Curated insights on AI agents, workflows, and autonomous systems for professionals.
Explore cutting-edge software architecture and agentic engineering at Craft Conference 2026. The only chance to meet with the author of the global top GitHub repos RuFlo (ClaudeFlow) and RuVector in Europe this year!
Discover D.U.H., an open-source project aiming to make building advanced AI agent solutions and workflows more accessible and transparent. It's designed to be provider-agnostic, supporting various frontier models and fostering community-driven development.
Discover the BHIL methodology for building AI-first projects, emphasizing clear specifications over code. Learn how to manage AI development through structured documentation, from product requirements to technical specifications and task breakdowns.
Explore how an 'evolved agentic container' integrates tools like notebooklm to describe its own functions. This development showcases advancements in autonomous systems that can understand and articulate their operational context.
This article is a Google sign-in page. It does not contain information about AI agents or their impact on work.
Discover how VisionClaw transforms organizations into 'governed agentic meshes,' where AI agents and human judgment collaborate seamlessly. This platform addresses the growing challenge of unmanaged AI adoption by providing a structured, secure, and auditable framework for autonomous systems.
A new AI model, GPT-5.5, demonstrates a significant leap in capabilities, showcasing an impressive step forward in AI development. This advancement signals a future where AI can perform increasingly complex tasks.
A community of AI practitioners shared working prototypes that automate everything from podcast production to building safety analysis. Their candid discussion reveals which models work best for different tasks, what actually breaks in production, and how to build agents that scale on modest hardware.
You can now build complex AI systems faster than you can explain them. A builder creating production multi-agent workflows reveals the real constraint isn't capability anymore—it's whether you can understand and trust what you've created.
Ethan Mollick examines the current capabilities and limitations of AI agents, then maps out the practical implications for how autonomous systems will reshape work in the near term.
Teams are building agent-driven systems that automatically organize knowledge, curate content, and handle complex workflows—but face real challenges around access control, creative oversight, and how to structure information so agents can actually use it effectively.
An AI agent swarm generated 138 fashion campaign assets in 96 minutes—without a human ever opening a creative application. The system took only voice instructions and handled everything from workflow design to quality assurance autonomously, delivering 9x faster results than traditional methods.
A WiFi-based system can now track multiple people's body positions through walls in real-time, opening new possibilities for healthcare monitoring and smart home automation without cameras. The open-source project has attracted significant developer attention and addresses privacy concerns in autonomous environment monitoring.
Beyond building bigger AI models lies a more durable path: systems that maintain internal coherence through structured contrast, self-measurement, and proof-gated learning. This framework could reshape how autonomous agents operate reliably in production environments.
A developer shares reflections on unexpected viral success with multiple open-source projects, emphasizing that community engagement and technical debate matter more than vanity metrics—lessons relevant to anyone building AI tools or platforms.
A new startup has solved a major cost problem holding back AI adoption: existing hardware wastes enormous resources running language models. Their approach cuts costs by up to 50x and energy use by 80%, making AI inference dramatically more affordable for enterprises.
Marketing teams can automate complex multi-channel campaigns using AI agents that handle timing, personalization, and content approval without constant manual oversight. Trigger.dev shows how to build drip campaigns, behavioral triggers, and approval workflows that scale across thousands of customers.
As AI agents become capable of handling complex tasks autonomously, the real question isn't whether they work—it's whether organizations will actually use them to do meaningful work instead of just generating more presentations.
Our Founder, Reuven Cohen showcases RuVector, an AI system that analyzes genetic sequences in milliseconds on a standard laptop—introducing an architecture designed around structured intelligence and continuous self-learning rather than traditional prompt-based outputs.
Large language models inherit a distinctly technical communication style from their developers. Understanding this hidden bias matters as you deploy AI agents in your organization—the way they 'speak' shapes how employees trust and adopt them.
OpenAI's GPT-5 represents a shift toward AI systems that take independent action rather than just responding to prompts. This changes how professionals might deploy AI in their workflows—from asking questions to letting AI handle complete tasks autonomously.
Adding an AI agent to your team isn't about replacing people—it's about amplifying what your existing workforce can accomplish. Explore how AI teammates boost performance, fill expertise gaps, and make work more enjoyable.
A new open-source tool by our London member Peter Hollis captures everything on your screen and in meetings, storing it locally with AI-powered search—giving autonomous systems a persistent memory without cloud dependencies or privacy trade-offs.
Organizations often fall into cycles of constant redesign without clear purpose. A potential AI-driven solution offers a way to break this pattern and focus design efforts where they matter most.
Beyond simple chatbots, modern AI tools serve different purposes in autonomous workflows. Learn which AI systems match your specific needs as intelligent agents reshape how work gets done.
As AI reshapes how expertise is valued at work, professionals need to understand what 'knowing things' actually means in a world where AI can do many tasks. This shifts how we think about building and demonstrating real capability.
The Agentics Foundation London chapter showcased real-world applications of AI agents in February 2026, from physical rehabilitation sensors to code structure visualization tools. Speakers demonstrated how agents are handling code generation, testing, and multi-language support—while raising questions about whether these advances actually matter beyond tech communities.
As AI agents become more capable, how do you actually verify they're doing what you need? Mollick explores the real challenges of working with powerful AI systems and what reliability means on the frontier of autonomous tools.
A new framework challenges how we think about rapid technological change, moving beyond exponential growth models to explain why our reality feels increasingly unpredictable and complex.
The Agentics Foundation's Assam Chapter is holding its first in-person meetup in Guwahati, bringing together 100+ community members to discuss AI agents, governance frameworks, and emerging applications in the Northeast India region.
