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Solving AI Latency and Cost Problems with Valkey - Aiven Webinar

LLM providers charge you for caching, and they do it on their terms. You can run it yourself for a fraction of the cost. In this Aiven webinar, Jay Miller (Staff Developer Advocate) shows how to use semantic caching and semantic routing on Valkey to cut prompt costs + latency. You'll see a working demo, "Template Scout", that searches GitHub for deployable repos and picks the cheapest model that can answer each question.

Seer Agent: Get Answers. Take Action.

This video walks through what it looks like to treat Sentry's Seer agent the way you already treat a chatbot, asking it plain language questions about your own production application. From Slack or inside your Sentry account, Seer Agent can answer questions with real context: the affected spans, the recent release, the likely cause. Seer doesn't stop at answering questions. Ask it to act on what it just told you and it completes that work inside Sentry, serving as an assistant to your projects, team workflows, and your future self.

Governing AI Agents From the Inside: What We Learned Building AgentIQ

When every employee is building AI agents, seeing what they did afterward isn't enough. AgentIQ's in-flow governance runs inside the agent's execution flow—pausing for human approval, enforcing policies by value, masking PII, and stopping runaway agents before costs spiral.

The 5 levels of the AI software factory for enterprises | EVOLVE 2026 keynote

Everyone online seems to have a fully autonomous SDLC. Most enterprises are still at level 3, and they'll be there for years. In the EVOLVE 2026 opening keynote, Cortex co-founders Anish Dhar (CEO) and Ganesh Datta (CTO) lay out a practical maturity model for getting from AI coding agents to an AI software factory without blowing up cost, quality, or security along the way. They've watched hundreds of engineering orgs adopt AI over the last two years. This talk distills what separated the successful rollouts from the chaotic ones.

AI Investigation for ITOps: Faster Root Cause with Edwin AI

AI investigation for IT operations finds the likely root cause of an incident and shows the evidence behind it. This video covers how deep AI investigation works for ITOps, SRE, and platform engineering teams using LogicMonitor's Edwin AI. Engineers lose time stitching together alerts, logs, and recent changes after an alert fires. Deep AI investigation hands that first pass to AI agents, so your team starts closer to the fix. Edwin AI, LogicMonitor's AI agent for ITOps, correlates alerts, identifies root causes, and recommends remediation.

Why AI development creates a reliability blind spot for humans, and what to do about it

Application development and operations teams are adopting AI coding tools at an exponentially increasing rate, from a rounding error of 6% of code output by AI in 2023, to as much as 51%-75% for a majority of enterprises. Agents are making pull requests (PRs) faster than human developers could have ever dreamed. As features are pushed to market faster, there’s a sharp increase in production incidents, with 80% of development shops specifically tracing production outages to AI.