AI Agent Frameworks: A Comparative Analysis of DSPy, Claude Agent SDK, OpenAI Agents SDK, CrewAI, AutoGen/Microsoft Agent Framework, LangGraph, and Google ADK
type: NewsArticle
description: Seven leading AI agent frameworks — DSPy, Claude Agent SDK, OpenAI Agents SDK, CrewAI, AutoGen/Microsoft Agent Framework, LangGraph, and Google ADK — now offer distinct trade-offs in abstraction level, provider scope, and orchestration philosophy as of mid-2026. LangGraph leads production deployments with 34.5 million monthly downloads and adoption by firms like Klarna and JP Morgan, while CrewAI enables the fastest prototyping at roughly 35 lines of code, and the Microsoft Agent Framework targets enterprise governance with OWASP compliance and dual-language support. The fragmentation means developers must prioritize between production durability, developer velocity, single-provider depth, or cross-vendor interoperability when selecting a framework.
date published: 2026-05-25 00:00:00+00:00
date modified: 2026-05-28 07:41:37.431799+00:00
language: en
is accessible for free: true
article body: Post # AI Agent Frameworks: A Comparative Analysis of DSPy, Claude Agent SDK, OpenAI Agents SDK, CrewAI, AutoGen/Microsoft Agent Framework, LangGraph, and Google ADK A deep-dive into the design philosophies, architectures, capabilities, trade-offs, and production readiness of the seven leading AI agent frameworks as of May 2026. ## Executive Summary The AI agent framework landscape in mid-2026 has crystallized into seven distinct approaches to building autonomous systems. Rather than a single winner, we see a fragmentation along three primary axes: **abstraction level** (from DSPy’s declarative programming model to LangGraph’s low-level graph runtime), **provider scope** (Claude Agent SDK’s Anthropic-only focus vs. the provider-agnostic CrewAI, LangGraph, and Google ADK), and **orchestration philosophy** (role-based teams in CrewAI vs. conversational debate in AutoGen vs. graph state machines in LangGraph). **Decision matrix — choose your framework by priority:** | If your top priority is… | Recommended framework(s) | Rationale | |---|---|---| Fastest prototype to working prototype | CrewAI | ~35 lines of code; team metaphor maps naturally to most business workflows | Maximum production durability (crash recovery, checkpointing) | LangGraph | First stable v1.0 with durable execution; deployed by 400+ firms | Deepest single-provider operational capabilities | Claude Agent SDK | File/shell access, MCP integration, 18 lifecycle hooks — same architecture as Claude Code | Cleanest multi-agent handoff with provider flexibility | OpenAI Agents SDK | Typed handoffs with metadata; 100+ models via Responses API; built-in tracing | Enterprise governance and OWASP compliance (Azure/.NET shops) | Microsoft Agent Framework | OWASP Agentic Top 10 coverage, dual-language (.NET + Python), best HITL | Prompt quality optimization across any pipeline | DSPy (combined with an orchestration framework) | MIPROv2 and GEPA optimizers produce better prompts automatically; pair with LangGraph…
publisher: Web Pulse
keywords: ai-agents, ai-tools, artificial-intelligence, large-language-models, ai-infrastructure
mentions: DSPy
mentions: Claude Agent SDK
mentions: OpenAI Agents SDK
mentions: CrewAI
mentions: AutoGen
mentions: LangGraph
mentions: Google ADK
mentions: Anthropic
citation: CreativeWork