A three-agent CrewAI pipeline backed by a locally running Llama 3.1 model via Ollama autonomously produces structured, cited research reports without requiring an OpenAI key. The pipeline uses a Resea…
SoloEngine, the first low-code Agentic AI development platform, enables building production-grade autonomous AI loops without writing code. It encapsulates Loop Engineering's six core primitives into …
The best open-source framework for building AI agents in 2026 depends on the use case, with popular options including LangChain/LangGraph, Google ADK, DeepAgents, CrewAI, AutoGen, and AG2.…
OWASP's Agentic Security Initiative Top 10 (ASI01-ASI10) provides a threat taxonomy for AI agents that use tools, memory, and multi-agent communication, distinct from the LLM Top 10. Testing 30 advers…
A developer argues that building an AI agent from scratch with vanilla Python and the OpenAI SDK is simpler and more transparent than using bloated frameworks like AutoGen, LangChain, or CrewAI. The p…
A developer identified a structural failure in multi-agent systems where write operations appear successful but data is lost due to race conditions in shared filesystem state. The issue, reported in f…
A new open-source tool, swarm-test, lets developers find failures in multi-agent AI systems before production by analyzing agent topology statically, without live LLM calls. It detects cascade failure…
A developer argues that enterprise AI agents often fail not because of model limitations but because they lack a shared business vocabulary. The engineer explains that building a taxonomy—a structured…
Lelu, an authorization engine for AI agents, detects prompt injection and low-confidence decisions to gate agent actions, offering four outcomes: allow, human review, compute (sandbox), or deny. The o…
A developer compiled a list of the 12 best frameworks for building AI agents in 2026, including LangGraph, LangChain, CrewAI, AutoGen, OpenAI Agents SDK, Semantic Kernel, PydanticAI, LlamaIndex, and H…
A developer built the same two-agent pipeline in LangGraph, CrewAI, and AutoGen, comparing their performance. Microsoft has discontinued support for AutoGen, which had 56,000 GitHub stars.…
Alibaba DAMO Academy released AgentScope 2.0, an open-source production-ready agent framework designed to leverage LLM reasoning without rigid pipeline constraints. The framework adds event systems, p…
A developer abandoned CrewAI for LangGraph after three months of production use, citing the framework's inability to handle conditional routing and retry logic in complex multi-agent pipelines. While …
Enterprise agentic AI projects face a critical governance gap between agent frameworks and production execution, with Gartner predicting over 40% will be canceled by 2027 due to inadequate risk contro…
Arize AI released Project Rosetta Stone, a reference implementation that builds the same agent across 22+ frameworks with three observability tiers, enabling engineers to see exactly how to instrument…
A developer built Gatewards, an open-source proxy that enforces per-agent API spending caps in the request path without taking custody of API keys. The tool addresses the gap between observability and…
A developer argues that most AI agents are overengineered, advocating for simpler workflows over complex multi-agent systems. The developer contends that many problems can be solved with deterministic…
Google introduced the Agent2Agent (A2A) protocol, an open standard for communication between independent AI agents, enabling interoperability across different frameworks and organizations. The protoco…
A guide promises to help developers ship their first AI agent in a day rather than two weeks, providing a 7-step path, copy-paste Agent SDK starter, and templates. The article targets builders who wan…
The success or failure of autonomous agent loops in AI systems depends on supervision, not the loop itself. Early failures were due to unsupervised loops, while successful production loops had constra…