Скачать или смотреть AI Agents for Prod: Full Stack Analysis

Engineering work doesn't happen inside individual tools. It happens between them.

Understanding how your service works means correlating code, infrastructure, runtime metrics, and security configurations. You have to synthesize all that information yourself. That's where Resolve's AI agents for Prod can actually add value for software engineering.

This video walks through a real example of Resolve investigating across an entire production stack. We start with a simple question about a Kafka cluster and progressively add complexity: checking infrastructure allocation, analyzing 12 hours of service health metrics, and auditing security risks.

Watch how Resolve moves from simple code search to correlating four different systems: code architecture, infrastructure constraints, runtime behavior, and security implications.

This is what AI agents for production systems should look like: a partner in your workflows that investigates across your entire stack and synthesizes findings automatically.

What You'll See in this Video:
Code search with evidence and data flow diagrams
Infrastructure correlation (memory limits, replicas, pod allocation)
Runtime health analysis across services (Grafana metrics and dashboards)
Security audit with prioritized risks and business impact
How AI agents handle engineering workflows, not just individual tasks

Timestamps:
0:00 How AI Has Evolved for Engineering
0:35 The Problem: Work Happens Between Tools
1:00 What AI Agents Should Do
1:27 Real Example Using Resolve AI
3:36 The Real Value of AI Agents

This demo uses Resolve AI to show how production-ready AI agents investigate across code, infrastructure, observability, and security in parallel.

At Resolve AI, we're building agents for software engineering and SRE that fundamentally change the way you and your team operate in production and handle incidents.

Learn more about Resolve AI at https://resolve.ai and stay up to date:
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