441 stories
A practical, vendor-neutral guide to the API contract behind controllable agent runs, including lifecycle state, events, approvals, cancellation, observability, and auditability.
The post Collective Model Intelligence: The Next Scaling Axis? appeared first on Lightspeed Venture Partners.
Most AI agent platform roundups compare frameworks, builders and runtimes as if they were the same purchase. We scored ten on one question: can it safely run real work after the demo?
AI News for 9/16/2026-9/17/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website lets you search all past issues. As a reminder, AINews is now a section of Latent Space. You can opt in/out of email frequencies!
Learn how to engineer the instructions, state, retrieval, memory, tools, and evaluation that reliable AI agents need at runtime.
Every LLM call is stateless; agent frameworks solve that within a single run, which is why the memory problem only shows up once the run ends.
For most of you reading, your card statement looks less like a list of hobbies and more like the most recent edition of LMArena.
In the Manus AI vs OpenAI comparison, Manus AI delivers superior execution for multi-step workflows that require writing code, analyzing data, and building finished deliverables. OpenAI Operator performs better for direct, browser-only tasks like booking travel and submitting...
A central goal of autonomous reinforcement learning is continuous policy training without external resets. However, existing paradigms largely depend on underlying environmental reversibility, a property absent in real world manipulation, where events such as pushing objects off tables or spilling…
TL;DR Taking place October 20 to 21 in San Jose, California, PyTorch Conference North America 2026 highlights open research, tooling, and performance optimization across compiler architecture, cross-hardware kernel domain-specific languages,...
AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive industry advisor list we may have ever seen for an early startup behind AIUC-1, their agent standard backed by real insurance:
Agent programs in healthcare and life sciences are being built under a different set of constraints than those in most industries. There’s plenty of upside if the constraints can be resolved.
A practical guide to AI agents for project management, with six workflows, tool categories, safety controls, and a 30-day pilot plan.
A practical comparison of seven leading AI agent frameworks: what each is built for, where it falls short, and how to choose.
Answer summary: The leading open source AI agent harnesses in 2026 include Stacklok Mecatl, OpenCode, and Pi, each taking a different approach to orchestrating agents, tools, and execution environments. Mecatl …
Answer summary: For enterprise AI infrastructure, Mecatl by Stacklok is the strongest open source option. It is the only agent harness built with architectural separation of the agent loop, tools, …
Answer summary: A cloud-native, Kubernetes-native agent harness eliminates the gap between local development and production, provides the isolation, scheduling, and identity primitives that enterprise agent workloads require, and lets platform …
A guide on scaling agents in Europe & the Middle East to see how Schneider Electric, Vodafone, and monday.com are approaching production AI at scale, from establishing shared agent platforms and LLMOps practices to designing multi-agent architectures with stronger observability, evaluation, and…
Showing 234 of 441 stories
Load more storiesGet the top AI news and tools straight to your inbox every week.
Weekly · AI news
Join 15,000+ AI enthusiasts
