{
  "id": 13688343,
  "title": "Foresight AI Brings Gremlin Agents to Reliability Engineering",
  "url": "https://urgent.news/2026/10/11/foresight-ai-brings-gremlin-agents-to-reliability-engineering",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-11T09:00:00.000Z",
  "source": {
    "name": "InfoQ",
    "slug": "infoq",
    "url": "https://www.infoq.com/news/2026/10/gremlin-foresight-ai/"
  },
  "original_language": "en",
  "account": "Reliability management firm Gremlin has launched Foresight AI, an agentic solution to help assess services for potential failures, suggest improvements, and verify that fixes maintain effectiveness. The platform operates as an add-on to Gremlin's existing infrastructure, enabling teams to execute pre-planned tests, limit the impact of failures, and employ automated testing to confirm that fixes remain effective over time.\n\nUsing reliability scores, organizations can measure their progress and prioritize investments in resilience. Foresight AI aims to provide reliability checks without requiring every developer to become an expert in distributed systems. According to Gremlin's CEO and co-founder, Kolton Andrus, the product addresses the issue of faster AI-assisted software delivery, where more code reaches production without close human review.\n\nForesight AI divides tasks among four specialized agents: an Analyst gathers service data and recommends tests; a Tester schedules and executes them; an Operator interprets failed tests and proposes remediations; and a Technical Program Manager tracks test coverage, reliability risks, and commitments across teams. The latter can generate weekly reports and share updates via Slack.\n\nThe product utilizes Gremlin's proprietary Failure Atlas, a record containing millions of fault-injection experiments conducted over ten years across thousands of distributed systems. Gremlin clarifies that system data does not train large language models; instead, agents use platform data and the Failure Atlas for decision-making, with an LLM used for searching, summarizing, and explaining results.\n\nWhat sets Foresight AI apart is its closed validation loop. When a test uncovers a weakness, the service first proposes a change and then runs the original test again to confirm the fix works. This ensures that no test or remediation occurs without approval, keeping engineers responsible for changes while automating much of the analysis and repetition involved.\n\nForesight AI also generates reports and dashboards from natural-language requests, creating charts, tables, tabs, and links to illustrate changes in reliability scores and the risks teams have addressed. This addresses a common challenge for reliability teams: avoided incidents do not produce the same visible evidence as outages.\n\nWhile Foresight AI automates many aspects of reliability engineering, Gremlin emphasizes that organizations must still decide which risks are acceptable and whether proposed changes should proceed. Analyst Jason English from Intellyx argues that observability and AI-based SRE products are largely reactive, relying on telemetry from problems that have already occurred. He advocates for fault injection, which creates controlled failure conditions before incidents and records how services respond, providing a more proactive approach.\n\nDespite Gremlin's claims of a supervised model with human oversight, some experts caution that automation may create new systems that reliability engineers must evaluate. Engineer Sandip Bhattacharya points out that organizations still need specialists to configure agents, assess their behavior through metrics, and adjust them as models and infrastructure change. Gremlin's Foresight AI, however, follows a successful beta period, demonstrating its capability to identify and address reliability risks before incidents occur. The product is now available for general use.",
  "summary": "Reliability management company Gremlin has announced the general availability of Foresight AI, an agentic product that analyses services for potential failures, recommends changes and reruns tests to check that a fix works. By Matt Saunders",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}