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startuphub.ai/startups/anthropicLive

Anthropic

Claimed·aDR 90·eDR 82·Agent 57·Speed 61

Anthropic is an AI safety and research public benefit corporation building reliable, interpretable, and steerable AI systems, best known for the Claude series of advanced AI models.

Last updated Nov 6, 2026

2021Active19San Francisco, United States

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OverviewProducts149

About

Anthropic is an American artificial intelligence public benefit corporation dedicated to AI research and products that prioritize safety, aiming to secure the benefits of AI while mitigating its risks. Its flagship product is Claude, a series of proprietary large language models (LLMs) including Opus, Sonnet, and Haiku, designed for various applications from summarization to code assistance and enterprise use.

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The Agents Were Fine. Everything Around Them Broke. - Joey Wang, Harvey

Harvey agents worked but its infra failed

Joey Wang detailed 10,000 agent-written PRs inside Harvey in a talk carried by AI Engineer . The affected system was Spectre, Harvey's internal cloud agent platform, Wang said. No outside attacker was needed to break it.

Harvey first described Spectre back in April as a harness that becomes the product, Wang said. The program listing adds context the talk skips: Harvey released its cloud agent platform to its own engineers before it shipped long-horizon agents to lawyers. Engineers kept their favorite tools under one rule, that "If a person can click it, an agent can call it."

In May only one Spectre task came from the terminal, Wang said. By October the command line started about 6,500 tasks a month, Wang said. Last month more than one agent started every minute and about 460 people used the platform, Wang said.

Mid-August broke the queue when one buggy release fired hundreds of alerts into one Slack channel, Wang said. About 50 tasks was normal for a day, but about 900 tasks started in four hours, Wang said. A repeat alert now joins the open investigation, Wang said. A later burst of about 950 tasks in three hours forced a fair-share queue, Wang said.

That queue gives keyboard users priority and shows a place in line, Wang said. A 300-task test cut scheduling from almost 2 seconds to 70 milliseconds, Wang said. About 110 people ran scheduled automations last month, Wang said, with auto-off after five straight failures. At the end of October PRs jumped about 60% in a single month and merges stretched from 15 to 30 minutes to over an hour, Wang said. On November 4 v

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