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The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.
README.md
Agentic Engineering Handbook
The definitive OpenAI, Anthropic, MCP, Harness, Evals, and Production Agent Systems learning roadmap.
If this repository helps you, consider giving it a ⭐
Why This Repository?
The AI industry has entered the Agentic Era. Building production-grade AI systems now requires mastering agents, tool use, MCP, memory, long-running workflows, coding agents, agent harnesses, evals, and safety — but the knowledge is scattered across OpenAI blogs, Anthropic engineering posts, SDK docs, cookbooks, and research papers.
This repository consolidates 114 official resources into one structured learning roadmap.
The goal: Become a world-class Agentic Engineer.
Learning Roadmap
Phase 1 — Agent Foundations
Build shared vocabulary for workflow vs agent, tool loop, handoff, guardrails.
Read First
| # | Title | Vendor |
|---|---|---|
| 1 | Building effective agents | Anthropic |
| 2 | New tools for building agents | OpenAI |
| 3 | Agents SDK overview | OpenAI |
Then Read
| Title | Vendor |
|---|---|
| Orchestrating Agents: Routines and Handoffs | OpenAI |
| Structured Outputs for Multi-Agent Systems | OpenAI |
Build Exercise
Build a customer service/ticket triage agent: router → specialist → evaluator, with all outputs constrained by structured schemas.
Phase 2 — MCP & Tool Ecosystem
Understand MCP server/client, remote vs local, tool loading, approval, connector boundaries.
Read First
| # | Title | Vendor |
|---|---|---|
| 1 | Introducing the Model Context Protocol | Anthropic |
| 2 | MCP and Connectors | OpenAI |
| 3 | Building MCP servers for ChatGPT Apps and API integrations | OpenAI |
Then Read
| Title | Vendor |
|---|---|
| Code execution with MCP: Building more efficient agents | Anthropic |
| Model Context Protocol - Codex | OpenAI |
| OpenAI Docs MCP | OpenAI |
Build Exercise
Build a read-only repo/docs MCP server, then create an eval to verify the agent correctly cites documentation.
Phase 3 — Context, Memory & Skills
Learn to control context window, short/long-term memory, skills/plugins, CLAUDE.md/AGENTS.md.
Read First
| # | Title | Vendor |
|---|---|---|
| 1 | Effective context engineering for AI agents | Anthropic |
| 2 | Equipping agents for the real world with Agent Skills | Anthropic |
| 3 | Building Reliable Agents with Memory and Compaction | OpenAI |
Then Read
| Title | Vendor |
|---|---|
| Custom instructions with AGENTS.md - Codex | OpenAI |
| Best practices for Claude Code | Anthropic |
| Agent Skills - Codex | OpenAI |
Build Exercise
Implement the same task as a Skill/Plugin, then measure accuracy and token cost across three variants: no skill, long prompt, and skill-based.
Phase 4 — Harness & Long-Running Agents
Master agent runtime: event stream, thread, tool execution, state, sandbox, approval, recovery.
Read First
| # | Title | Vendor |
|---|---|---|
| 1 | Unrolling the Codex agent loop | OpenAI |
| 2 | Unlocking the Codex harness: how we built the App Server | OpenAI |
| 3 | Effective harnesses for long-running agents | Anthropic |
Then Read
| Title | Vendor |
|---|---|
| The next evolution of the Agents SDK | OpenAI |
| Harness design for long-running application development | Anthropic |
| Scaling Managed Agents: Decoupling the brain from the hands | Anthropic |
Build Exercise
Build a mini coding harness: plan file, shell tool, apply patch, test gate, event log, and resume capability.
Phase 5 — Coding & Workspace Agents
Compare Codex vs Claude Code product/SDK forms; learn multi-agent, IDE, workspace collaboration.
Read First
| # | Title | Vendor |
|---|---|---|
| 1 | Introducing Codex | OpenAI |
| 2 | Best practices for Claude Code | Anthropic |
| 3 | Enabling Claude Code to work more autonomously | Anthropic |
Then Read
| Title | Vendor |
|---|---|
| Introducing the Codex app | OpenAI |
| Introducing workspace agents in ChatGPT | OpenAI |
| Apple's Xcode now supports Claude Agent SDK | Anthropic |
| Building Consistent Workflows with Codex CLI & Agents SDK | OpenAI |
Build Exercise
Run both OpenAI/Codex and Claude Code style workflows on the same repo: issue → plan → patch → tests → PR summary.
Phase 6 — Evals, Safety & Production
Build pre/post-launch eval loop, trace loop, safety boundaries, permissions, regression monitoring.
Read First
| # | Title | Vendor |
|---|---|---|
| 1 | Demystifying evals for AI agents | Anthropic |
| 2 | Testing Agent Skills Systematically with Evals | OpenAI |
| 3 | Build an Agent Improvement Loop with Traces, Evals, and Codex | OpenAI |
Then Read
| Title | Vendor |
|---|---|
| Running Codex safely at OpenAI | OpenAI |
| How we contain Claude across products | Anthropic |
| Evals API Use-case - MCP Evaluation | OpenAI |
| Measuring AI agent autonomy in practice | Anthropic |
Build Exercise
Build a smoke/macro eval suite for your agent: task success rate, tool misuse, prompt injection resistance, latency, cost, and human approval count.
Full Reading Table
Priority guide: P0 = must-read (architectural/conceptual), P1 = highly useful (implementation detail), P2 = optional context (background/releases).
| Priority | Title | Vendor | Topic | Key Idea | Date |
|---|---|---|---|---|---|
| P0 | OpenAI for Developers in 2025 | OpenAI | Agents; MCP; Platform | Annual overview: systematic walkthrough of Responses API, Agents SDK, AgentKit, Codex, MCP, Apps SDK, and AGENTS.md. | 2025-12-30 |
| P0 | New tools for building agents | OpenAI | Agents; Responses API; Tools | Key starting point for OpenAI's agent platform: Responses API, built-in web/file/computer tools, Agents SDK, tracing/observability. | 2025-03-11 |
| P0 | Introducing AgentKit | OpenAI | Agents; Evals; AgentKit | AgentKit, expanded evals, agent RFT: the official agent toolchain from prototype to production. | 2025-10-06 |
| P0 | Agents SDK overview | OpenAI | Agents; SDK | Official SDK entry point: concepts and boundaries of agent, tool, handoff, guardrail, and tracing. | Current docs |
| P0 | Orchestrating Agents: Routines and Handoffs | OpenAI | Agents; Handoffs; Orchestration | Classic introduction: how routines, handoffs, and tool calling combine into controllable multi-flow agents. | 2024-10-10 |
| P0 | Introducing the Model Context Protocol | Anthropic | MCP; Standards | The origin article for MCP: an open standard connecting AI assistants to data, tools, and systems. | 2024-11-25 |
| P0 | Building effective agents | Anthropic | Agents; Patterns; Frameworks | Essential agent primer: workflow vs agent, prompt/tool/retrieval, orchestrator-worker, evaluator-optimizer patterns. | 2024-12-19 |
| P0 | New tools and features in the Responses API | OpenAI | MCP; Responses API; Tools | Responses API extended to remote MCP servers, image/code/file tools; see how OpenAI integrates MCP into its runtime. | 2025-05-21 |
| P0 | MCP and Connectors | OpenAI | MCP; Connectors; Responses API | Official guide to connecting remote MCP servers and connectors; includes approvals and security considerations. | Current docs |
| P0 | Building MCP servers for ChatGPT Apps and API integrations | OpenAI | MCP; ChatGPT Apps; API | Official guide to writing MCP servers: supply tools/knowledge to ChatGPT Apps, deep research, and API integrations. | Current docs |
| P0 | Building a Deep Research MCP Server | OpenAI | MCP; Deep research | Minimal implementation of a search/fetch MCP server for Deep Research. | 2025-06-25 |
| P0 | Model Context Protocol - Codex | OpenAI | MCP; Codex | How Codex CLI/IDE connects to MCP servers, adding Figma, browser, docs, and internal tool context to agents. | Current docs |
| P0 | Introducing Codex | OpenAI | Agents; Coding; Sandbox | Cloud-based software engineering agent: parallel tasks, repo sandbox, running tests/linters/type checkers, producing auditable evidence. | 2025-05-16 |
| P0 | Unrolling the Codex agent loop | OpenAI | Harness; Agent loop; Codex | How Codex CLI chains prompt, tool schema, MCP tools, Responses API, and context management into an agent loop. | 2026-01-23 |
| P0 | Unlocking the Codex harness: how we built the App Server | OpenAI | Harness; Codex App Server; JSON-RPC | Core harness article: Codex core, App Server, JSON-RPC, streaming progress, approval, diff, and thread management. | 2026-02-04 |
| P0 | From model to agent: Equipping the Responses API with a computer environment | OpenAI | Harness; Responses API; Sandbox | Responses API + shell tool + hosted containers form the agent runtime; essential for understanding the model-to-agent execution environment. | 2026-03-10 |
| P0 | Harness engineering: leveraging Codex in an agent-first world | OpenAI | Harness; Agent-first engineering | Design product code, tests, CI, docs, and observability to be agent-readable/executable; learn agent-first repo organization. | 2026-02-11 |
| P0 | The next evolution of the Agents SDK | OpenAI | Harness; Agents SDK; MCP; Skills | Agents SDK harness becomes more complete: memory, sandbox orchestration, Codex-like filesystem tools, MCP, skills, AGENTS.md. | 2026-04-15 |
| P0 | Building Consistent Workflows with Codex CLI & Agents SDK | OpenAI | MCP; Codex; Agents SDK | Codex CLI as an MCP server integrated with Agents SDK; real multi-agent dev workflow. | 2025-10-01 |
| P0 | Building Reliable Agents with Memory and Compaction | OpenAI | Memory; Compaction; Reliability | Memory and compaction design for long-context/multi-turn agents. | 2026-05-01 |
| P0 | Build an Agent Improvement Loop with Traces, Evals, and Codex | OpenAI | Evals; Traces; Self-improvement | Connect traces, evals, and Codex fixes into an agent improvement loop. | 2026-05-12 |
| P0 | Eval Driven System Design - From Prototype to Production | OpenAI | Evals; Production | Use evals as the driving force for system design; ideal for moving agents from demo to production. | 2025-06-02 |
| P0 | Testing Agent Skills Systematically with Evals | OpenAI | Evals; Skills; Agents | Systematically test agent skills with evals; establish quality gates before skill release. | 2026-01-22 |
| P0 | Evals API Use-case - MCP Evaluation | OpenAI | MCP; Evals | Evaluate QA/retrieval capabilities with MCP tools; ideal for building an MCP regression suite. | 2025-06-09 |
| P0 | Running Codex safely at OpenAI | OpenAI | Safety; Sandbox; Codex | How OpenAI runs Codex internally: sandbox, approvals, network policy, agent-native telemetry. | 2026-05-20 |
| P0 | Building Governed AI Agents - A Practical Guide to Agentic Scaffolding | OpenAI | Governance; Guardrails; Agents | Governed agent scaffolding: permissions, guardrails, auditing, and organizational policies. | 2026-02-23 |
| P0 | Macro Evals for Agentic Systems | OpenAI | Evals; Agentic systems | Evaluate agents at the end-to-end/macro level, not just individual step outputs. | 2026-05-19 |
| P0 | Best practices for Claude Code | Anthropic | Coding agents; Claude Code | Claude Code methodology: verification loop, explore-plan-code, CLAUDE.md, permissions, MCP, subagents, context management. | 2025-04-18 |
| P0 | How we built our multi-agent research system | Anthropic | Agents; Multi-agent; Research | Claude Research multi-agent architecture: planner + parallel research agents + synthesis; production multi-agent experience. | 2025-06-13 |
| P0 | Writing effective tools for AI agents - with AI agents | Anthropic | Tools; MCP; Evals | Tool quality determines agent quality: tool descriptions, context budget, eval, and letting Claude optimize its own tools. | 2025-09-11 |
| P0 | Effective context engineering for AI agents | Anthropic | Context; Agents | Context is the agent's core resource: selection, compression, isolation, persistence, and context pollution control. | 2025-09-29 |
| P0 | Enabling Claude Code to work more autonomously | Anthropic | Claude Code; Agent SDK; Subagents | Claude Agent SDK, subagents, hooks, background tasks, checkpoints, and other autonomous coding agent capabilities. | 2025-09-29 |
| P0 | Equipping agents for the real world with Agent Skills | Anthropic | Skills; Agents | Agent Skills as modular capability packages: instructions, resources, scripts — reducing context burden and improving reliability. | 2025-10-16 |
| P0 | Code execution with MCP: Building more efficient agents | Anthropic | MCP; Code execution; Context | Key article on MCP scale challenges: reduce token overhead with code execution/on-demand tools; learn progressive disclosure. | 2025-11-04 |
| P0 | Introducing advanced tool use on Claude Developer Platform | Anthropic | Tools; MCP; Advanced tool use | Tool search, deferred loading, programmatic tool calling; solving context pollution from large numbers of MCP tools. | 2025-11-24 |
| P0 | Effective harnesses for long-running agents | Anthropic | Harness; Long-running agents | Essential harness reading: working across multiple context windows, task logging, external state, agent self-recovery. | 2025-11-26 |
| P0 | Demystifying evals for AI agents | Anthropic | Evals; Agents | Agent evals are more complex than static evals: multi-turn, tools, state changes, creative solutions, failure taxonomy. | 2026-01-09 |
| P0 | Measuring AI agent autonomy in practice | Anthropic | Agents; Autonomy; Measurement | Quantify agent autonomy using metrics like task duration and supervision needs; ideal for building autonomy benchmarks. | 2026-02-18 |
| P0 | Harness design for long-running application development | Anthropic | Harness; Application development | Harness design patterns for delegating long-running app development tasks to agents; compare with OpenAI Codex harness. | 2026-03-24 |
| P0 | Scaling Managed Agents: Decoupling the brain from the hands | Anthropic | Managed agents; Harness | Decouple the model brain from execution hands/harness, keeping interfaces stable as the harness evolves. | 2026-04-08 |
| P0 | How we contain Claude across products | Anthropic | Safety; Containment; Agents | Blast radius of powerful agent releases, human-in-the-loop, and containment strategies. | 2026-05-25 |
| P1 | Structured Outputs for Multi-Agent Systems | OpenAI | Agents; Multi-agent; Structured outputs | Use strict schemas to constrain structured messages and handoffs between multiple agents. | 2024-08-06 |
| P1 | Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku | Anthropic | Agents; Computer use | Claude computer use beta starting point: the model uses a computer via screenshots and actions. | 2024-10-22 |
| P1 | Raising the bar on SWE-bench Verified with Claude 3.5 Sonnet | Anthropic | Agents; Coding; Evals | SWE-bench agent scaffolding article: same model performance strongly depends on harness/scaffolding. | 2025-01-06 |
| P1 | Introducing Operator | OpenAI | Agents; Computer use; Safety | Early product form of browser-based agents: model clicks, types, and executes tasks on web pages, emphasizing user confirmation and safety boundaries. | 2025-01-23 |
| P1 | Computer-Using Agent | OpenAI | Agents; Computer use | Understand how CUA combines vision, mouse/keyboard actions, and environment feedback into an agent loop; compare with Claude computer use. | 2025-01-23 |
| P1 | Claude 3.7 Sonnet and Claude Code | Anthropic | Agents; Coding; Claude Code | Early release of Claude Code, marking Claude's entry into the agentic coding tool space. | 2025-02-24 |
| P1 | The think tool: Enabling Claude to stop and think in complex tool use situations | Anthropic | Tools; Reasoning; Agents | Give the model an explicit think tool in complex tool-use chains; learn tool design for policy-heavy/multi-step decisions. | 2025-03-20 |
| P1 | Evaluating Agents with Langfuse | OpenAI | Evals; Agents | Observe and evaluate Agents SDK runs with Langfuse; learn tracing/eval workflows. | 2025-03-31 |
| P1 | Parallel Agents with the OpenAI Agents SDK | OpenAI | Agents; Parallelism; Agents SDK | Parallel agent patterns: decompose tasks, execute in parallel, aggregate results. | 2025-05-01 |
| P1 | Multi-Agent Portfolio Collaboration with OpenAI Agents SDK | OpenAI | Agents; Multi-agent; Portfolio | Multi-agent collaboration business example: research, analysis, combined output. | 2025-05-28 |
| P1 | MCP-Powered Agentic Voice Framework | OpenAI | MCP; Voice; Agents | Voice agent + MCP paradigm: real-time interaction, tool extension, task execution. | 2025-06-17 |
| P1 | Deep Research API with the Agents SDK | OpenAI | Agents; Deep research; Agents SDK | Integrate Deep Research API into Agents SDK workflows. | 2025-06-25 |
| P1 | Desktop Extensions: One-click MCP server installation for Claude Desktop | Anthropic | MCP; Claude Desktop; Packaging | Package local MCP servers as one-click install extensions; learn MCP distribution/installation/local permission issues. | 2025-06-26 |
| P1 | Building a Supply-Chain Copilot with OpenAI Agent SDK and Databricks MCP Servers | OpenAI | MCP; Agents; Databricks | Enterprise data platform MCP + Agent SDK business agent example. | 2025-07-08 |
| P1 | Introducing ChatGPT agent: bridging research and action | OpenAI | Agents; ChatGPT; Computer use | End-user-facing ChatGPT agent: combining research, browser, computer use, file/slide capabilities. | 2025-07-17 |
| P1 | ChatGPT agent System Card | OpenAI | Agents; Safety; Evals | Learn pre-launch risk classification, evaluation, permissions, human confirmation, and abuse prevention for agent products. | 2025-07-17 |
| P1 | Context Engineering - Short-Term Memory Management with Sessions | OpenAI | Context; Sessions; Agents | How short-term memory/session state affects agent reliability. | 2025-09-09 |
| P1 | Introducing upgrades to Codex | OpenAI | Agents; Coding; IDE | Codex evolves from research preview to daily dev tool: CLI, IDE, web/mobile collaboration, and more independent task execution. | 2025-09-15 |
| P1 | Introducing Claude Sonnet 4.5 | Anthropic | Agents; Claude Agent SDK; Computer use | Sonnet 4.5 emphasizes coding, complex agents, computer use, with simultaneous Agent SDK launch. | 2025-09-29 |
| P1 | Introducing apps in ChatGPT and the new Apps SDK | OpenAI | MCP; Apps; ChatGPT | Apps SDK extends UI and tool server via MCP; entry point for understanding the ChatGPT app / MCP app ecosystem. | 2025-10-06 |
| P1 | Codex is now generally available | OpenAI | Agents; Coding; Codex SDK | Codex GA, Slack integration, Codex SDK, admin tools; see how coding agents enter enterprise management. | 2025-10-06 |
| P1 | Using PLANS.md for multi-hour problem solving | OpenAI | Codex; Long-running; Planning | Plan files and cross-context task management for long-running coding agents. | 2025-10-07 |
| P1 | Beyond permission prompts: making Claude Code more secure and autonomous | Anthropic | Safety; Permissions; Claude Code | From simple permission prompts to fine-grained security policies, reducing autonomous mode risk and interruptions. | 2025-10-20 |
| P1 | Introducing Aardvark: OpenAI's agentic security researcher | OpenAI | Agents; Security | Security-domain agent form: continuous scanning, issue verification, fix suggestions; later integrated as Codex Security. | 2025-10-30 |
| P1 | Build a coding agent with GPT 5.1 | OpenAI | Agents; Coding | Build a coding agent from scratch: understand file editing, command execution, loops, and verification. | 2025-11-13 |
| P1 | OpenAI co-founds Agentic AI Foundation | OpenAI | MCP; Standards; AGENTS.md | MCP, AGENTS.md, and agent standards enter the Linux Foundation/AAIF context; understand ecosystem standardization. | 2025-12-09 |
| P1 | Donating MCP and establishing the Agentic AI Foundation | Anthropic | MCP; Standards; AAIF | Anthropic donates MCP to Linux Foundation/AAIF; read alongside OpenAI's AAIF article. | 2025-12-09 |
| P1 | Context Engineering for Personalization - Long-Term Memory Notes | OpenAI | Context; Long-term memory; Agents | How long-term memory serves as agent personalization/state management. | 2026-01-05 |
| P1 | Supercharging Codex with JetBrains MCP at Skyscanner | OpenAI | MCP; Codex; IDE | Real IDE/MCP case study: how Codex CLI accesses IDE context and dev tools via JetBrains MCP. | 2026-01-11 |
| P1 | Designing AI-resistant technical evaluations | Anthropic | Evals; Technical hiring | How strong agents continuously break technical evaluations; relevant to benchmark contamination prevention and eval design. | 2026-01-21 |
| P1 | Inside OpenAI's in-house data agent | OpenAI | Agents; Data; Memory | Internal data agent case study: memory, Codex, data context, reliability; learn enterprise knowledge/data agents. | 2026-01-29 |
| P1 | Introducing the Codex app | OpenAI | Agents; Coding; Multi-agent | Desktop command center for agents: multi-threaded/parallel long tasks, project-level agent workflows. | 2026-02-02 |
| P1 | Apple's Xcode now supports Claude Agent SDK | Anthropic | Claude Agent SDK; Xcode; MCP | Embed Claude Agent SDK in Xcode: harness, subagents, background tasks, plugins, MCP. | 2026-02-03 |
| P1 | Quantifying infrastructure noise in agentic coding evals | Anthropic | Evals; Coding agents; Infrastructure | Environment configuration significantly impacts scores in agentic coding evals; control infrastructure noise in both production and benchmarks. | 2026-02-05 |
| P1 | Building a C compiler with a team of parallel Claudes | Anthropic | Multi-agent; Coding; Long-running | Parallel Claude teams completing large engineering tasks; learn multi-agent division of labor, coordination, and long-running execution. | 2026-02-05 |
| P1 | Codex Security: now in research preview | OpenAI | Agents; Security; Codex | Productization of an agentic security researcher: vulnerability discovery, verification, fix suggestions, reducing triage noise. | 2026-03-06 |
| P1 | Eval awareness in Claude Opus 4.6's BrowseComp performance | Anthropic | Evals; Agent awareness | Risk of models recognizing/adapting to evaluations; relevant to agent benchmark credibility discussions. | 2026-03-06 |
| P1 | How we built Claude Code auto mode: a safer way to skip permissions | Anthropic | Safety; Permissions; Autonomy | Claude Code auto mode risk classification, allow/block rules, exception handling, and security testing. | 2026-03-25 |
| P1 | Migrate a Legacy Codebase with Sandbox Agents | OpenAI | Agents; Sandbox; Evals | Sandbox agent evaluation and execution patterns in large legacy code migrations. | 2026-04-07 |
| P1 | Codex for (almost) everything | OpenAI | Agents; Codex; MCP; Plugins | Codex app expanded to Windows/macOS, computer use, in-app browser, memory, plugins, MCP servers. | 2026-04-16 |
| P1 | Computer Use Agents in Daytona Sandboxes | OpenAI | Computer use; Sandbox; Agents | Computer-use agents and sandbox runtimes; compare with Operator/CUA/Claude computer use. | 2026-04-19 |
| P1 | Introducing workspace agents in ChatGPT | OpenAI | Agents; Workspace; Governance | Workspace agents: shared agents, permissions, tools, memory, safeguards; ideal for team collaboration agent design. | 2026-04-22 |
| P1 | Building workspace agents in ChatGPT to complete repeatable, end-to-end work | OpenAI | Workspace agents; ChatGPT | Practical workspace agents for repeatable end-to-end team workflows. | 2026-04-22 |
| P1 | Speeding up agentic workflows with WebSockets in the Responses API | OpenAI | Agents; Latency; Responses API | Optimize latency by treating agentic rollouts as long-lived connections/tasks; learn production agent transport and caching. | 2026-05-01 |
| P1 | Agents for financial services | Anthropic | Agents; Finance; MCP | Ten ready-to-run agent templates, Claude Code/Cowork plugins, Managed Agents cookbooks, MCP app. | 2026-05-05 |
| P1 | Migrate from the Claude Agent SDK to the OpenAI Agents SDK | OpenAI | Agents SDK; Migration | Compare Claude Agent SDK and OpenAI Agents SDK from a migration perspective; ideal for dual-stack learning. | 2026-05-07 |
| P1 | Building a safe, effective sandbox to enable Codex on Windows | OpenAI | Safety; Sandbox; Codex | Coding agent sandbox design on Windows: file access, network restrictions, approval tradeoffs. | 2026-05-13 |
| P1 | Building self-improving tax agents with Codex | OpenAI | Agents; Evals; Self-improvement | Combine production traces, expert feedback, Codex loop, and eval infrastructure into self-improving business agents. | 2026-05-27 |
| P1 | SchemaFlow: Agentic Database Change Impact Analysis, SQL Generation, and Eval Guardrails | OpenAI | Evals; SQL; Agent guardrails | Guardrails and eval guardrails examples for data/SQL agents. | 2026-06-05 |
| P1 | Agents SDK quickstart | OpenAI | Agents; SDK | Quickly build a minimal agent; understand the code patterns of run, tool, and handoff. | Current docs |
| P1 | MCP Apps compatibility in ChatGPT | OpenAI | MCP; Apps SDK; UI | Understand MCP Apps UI standards, iframe/bridge, and compatibility between ChatGPT and other hosts. | Current docs |
| P1 | Use Codex with the Agents SDK | OpenAI | MCP; Codex; Agents SDK | Use Codex as an MCP server for other agents to call; ideal for multi-agent dev workflows. | Current docs |
| P1 | Agent approvals and security - Codex | OpenAI | Safety; Approvals; Codex | Official reference for Codex approval modes, sandbox, network access; read alongside OpenAI/Anthropic safety articles. | Current docs |
| P1 | Agent Skills - Codex | OpenAI | Codex; Skills; Plugins | Skills/Plugins as reusable workflow packages; compare with Anthropic Agent Skills. | Current docs |
| P1 | Custom instructions with AGENTS.md - Codex | OpenAI | AGENTS.md; Context | How AGENTS.md provides persistent project specifications for agents; establish repo-level agent contracts. | Current docs |
| P1 | Agents SDK integrations and observability | OpenAI | Observability; MCP; Tracing | Tracing, MCP integration, provider/observability; essential for production agent debugging. | Current docs |
| P1 | Secure MCP Tunnel | OpenAI | MCP; Security; Private tools | Securely expose private/intranet MCP servers to supported OpenAI surfaces; ideal for enterprise deployment. | Current docs |
| P1 | How Claude Code works | Anthropic | Claude Code; Agentic loop; Harness | Under-the-hood architecture of Claude Code: the agentic loop (gather context → act → verify), built-in tool categories, context window management, and extension points. | Current docs |
| P2 | Introducing Contextual Retrieval | Anthropic | Context; Retrieval; RAG | Not agent-specific, but important for agent RAG/context: prepend context to chunks before retrieval to improve recall. | 2024-09-19 |
| P2 | Developing a computer use model | Anthropic | Computer use; Agents | More technical explanation of how the computer-use model moves the mouse, clicks, types, and reads screen feedback. | 2024-10-22 |
| P2 | Introducing Claude 4 | Anthropic | Agents; Coding; Long-running | Overview of Claude Opus/Sonnet 4 capabilities: coding, advanced reasoning, agent workflows. | 2025-05-22 |
| P2 | Claude for Financial Services | Anthropic | Agents; Connectors; Finance | Vertical industry agent/connector productization case; understand data, permissions, and tool integration in finance. | 2025-07-15 |
| P2 | Advancing Claude for Financial Services | Anthropic | Agents; Skills; Finance | Claude for Excel, real-time data connectors, pre-built Agent Skills for vertical industry productization. | 2025-10-27 |
| P2 | Introducing GPT-5.3-Codex | OpenAI | Agents; Coding model; Evals | Codex-native model and long-running coding/terminal/agentic benchmarks; understand how model capabilities serve the harness. | 2026-02-05 |
| P2 | Introducing OpenAI Frontier | OpenAI | Agents; Enterprise; Governance | Enterprise AI coworker/agent platform: shared context, onboarding, permissions, guardrails, governance. | 2026-02-10 |
| P2 | Introducing Claude Sonnet 4.6 | Anthropic | Agents; Planning; Computer use | Sonnet 4.6 emphasizes coding, computer use, long-context reasoning, agent planning. | 2026-02-17 |
| P2 | Introducing Claude Opus 4.6 | Anthropic | Agents; Long-running; Tool use | Model release perspective on long-running tasks, agentic harness, subagents, and tool call capabilities. | 2026-02-25 |
| P2 | Introducing Claude Opus 4.7 | Anthropic | Agents; Long-running; Coding | Stronger software engineering and long-running task performance; track how model capabilities impact agent workloads. | 2026-04-16 |
| P2 | An update on recent Claude Code quality reports | Anthropic | Reliability; Claude Code; Agent SDK | Postmortem on Claude Code/Agent SDK quality regression; learn agent product operations and regression control. | 2026-04-23 |
| P2 | Introducing Claude Opus 4.8 | Anthropic | Agents; Dynamic workflows; Long-running | Dynamic workflows, hundreds of parallel subagents, long-running agentic tasks — latest model/product direction. | 2026-05-28 |
| P2 | Codex for every role, tool, and workflow | OpenAI | Agents; Codex; Plugins | Codex expands from development to knowledge work: role-specific plugins, Sites, annotations, parallel workflows. | 2026-06-02 |
| P2 | Codex is becoming a productivity tool for everyone | OpenAI | Agents; Knowledge work | Usage data shows how non-developers use Codex for reports, spreadsheets, research, automation, and lightweight tools. | 2026-06-02 |
| P2 | OpenAI Docs MCP | OpenAI | MCP; Docs; Context | Official OpenAI docs MCP server; connect docs directly to local agents/IDEs. | Current docs |
| P2 | Codex SDK | OpenAI | Codex SDK; Automation | Programmatically control Codex in CI/CD or internal tools; embed coding agents into existing workflows. | Current docs |
| P2 | When AI builds itself | Anthropic | Agents; Recursive self-improvement; Safety | How AI systems accelerate their own development through recursive self-improvement; three possible futures and the need for verifiable coordination. | 2026-05 |
Who Is This For?
- AI Engineers
- Agent Engineers
- LLM Engineers
- Platform Engineers
- Research Engineers
- AI Startup Founders
Contributing
Contributions are welcome. If you find:
- New OpenAI resources
- New Anthropic resources
- MCP updates
- Agent evaluation frameworks
- Production engineering articles
Please open a pull request.
Vision
The goal of this project is to become the System Design Primer for Agentic Engineering.
If you're serious about building production AI agents, start here.
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