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ProtoLink is a lightweight A2A-first Python framework for building pluggable agents and multi-agent systems, emphasizing local-first, LLM-agnostic design with optional modules.
Austin Berke, Lead AI Product Engineer at Harmonic, shared how they used LangChain's Deep Agents framework to rebuild Scout, quadrupling user retention from week 1 to week 4. The core approach is to use the file system as shared storage to manage context, connecting agents, frontend, and deterministic processes, allowing the model to build context on demand.
Aeon is an autonomous agent framework that ships features to repos, finds real vulnerabilities, and deploys live apps without approval loops, running unattended on GitHub Actions. It supports 60+ skills across six harnesses and can write new skills for itself.
Discusses Codex's gradual monopoly trend on X and overseas markets, and how the survival space for other frameworks like Kimi CLI, ZCode, and Grok Build is shrinking.
LiveKit Agents is an open-source real-time voice agent framework supporting WebRTC, telephony integration, semantic turn detection, MCP tool calling, and multi-agent handoff, helping developers quickly build real-time voice applications such as AI customer service and phone bots.
Hermes Agent v0.20.0 'The Herald' released with conversational voice and barge-in, grounded citations with fact-checking, outbound webhooks, desktop platform features, A2A protocol support, and major performance improvements.
The paper proposes an unsupervised self-evolving agent framework inspired by diffusion models, using self-supervised semantic diffusion to train external skill libraries for LLM agents in specialized domains like creative screenwriting, without requiring weight access or external supervision.
Matryoshka Agent is a hierarchical agent framework that decomposes long-horizon machine learning engineering tasks into a high-level Orchestrator and low-level Sub-Agents, enabling efficient exploration and iterative refinement. It significantly improves performance on complex MLE tasks, allowing a 4B model to match the orchestration of o4-mini and yielding up to 36.7% relative gain on a 30B coder model.
A new AI agent framework that treats agents as software components, offering more transparent and controllable development instead of the illusion of control found in most frameworks.
The Eve framework by Vecel is an elegant agent framework likened to Next.js for agents, where the file system serves as a simplified agent stack.
Anthropic published a playbook proposing an AI Operating System architecture that coordinates memory, planning, tools, and evaluation, shifting from single-prompt chatbots to production-grade autonomous agents.
Guillermo Rauch announces Eve.dev, a framework for building durable agents inspired by Next.js, featuring durability, sandboxing, human-in-the-loop, and easy integration with existing Next.js apps.
Spring AI Alibaba is an open-source Java framework for building stateful agentic workflows with multi-agent orchestration, graph workflows, and multimodal support, integrating with Spring AI.
A 13-step roadmap for transitioning from loop-based to graph-based agent design, emphasizing immutable state, pure nodes, and checkpoints for resilience.
Pi 0.81.0 adds support for llama.cpp, enabling local LLM inference within the Pi coding agent harness.
Mastra released file-based agents allowing developers to define agents on the filesystem and immediately use them in the Agent Studio GUI, eliminating glue code and simplifying sharing.
The yoyo framework achieves persistent directed graph state management by integrating the GASP (Git Agent State Protocol), enabling agent states to be branchable, versionable, auditable, and replayable, marking a shift from wild growth to traceable persistence.
Google released ADK 2.0, an open-source, code-first Python framework for building AI agents with graph-based orchestration and agent-to-agent delegation, aiming to replace expensive enterprise agent frameworks.
AVE-Compass is a new benchmark for holistic evaluation of audio-video editing abilities, with 145 videos, 196 editing instructions, and 2,688 checklist items. It also proposes AVE-Agent, a modular agent framework that improves cross-modal editing via self-reflection and evaluator feedback.
The author promotes his open-source book 'In-depth Understanding of AI Agents: Design Principles and Engineering Practices', continuously revised and incorporating the latest research results, covering Agent design principles and engineering practices, with example code and experiments.