: A Practical Implementation Guide

When an agent call spans five services, four models, and three external APIs, you need trace context that follows the work all the way through. Here is how to instrument it.

13 min read

May 14, 2026

AI Observability

Logging Tool Calls, Inputs, and Outputs for Debuggable Agents

The difference between agents that are debuggable and ones that are black boxes is almost entirely in how you log. What to capture, how to structure it, and where to send it.

9 min read

May 11, 2026

AI Observability

Agent Metrics That Actually Matter: Latency, Cost, and Success Rate

What metrics to track for each agent in your system, how to define success in a way that is measurable, and the dashboards worth building from day one.

10 min read

May 9, 2026

AI Observability

Visualizing Agent Execution Graphs for Faster Debugging

A trace is a timeline. An execution graph shows you the shape of the work. How to build and display agent execution graphs that reveal what a trace alone cannot.

8 min read

May 7, 2026

AI Observability

Alerting on Agent Drift and Hallucination Patterns in Production

Agents that worked perfectly in staging can start behaving strangely weeks after deployment. How to detect semantic drift and hallucination before users do.

11 min read

May 5, 2026

Token Management

Context window budgeting, compression, RAG tradeoffs, and multi-turn optimization

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Token Management

Context Window Budgeting Strategies for Long-Running Agents

Context windows fill up faster than you expect in agentic workflows. A systematic approach to allocating tokens across system prompts, memory, tools, and user messages.

11 min read

May 13, 2026

Token Management

Prompt Compression and Summarization Techniques That Preserve Meaning

Compressing long contexts without losing the information that matters. Techniques from extractive summarization to hierarchical compression that hold up under adversarial conditions.

10 min read

May 10, 2026

Token Management

Dynamic Context Pruning During Long Agentic Tasks

Not everything in a growing context window is still relevant. How to identify and remove stale context at runtime without breaking the agent's ability to complete its task.

9 min read

May 8, 2026

Token Management

RAG vs Full-Context: Choosing the Right Knowledge Architecture

Retrieval-augmented generation and full-context approaches have fundamentally different performance profiles. Here is the data you need to choose between them for your use case.

12 min read

May 6, 2026

Token Management

Managing Token Limits in Multi-Turn Agentic Loops

Multi-turn agents accumulate context with every round trip. Strategies for sliding windows, checkpoint summarization, and conversation compaction that keep agents productive over long sessions.

10 min read

May 4, 2026

Testing & Evaluation

Unit testing, end-to-end evals, red-teaming, and regression testing for agents

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Testing & Evaluation

Unit Testing Tool Calls and Agent Logic Without Mocking Everything

Effective agent tests are harder to write than application tests because nondeterminism is a first-class feature. Strategies for making tests reliable without over-mocking the model.

11 min read

May 12, 2026

Testing & Evaluation

End-to-End Evaluation Frameworks for AI Agents: AgentBench, GAIA, and Beyond

What the leading agent benchmarks actually measure, their blind spots, and how to design custom eval suites that reflect what your agent is expected to do in production.

13 min read

May 10, 2026

Testing & Evaluation

Red-Teaming AI Agents Before Production: A Systematic Approach

Adversarial testing for agents is not optional. How to structure red-team exercises that surface real vulnerabilities before they become incidents in production.

12 min read

May 8, 2026

Testing & Evaluation

Regression Testing for Prompt Changes: Catching Silent Breakages

Changing one line of your system prompt can break a behavior that was working fine for months. How to build regression test suites that catch semantic regressions before they reach users.

9 min read

May 6, 2026

Testing & Evaluation

Building Custom Evaluation Pipelines for Your Specific Agent

Generic benchmarks will not tell you if your customer support agent is getting better. How to define task-specific metrics and automate evaluation at scale.

10 min read

May 4, 2026

Reliability & Resilience

Retry logic, circuit breakers, graceful degradation, and failure recovery

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Reliability & Resilience

Retry, Timeout, and Circuit Breaker Patterns for Agentic Pipelines

LLM calls fail. External APIs go down. Network requests time out. The reliability primitives every agent needs and how to configure them without creating runaway retry storms.

12 min read

May 11, 2026

Reliability & Resilience

Handling Partial Failures in Agent Pipelines Without Losing Work

When step three of a seven-step pipeline fails, should you restart from scratch or recover from the checkpoint? Designing agents that handle partial failure gracefully.

10 min read

May 9, 2026

Reliability & Resilience

Graceful Degradation Strategies for Production AI Agents

When the frontier model is down, your agent should not simply error out. Designing degradation paths that reduce capability gracefully rather than failing completely.

9 min read

May 7, 2026

Reliability & Resilience

Idempotency in Agent-Triggered Actions: Preventing Duplicate Operations

When a retry sends an email twice or charges a card twice, idempotency is your safety net. How to design agent tool calls that are safe to retry without side effects.

8 min read

May 5, 2026

Reliability & Resilience

Agent Restart and Failure Recovery Logic That Actually Works

Crash recovery for agents is fundamentally different from crash recovery for stateless services. Designing restart logic that restores meaningful state without replaying harmful side effects.

11 min read

May 3, 2026

Planning & Reasoning

ReAct, Chain-of-Thought, Tree-of-Thought, and task decomposition strategies

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Planning & Reasoning

ReAct: How Reasoning and Acting Together Makes Agents Dramatically More Reliable

The ReAct pattern interleaves reasoning traces with action execution. Why this simple idea produces agents that are more reliable, debuggable, and correctable than pure action-taking models.

13 min read

May 15, 2026

Planning & Reasoning

Chain-of-Thought Prompting for Complex Agent Tasks

Chain-of-thought is not just a prompting trick. When applied correctly, it is an architectural decision that changes how agents decompose, execute, and verify complex multi-step work.

11 min read

May 12, 2026

Planning & Reasoning

Tree-of-Thought: Exploring Multiple Reasoning Paths for Hard Problems

When the best answer requires backtracking and exploring alternatives, Tree-of-Thought gives agents a framework for deliberate, non-linear reasoning over complex tasks.

10 min read

May 10, 2026

Planning & Reasoning

Task Decomposition Strategies for Agentic Workflows

Complex tasks that fail as a whole often succeed when broken into the right sub-tasks. Heuristics for decomposing tasks in a way that improves success rate without compounding errors.

9 min read

May 8, 2026

Planning & Reasoning

Replanning When Agent Execution Fails: Dynamic Plan Revision

The plan that looked perfect before execution rarely survives contact with the real world. How to design agents that detect plan failures early and replan without restarting from scratch.

10 min read

May 6, 2026

Performance & Scalability

Parallelism, caching, horizontal scaling, and latency optimization

All 5

Performance & Scalability

Parallelizing Agent Workloads Safely: Concurrency Without Chaos

Running agent subtasks in parallel dramatically reduces latency. The coordination patterns, shared-state risks, and resource limits you need to understand before you parallelize.

12 min read

May 14, 2026

Performance & Scalability

Caching LLM Responses Safely: Speed Without Stale Answers

Caching makes agents dramatically faster and cheaper. It also introduces subtle bugs when cached answers are no longer correct. The techniques that give you speed without sacrificing correctness.

10 min read

May 12, 2026

Performance & Scalability

Horizontal Scaling of Agent Fleets: Infrastructure and Architecture

Scaling agents is not the same as scaling APIs. Stateful agents, long-running tasks, and model rate limits all create unique infrastructure challenges at scale.

11 min read

May 10, 2026

Performance & Scalability

Latency Optimization in Multi-Step Agent Pipelines

Every step in an agent pipeline adds latency. Profiling tools, parallel execution, streaming responses, and speculative execution techniques that cut total pipeline time.

10 min read

May 8, 2026

Performance & Scalability

Cost Profiling and Optimization for Production Agent Systems

Agent systems can generate surprisingly large LLM bills. How to attribute costs per agent, identify expensive edge cases, and optimize spend without degrading quality.

9 min read

May 6, 2026

Memory & State

Vector store design, session persistence, and multi-user memory architecture

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Memory & State

Vector Store Design for Agent Memory: Beyond the Basic Similarity Search

Most agent memory implementations stop at similarity search. The vector store design decisions that determine whether your agent's memory actually helps it do better work.

13 min read

May 13, 2026

Memory & State

When to Summarize vs Retain Raw History in Agent Memory

Summaries save tokens. Raw history preserves detail. The signals that tell you which approach to use and how to design hybrid memory systems that apply both where appropriate.

10 min read

May 11, 2026

Memory & State

Persistent State Across Agent Sessions: Patterns and Pitfalls

Agents that remember previous conversations are more useful. The storage patterns, serialization formats, and recovery strategies that make persistence reliable rather than fragile.

11 min read

May 9, 2026

Memory & State

Short-Term, Long-Term, and Episodic Memory Architecture for AI Agents

Humans use different memory systems for different timescales. Designing analogous memory architectures for agents that behave well whether a conversation is new or months old.

12 min read

May 7, 2026

Memory & State

Designing Agent Memory for Multi-User Systems Without Cross-Contamination

In a multi-tenant agent platform, one user's memories must never influence another's results. Memory isolation strategies, namespace designs, and audit patterns for shared agent infrastructure.

9 min read

May 5, 2026

Ethics & Compliance

Auditability, GDPR, HIPAA, bias mitigation, and responsible AI deployment

All 5

Ethics & Compliance

Auditability and Explainability of Agent Decisions in Regulated Industries

When an autonomous agent makes a consequential decision, someone needs to be able to explain why. Designing agent systems that produce auditable decision trails without sacrificing performance.

12 min read

May 15, 2026

Ethics & Compliance

GDPR and HIPAA Compliance with Autonomous AI Agents

Autonomous agents that process personal or health data must meet the same regulatory standards as any other software system. The specific requirements and how to design agents that meet them.

13 min read

May 13, 2026

Ethics & Compliance

Bias and Fairness in Automated Agent Decision-Making

LLMs inherit biases from training data. When agents make decisions that affect people, those biases produce real-world harm. Detection frameworks and mitigation strategies for production systems.

11 min read

May 11, 2026

Ethics & Compliance

Responsible AI Deployment Practices for Agentic Systems

Shipping agents into production is easy. Doing it responsibly requires deliberate process. A checklist-driven framework for responsible deployment from staging to full production traffic.

10 min read

May 9, 2026

Ethics & Compliance

Building Transparent Agent Systems That Earn User Trust

Transparency is not just a compliance checkbox. Users who understand what an agent is doing are more likely to trust it, correct it, and use it effectively. Design patterns for agent transparency.

9 min read

May 7, 2026