38 stories
TL;DR An agent can spot a customer issue and recommend a next step. Finishing the job means pulling account details, checking a policy, updating the...
Twice as many companies use OpenAI's agent orchestration platform as Anthropic's, VentureBeat Intelligence found in its September survey on agent orchestration. OpenAI holds that lead even though Anthropic may lead OpenAI on other important indicators.
Build reliable computer use agents that pause when needed, let a human verify or intervene, then resume. Use the awaiting_human state and resume endpoint to orchestrate safe workflows.
TL;DR: AI agent orchestration is the coordination of multiple agents, tools, models, and shared state, and in production it only works when operational controls run inside every agent, tool call, and handoff. Each orchestration pattern fails in its own way, so each needs its own controls.
Ship a human-like automation agent in hours, not days. You’ll drive real desktops, browsers, and terminals with the Coasty computer use API, paying only for steps you take.
Despite rapid progress in automating scientific research, generating promising and well grounded research solutions remains a central challenge. We isolate research ideation as a standalone task and build our solution on the intuition that a challenge in one field can often be addressed by a…
For the August VB Pulse, VentureBeat Intelligence surveyed respondents from organizations with 100 or more employees. We asked which agent orchestration platforms they run and why, what they plan to adopt next, where they expect agent control to sit and how they stop runaway agent spending.Read more
Learn what subagents are, how AI agents delegate tasks, and when multi-agent workflows outperform a single agent, with architecture patterns, risks, and design guidance.
Banks are fueling a hiring surge for AI engineers who are good at "agent orchestration" — the ability to coordinate teams of specialized agents.
Banks are fueling a hiring surge for AI engineers who are good at "agent orchestration" — the ability to coordinate teams of specialized agents.
Running one AI coding agent is productive. Running five of them at once across three repositories? That’s a coordination problem. Agentic development environments (ADEs) give you a single surface to orchestrate multiple agents, review what each one changed, and get code merged.
AI agent orchestration explained: the coordination patterns, how it works at production scale, and when to build on a framework versus buy a platform.
Replacing one LLM agent with a collaborating team can raise accuracy, but whether scaling the team helps, and which architecture to scale, is unclear. Sweeping eight agent orchestration architectures across five instruction-tuned 7-9B models, five short-answer benchmarks, and an executable-code…
AI phone agent pricing hides three cost layers enterprise buyers never see. Avoid budget surprises with our full 2026 vendor breakdown.
A practical, vendor-neutral guide to the API contract behind controllable agent runs, including lifecycle state, events, approvals, cancellation, observability, and auditability.
Learn how to engineer the instructions, state, retrieval, memory, tools, and evaluation that reliable AI agents need at runtime.
A practical guide to AI agents for project management, with six workflows, tool categories, safety controls, and a 30-day pilot plan.
Gartner published its first Magic Quadrant for AI Governance Platforms in June and a Hype Cycle for AI Governance Technologies in August. Both are rigorous. Both answer the question they set out to answer. Our argument is with the title, "AI Governance," not the research under it.
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