AI in Software Engineering - AI models have solved coding, but not software engineering, as production speed and tribal knowledge are key [4] - Building AI to accelerate production is challenging due to reliability requirements and the need for multi-agent orchestration [5][6][7] - Resolve AI focuses on using AI agents to troubleshoot alerts and incidents, acting as an AI site reliability engineer [11] - The company's AI agents can replace significant amounts of work, offering value exceeding coding agents [10] Resolve AI's Business and Technology - Resolve AI was founded to address the problem of increasing data and work for humans caused by existing observability tools [9] - Resolve AI's agents utilize human tools and understand production systems from code to backend databases [11] - Large enterprises are adopting Resolve AI's product in production with success, using it for "vibe debugging" beyond incidents and alerts [12] - Resolve AI differentiates itself by understanding the entire production system, not just code, and extracting knowledge unique to each company [13] Talent Acquisition and Future Vision - Resolve AI competes with major AI labs like Meta, OpenAI, and Anthropic for AI engineering talent [14] - Resolve AI attracts talent by offering the opportunity to have a significant impact on the company and the enterprise software engineering landscape [16] - The future of production engineering involves humans operating at a higher level of abstraction, with agents handling much of the underlying work [17]