All posts tagged: orchestration

Claude Code’s revised projects adds AI orchestration, but local developers must wait

Claude Code’s revised projects adds AI orchestration, but local developers must wait

Published by skeptic

Screenshot by David Gewirtz/ZDNET ZDNET’s key takeaways Claude Code Projects could tame multi-agent chaos. Cloud users get persistent threads and shared memory. Local workflows remain outside the new system for now. Claude Code has always had projects, in the sense that a given directory is declared as the root for source code. I keep each of the apps I’m developing in separate directories, and I’ve built up a complex orchestration and management workflow that allows certain messages to be exchanged between these directories. Beyond that, they’re isolated code structures. Also: After the vibe-coding rush comes the debugging hangover Today, Anthropic is announcing that it’s redesigning the idea of projects in Claude Code, adding both superpowers and hard limits. For certain classes of work, they can be game-changing. For other types of work, they’re essentially irrelevant. Right now, this capability is being offered to “Select Claude Pro and Max subscribers who use cloud sessions in Claude Code and don’t have any existing projects on the web and desktop,” Anthropic said. Features will roll out to other …

Orchestration is the new challenge for CX in the age of AI agents

Orchestration is the new challenge for CX in the age of AI agents

Published by skeptic

Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of that deployment has involved attaching conversational AI to legacy systems never built for it, says Gaurav Anand, global head of the Customer Interaction Suite at Tata Communications. “In the rush to deploy AI, organizations have largely bolted conversational AI onto legacy systems,” Anand says. “As a result, while many enterprises have adopted digital tools, very few have platforms that are truly integrated, scaled, and capable of seamless orchestration.” That gap creates a heavy cognitive load for human agents who must piece together context across disjointed tools to understand what an AI system has already told a customer. The challenge is not simply access to data, but the absence of a shared enterprise context that connects customer identities, interactions, transactions, policies, journeys, and operational systems into a common understanding. Traditional CX architecture was built for linear, human-driven routing, not for managing real-time data flows between autonomous AI …

Agentic orchestration: Enterprise AI organizations know how to govern agents but still can’t meter what they cost

Agentic orchestration: Enterprise AI organizations know how to govern agents but still can’t meter what they cost

Published by skeptic

Across 107 enterprises, agentic orchestration is not a choice of a single platform. The typical enterprise runs three orchestration platforms at once, and selects them for flexibility across models rather than affinity to any single one. Microsoft leads primary usage while Anthropic leads forward consideration by a wide margin.  The AI control plane enterprises expect is deliberately hybrid, meaning it includes use of the leading AI providers, but also provider-independent technologies — and the risk they fear most from provider-resident control is not lock-in but the provider’s own security and permissioning limits.  One in five enterprises still has no real-time way to stop a runaway agent before the bill arrives. This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what drives the choice, what they optimize for, how they expect agent control to be structured, and — most revealingly — how orchestrated their deployed “agents” actually are and how tightly they control the cost of running them. The central finding is that orchestration has become plural. Eighty-five percent of …

Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents

Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents

Published by skeptic

Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is deliberately hybrid to avoid lock-in, and real-time fiscal control over token burn remains the exception. This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what drives the choice, what they optimize for, how they expect agent control to be structured, and — most revealingly — how orchestrated their deployed “agents” actually are and how tightly they control the cost of running them. The central finding is a gap between orchestration ambition and orchestration reality. Enterprises are consolidating fast onto the major model platforms: Anthropic’s Claude is the primary platform for 40%, more than double any rival, followed by Microsoft (18%) and OpenAI (13%). The choice is driven by “model gravity” — native alignment with …

Adobe embeds agentic AI workflows across Creative Cloud, shifting from media generation to production orchestration

Adobe embeds agentic AI workflows across Creative Cloud, shifting from media generation to production orchestration

Published by skeptic

Adobe has announced a major expansion of its “creative agent” across its flagship Creative Cloud suite and upgraded Firefly AI studio. Available in public beta starting today across Premiere Pro, Photoshop, Illustrator, InDesign, and Frame.io, the agent is designed to serve everyone from individual creators to enterprise marketing teams. Unlike first-generation generative AI tools that simply output flat media from a chat interface, Adobe’s embedded assistant acts as an orchestration layer. It interprets natural language prompts and directly accesses the underlying software’s APIs to execute complex, multi-step production workflows—from batch-renaming video sequences to dynamically updating brand assets across print layouts—while leaving the final aesthetic decisions entirely in the hands of the human designer. Technology: Contextual Memory and DOM Manipulation At the core of this release is a significant technical upgrade to how Adobe’s AI handles persistent memory and context window management. In its upgraded Firefly creative AI studio—currently in private beta—Adobe has introduced two foundational architectural components: “Elements” and “Projects”. Elements functions as a visual variables library, allowing users to save and reuse specific characters, …

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

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

Published by skeptic

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 orchestration, into a single runtime. This move could threaten the standalone tools that many enterprises cobble together. The new capabilities — ‘Dreaming,’ ‘Outcomes,’ and ‘Multi-Agent Orchestration’ — aim to make agents inside Claude Managed Agents “more capable at handling complex tasks with minimal steering,” Anthropic said in a press release.   Dreaming deals with memory, where agents “reflect” on their many sessions and curate memories so they learns and surface unknown patterns. Outcomes allows teams to define and set specific rubrics to measure an agent’s success, while Multi-Agent Orchestration breaks jobs down so a lead agent can delegate to other agents. Claude Managed Agents ideally provides enterprises with a simpler path to deploy agents and embeds orchestration logic in the model layer. It’s an end-to-end platform to manage state, execution graphs, and routing. With the addition of Dreaming, Outcomes and Multi-agent Orchestration, Claude Managed Agents expands capabilities even further …

AWS Quick’s personal knowledge graph is making orchestration decisions most control planes can’t see

AWS Quick’s personal knowledge graph is making orchestration decisions most control planes can’t see

Published by skeptic

Enterprise AI teams running centralized orchestration stacks now have a new variable to account for: AWS Quick, which expanded this week to a desktop-native agent that builds a persistent personal knowledge graph and executes actions across local files and SaaS tools — outside the visibility of most control planes. Unlike chat-based copilots that reset with each session, Quick now maintains a continuously updated knowledge graph built from the user’s local files, calendar, email and connected SaaS apps. It uses it to proactively trigger actions without waiting to be asked. AWS launched Quick in October last year as an alternative to AI workflow and productivity platforms coming from Google, OpenAI and Anthropic. It was a way for enterprise employees to access insights from connected applications, an agent builder, deep research, and workflow automation. Now, it’s grown beyond a simple AI assistant and acts more as a proactive workflow agent with a stateful, real-time knowledge graph of the user. It integrates with third-party apps like Google Workspace, Microsoft 365, Zoom, Salesforce and Slack — and now local …

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

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

Published by skeptic

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 move enterprise AI systems out of proofs of concept and into the business processes that generate revenue. The product, which launches as part of Mistral’s Studio platform, is the company’s clearest articulation yet of a thesis that is quietly reshaping the enterprise AI market: that the bottleneck for organizations adopting AI is no longer the model itself, but the infrastructure required to run it reliably at scale. “What we’re seeing today is that organizations are struggling to go beyond isolated proofs of concept,” Elisa Salamanca, who leads go-to-market for Mistral’s enterprise products, told VentureBeat in an exclusive interview ahead of the launch. “The gap is operational. Workflows is the infrastructure to run AI systems reliably across business-critical processes.” The release arrives at a pivotal moment for both Mistral and the broader AI industry. The dedicated agentic AI market has been valued at approximately $10.9 billion in 2026 and is …

Kimi K2.6 runs agents for days — and exposes the limits of enterprise orchestration

Kimi K2.6 runs agents for days — and exposes the limits of enterprise orchestration

Published by skeptic

Most orchestration frameworks were built for agents that run for seconds or minutes. Now that agents are running for hours — and in some cases days — those frameworks are starting to crack. Several model providers, such as Anthropic with Claude Code and OpenAI with Codex, introduced early support for long-horizon agents through multi-session tasks, subagents and background execution. However, these systems sometimes assume agents are still operating within bounded-time workflows even when they run for extended periods.  Open-source model provider Moonshot AI wants to push beyond that with its new model, Kimi K2.6.  Moonshot says the model is designed for continuous execution, with internal use cases including agents that ran for hours and, in one case, five straight days, handling monitoring and incident response autonomously. But this growing use of this type of agent is exposing a critical gap in orchestration: most orchestration frameworks were not designed for this type of continuous, stateful execution. Open-source models, such as Kimi K2.6, that rely on agent swarms are making the case that their orchestration approach comes …

8 billion tokens a day forced AT&T to rethink AI orchestration — and cut costs by 90%

8 billion tokens a day forced AT&T to rethink AI orchestration — and cut costs by 90%

Published by skeptic

When your average daily token usage is 8 billion a day, you have a massive scale problem. This was the case at AT&T, and chief data officer Andy Markus and his team recognized that it simply wasn’t feasible (or economical) to push everything through large reasoning models. So, when building out an internal Ask AT&T personal assistant, they reconstructed the orchestration layer. The result: A multi-agent stack built on LangChain where large language model “super agents” direct smaller, underlying “worker” agents performing more concise, purpose-driven work. This flexible orchestration layer has dramatically improved latency, speed and response times, Markus told VentureBeat. Most notably, his team has seen up to 90% cost savings. “I believe the future of agentic AI is many, many, many small language models (SLMs),” he said. “We find small language models to be just about as accurate, if not as accurate, as a large language model on a given domain area.” Most recently, Markus and his team used this re-architected stack along with Microsoft Azure to build and deploy Ask AT&T Workflows, …