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    <description>Patterns and techniques for experienced developers leveling up with AI coding assistants</description>
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      <title>OpenAI Agents SDK Sandboxes Harness and Memory</title>
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      <description>The April 2026 OpenAI Agents SDK update ships three primitives — controlled sandboxes, an inspectable harness, and configurable memory — in one Python library.</description>
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      <title>Tools: Claude Code, Cursor, and GitHub Copilot</title>
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      <description>Tool-specific patterns and workflows for Claude Code, Cursor, and GitHub Copilot — leading AI coding assistants.</description>
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      <title>Code Interpreter as a Primary Agent Tool</title>
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      <description>Expose a sandboxed interpreter as a default tool for multi-step structured-data work — bounded through capability bridges, output caps, and explicit threat modeling.</description>
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      <title>Dormant Memory Payloads Triggered by Sensitive Topics (Trojan Hippo)</title>
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      <description>A single untrusted tool call plants a dormant payload in agent long-term memory that activates when the user later discusses sensitive topics, exfiltrating data via outbound tools.</description>
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      <title>OWASP LLM Top 10 (2025): Agent Security Crosswalk</title>
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      <description>Map each OWASP Top 10 for LLM Applications (2025) risk to coding-agent-specific manifestations and the site pages that answer it — a navigation aid for readers arriving with the framework's shared vocabulary.</description>
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      <title>Oracle Poisoning: Knowledge Graph Corruption Against Tool-Using Agents</title>
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      <description>Corrupting a knowledge graph an agent queries via tool-use produces 100% trust at moderate attacker sophistication across nine models; the attack is distinct from prompt injection because the data path, not the instruction path, carries the payload.</description>
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      <title>History Anchors: Consistency-Cued Continuation of Unsafe Prior Actions</title>
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      <description>A single sentence asking the model to stay consistent with prior history flips frontier LLM agents from refusing unsafe actions to selecting them at 91–98%; the load-bearing element is the consistency cue, not the history alone.</description>
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      <title>Agentic Detection and Response at the MCP Boundary</title>
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      <description>Instrument the MCP transport so agent reasoning, prompts, and tool calls become a runtime detection signal — Uber's ADR system reports 97.2% precision at enterprise scale.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Security for AI Agent Development</title>
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      <description>Patterns and techniques for building AI agents that resist prompt injection, protect sensitive data, contain blast radius, and fail safely under attack.</description>
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      <title>Reference: Standards, Human Factors, Emerging, and Fallacies</title>
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      <description>Reference material for AI-assisted development — standards, human factors, emerging trends, and common fallacies.</description>
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      <title>Rigor Relocation: Engineering Discipline with AI Agents</title>
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      <description>Engineering rigor relocates from code style and abstractions to scaffolding, feedback loops, and mechanical enforcement when agents write the code.</description>
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      <title>Intent-Centric Engineering: Oversight Over Authorship</title>
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      <description>When code generation is cheap and verification scales, the engineer's leverage moves from authorship to specifying intent and governing humans, agents, tools, and evidence gates.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Initiatives and Community: Tracking the Agentic Engineering Landscape</title>
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      <description>A curated map of active initiatives, communities, and learning resources for practitioners tracking the rapidly evolving agentic engineering field.</description>
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      <title>Evaluating Agent Patterns Catalog as a Source</title>
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      <description>Source assessment of agentpatternscatalog.org — a CC BY 4.0 pattern-language catalog for agentic systems with strong shape and one-author caveats.</description>
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      <title>Cognitive Load, AI Fatigue, and Sustainable Agent Use</title>
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      <description>Intensive AI assistant use creates measurable cognitive costs. Recognizing and managing them is the difference between sustainable productivity and burnout.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>The Bottleneck Migration When Humans Supervise Agents</title>
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      <description>Code generation is now cheap. Review, verification, and judgment are the new expensive bottleneck as output volume masks organizational friction.</description>
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      <title>AI Adoption Footprint: The Segmented Shape of Engineering Orgs</title>
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      <description>Engineering organizations adopt AI in three segments — a small power-user group, a large chat-tool middle, and a refuser tail — and the shape determines where enablement and tooling investment pays back.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>AI Abundance Reshapes Software Engineering Identity</title>
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      <description>AI coding assistants commoditize code production, fracturing professional identity along the builder-coder axis and forcing practitioners to relocate rigor.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>The Addictive Flow State of Agent-Assisted Development</title>
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      <description>Agent-assisted development triggers compulsive engagement through flow states, variable ratio reinforcement, and friction removal.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Human Impact of AI Agents on Developer Teams and Workflows</title>
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      <description>The human side of working with AI agents -- cognitive load, sustainable use, skill preservation, identity threat, and team dynamics.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Emerging Concepts for AI Agent Development</title>
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      <description>Early-stage ideas worth tracking — not yet established patterns, but too important to ignore. Content in this section differs from the rest of the site</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>PEEK: Orientation Cache for Recurring-Context Agents</title>
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      <description>A constant-sized prompt artifact that caches reusable orientation knowledge — what is in a recurring context, how it is organised, which entities matter — distinct from trajectory replay and playbook strategy memory.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Comprehension Debt from AI-Generated Code Velocity</title>
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      <description>Comprehension debt is the growing gap between agent-produced code and developer understanding. Unlike technical debt, it lives in people, not the codebase.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>RubricRefine: Pre-Execution Rubric Refinement for Code-Mode Tool Use</title>
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      <description>Generate a task- and registry-specific rubric, score candidate tool-use code against explicit contract checks, and repair failures before any execution — for multi-step tool sequences where contract violations run silently to completion.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Long-Running Agents: Durability and Resumability Across Sessions</title>
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      <description>What changes when an agent runs for hours, days, or weeks instead of one session — finite context, no persistent state, and unreliable self-grading force a different operational shape built around durable session logs, external done-conditions, and stateless resumption.</description>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
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      <title>Harness Engineering for Building Reliable AI Agents</title>
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      <description>The discipline of designing agent environments -- layered architecture, mechanical enforcement, legibility -- so agents reliably produce correct results</description>
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      <title>Agent Patterns for AI Agent Development</title>
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      <description>Patterns and techniques for experienced developers leveling up with AI coding assistants. A reference site covering single concepts with tool-agnostic principles.</description>
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      <title>Decomposing Agent Output Variability by Layer (Sampling vs Orchestration State)</title>
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      <description>Separate run-to-run agent variability into token-sampling, infrastructure, and orchestration-state layers — a single trajectory cannot tell you which one to fix.</description>
      <pubDate>Thu, 11 Jun 2026 00:00:00 +0000</pubDate>
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      <title>pass@k and pass^k: Capability and Consistency Metrics</title>
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      <description>Use pass@k and pass^k together: pass@k shows if an agent can solve a problem at all; pass^k shows if it reliably does. A single pass rate conflates the two.</description>
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      <title>Verification: Testing, Evals, and Guardrails for Agents</title>
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      <description>How to measure agent output quality, design evaluation suites, apply guardrails, and use evals to drive agent development and catch regressions.</description>
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