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87% of finance leaders are raising their AI budget for FY2027, 45% of them by more than 20%, even though 61% already spend more on AI than they can justify. Most can't see where it goes: 54% can't break AI spend below a rough category, so budgets default to the total and keep climbing. The teams that allocate spend, tying each AI dollar to the team, product, or outcome behind it, are the ones who can defend the number to a board.

Harvey AI pricing is not published: every deal is sales-negotiated. Reported figures across procurement research converge on roughly $1,200 per lawyer per month at the base, 20-to-25-seat minimums, and 12-month terms, putting reported entry floors near $290,000 to $360,000 a year. Premium bundles run higher. No free tier, no monthly plan, no self-serve. Every figure on this page is labeled for what it is: disclosed by Harvey, reported by named research and journalists, or computed from those reports.

We’re excited to announce that Agentic Pipelines is now generally available across all paid Cloud Bitbucket plans. You can run agents on our cloud runners or on self-hosted Linux Docker runners, with support for more runner types coming soon. With this launch, Bitbucket Pipelines evolves from a CI/CD tool into an intelligent workflow engine that increases developer productivity by letting agents handle routine engineering tasks.

In short, in the five weeks to 27th October 2026, Okta, Satya Nadella, the Cloud Security Alliance and Salesforce each put the words “kill switch” or “emergency brake” next to AI agents, and the AI Kill Switch Act, introduced in the US House on 23rd July, would require the largest model providers to be able to throttle, suspend or shut their systems down on order. Every one of those switches stops something, and none of them stops the same thing.

TL;DR Managing Kafka consumer lag manually is time-consuming and error-prone. Today, we'll show you how to create a fully automated consumer lag monitoring agent in just 5 minutes using Aiven Managed Agents. This agent will monitor your Kafka services and send real-time alerts to Slack when consumer lag is high.

“Why aren’t my campaigns syncing to Salesforce?” “Your dashboard won’t load. Is something down?” When customers report a problem, your support team needs to understand whether it’s related to your product or a provider you depend on. Your AI support agent needs that context, too. By connecting StatusGator to Intercom through MCP, you can give Fin access to live status data and help it provide more useful answers during support conversations.

A tampered build of the Claude Code editor extension (anthropic.claude-code 2.1.313) was published on the Open VSX store used by Vs code,Cursor and similar editors, quietly gives attackers persistent remote access to any computer that runs it, while the extension keeps working normally. Researchers don’t yet know how it was published (the listing belongs to an Anthropic employee) or who is behind it. They found no evidence that Anthropic’s official Marketplace release was affected.

Running several coding agents at once is pretty straightforward. Give each a task, let them work independently, and you can make progress on multiple things at the same time. But the more agents you have working, the more changes you need to coordinate. Agents can edit overlapping code, make conflicting assumptions, or finish work that depends on changes another agent hasn’t completed.

Improving an AI agent means knowing which behaviors to change and where those changes will have the greatest impact. Insights in Datadog Agent Observability improves AI agents by analyzing agent traces to identify recurring cost and reliability problems. It then explains the causes of those problems, assesses their impact, and recommends fixes backed by evidence. At Datadog, we use Insights to improve the agent behind Insights.