Frameworks
9 articles in this topic.
MCP is the USB-C of AI tools, finally
Anthropic shipped the Model Context Protocol in late 2024 as a small, JSON-RPC-shaped spec for connecting LLM clients to tools and data sources. Eighteen months later, it's the most adopted open protocol in the AI space — and the hype is, for once, an undercount.
We built the same agent three times: MAF, LangGraph, and ADK
Three frameworks, one problem: an invoice-processing agent that ingests PDFs, validates against a database, asks a human when uncertain, and writes back to an ERP. What each framework made easy. What each one made painful.
Google's Agent Development Kit, and when to reach for it
ADK is Google's bet on agent infrastructure: a thin SDK that takes Gemini's strengths — tool calling, grounding, multimodality — and makes them deployable to Vertex AI Agent Engine in one command. It is less framework than LangGraph, more framework than calling the model directly, and uniquely useful inside Google Cloud.
Microsoft Agent Framework, six months in
Microsoft consolidated Semantic Kernel and AutoGen into a single Agent Framework in late 2025. Half a year later, the picture is clear: MAF is the Azure-native option for shops that already speak C# and .NET, and its workflow/agent split is the most pragmatic in the industry.
LangGraph is what you reach for when the agent has to remember
By mid-2026 LangGraph is the default orchestration layer for stateful, long-running, human-in-the-loop agents. Not because of the API — because of the checkpoints, the interrupts, and the fact that the state outlives the request.
CrewAI vs LangGraph vs AutoGen: the ecosystem reality of 2026
Three years into the agent framework era, only two of those three names belong in the same sentence in 2026. Here's the actual usage picture — stars, downloads, who's running what in production, and where each one quietly wins.
DSPy: declarative prompting in production
Stanford's DSPy proposes 'programming, not prompting' — declare a signature, compose modules, let an optimizer write the prompt. The pitch is irresistible; the production reality is more selective. Where DSPy actually ships, and why most teams quietly keep their prompts.
Pydantic AI: typed agents for the Python ecosystem
The Pydantic team built the framework most FastAPI engineers were quietly wishing for. Schema-first, model-agnostic, async-native — the agent framework that feels like Python production code instead of a research demo.
Inspect AI: the UK AISI's eval framework everyone copied
A government safety institute released an MIT-licensed eval framework in 2024. By 2026 it's the de facto standard at Anthropic, OpenAI, DeepMind, and the enterprise teams that take evals seriously. Here's why it won — and what the alternatives still get right.