venturebeat
Shared memory is the missing layer in AI orchestration

The key to successful AI agents within an enterprise? Shared memory and context. This, according to Asana CPO Arnab Bose, provides detailed history and direct access from the get-go — with guardrail checkpoints and human oversight, of course. This way, “when you assign a task, you're not having to go ahead and re-provide all of the context about how your business works,” Bose said at a recent VB event in San Francisco. AI as an active teammate, rather than a passive add-onAsana launched Asana AI Teammates last year with the philosophy that, just like humans, AI agents should be plugged directly into a team or project to create a collaborative system. To further this mission, the project management company has fully integrated with Anthropic’s Claude.  Users can choose fro [...]

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venturebeat
Claude’s next enterprise battle is not models: it’s the agent control plane

New VB Pulse data shows Microsoft and OpenAI leading enterprise agent orchestration, but Anthropic’s first measurable foothold points to a larger fight over who controls the infrastructure where AI [...]

Match Score: 219.20

venturebeat
Mistral AI launches Workflows, a Temporal-powered orchestration engine already running millions of daily executions

Mistral AI, the Paris-based artificial intelligence company valued at €11.7 billion ($13.8 billion), today released Workflows in public preview — a production-grade orchestration layer designed to [...]

Match Score: 92.49

venturebeat
Anthropic wants to own your agent's memory, evals, and orchestration — and that should make enterprises nervous

Just a few weeks after announcing Claude Managed Agents, Anthropic has updated the platform with three new capabilities that collapse infrastructure layers like memory, evaluation, and multi-agent orc [...]

Match Score: 85.75

venturebeat
Vibe coding can build your pipeline. It can't explain it six months later

AI coding agents are rapidly accelerating data engineering by generating transformations, pipelines, orchestration workflows, validation tests, and infrastructure configurations from prompts. However, [...]

Match Score: 84.82

venturebeat
A 0.12% parameter add-on gives AI agents the working memory RAG can't

AI agents forget. Every time a coding assistant loses track of a debugging thread, or a data analysis agent re-ingests the same context it already processed, the team pays in latency, token costs, and [...]

Match Score: 82.54

venturebeat
AI agents are learning on the job — just not for your whole team

When someone on a team corrects an AI agent — better prompts, better feedback, better context — that improvement disappears the moment a colleague opens the same tool. The correction doesn't [...]

Match Score: 77.71

venturebeat
Google PM open-sources Always On Memory Agent, ditching vector databases for LLM-driven persistent memory

Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory.This week, he published an open-sour [...]

Match Score: 77.04

venturebeat
DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups

When an enterprise LLM retrieves a product name, technical specification, or standard contract clause, it's using expensive GPU computation designed for complex reasoning — just to access stati [...]

Match Score: 72.17

venturebeat
Your enterprise AI agents should automatically remember which model is right for which task. Mindstone built the capability with Rebel

AI agent orchestration platforms are popping up like weeds these days, but London-based AI transformation startup Mindstone's Rebel might be among the most promising I've come across. That&# [...]

Match Score: 71.14