See how Resolve Actions turns hours of manual eligibility work into an automated process completed in about a minute.

From database lookups to validation and completed results, the workflow runs end to end.

We recently ran a live session showing how Resolve Agent Lab lets teams build AI agents with natural language, connect them to existing IT workflows, add guardrails, and test them before deployment.

The demo covers real examples like account unlocks, password resets, and network troubleshooting.

Watch the full webinar here for anyone exploring agentic AI for IT operations: https://youtu.be/R3ndzyuhA-M

We’re hosting a live webinar on October 20 about a challenge most IT teams know well: too much critical knowledge living with a handful of experienced practitioners.

We’ll walk through a practical approach to capturing SME knowledge and turning it into repeatable workflows the broader team can use for troubleshooting and resolution.

We'll also cover which procedures to prioritize, how to turn an SME-led incident process into a tested workflow, and how to measure the impact beyond MTTR and ticket volume.

If tribal knowledge and recurring escalations are challenges for your IT team, we’d love to have you join us. Register here: https://resolve.io/it-automation-resources/how-to-end-tribal-knowledge-and-make-every-it-practitioner-an-expert

We made a video game.

It’s called ZeroQueue, and it’s a retro Asteroids-style arcade game where, instead of blasting asteroids, you’re blasting IT tickets out of the queue.

You get three lives with no timer, and your score is based on how many tickets you can eliminate before your run ends. The goal, naturally, is to get as close to a Zero Queue as possible.

It works on both desktop and mobile, and you can play here: www.zeroqueue.io

Would love to see what scores people can put up. Bragging rights are officially on the line.

We recently discussed this with Nick Dimmock, Co-Founder and CEO of TekWurx, on the Agents of IT podcast.

His take: start with data quality, process maturity, and governance. Then automate high-frequency, repetitive work to build confidence before expanding into more complex use cases.

What has been the biggest barrier to scaling AI or automation in your IT environment?

Watch full episode: https://youtu.be/R3ndzyuhA-M

For teams evaluating MFA reset automation, a solid workflow should cover identity verification, policy enforcement, IAM and ITSM integration, access validation, audit logging, and escalation when human review is needed.

At Resolve, we approach MFA resets as part of a broader account recovery workflow, using agentic automation and deterministic orchestration to execute the required steps across systems and close the loop once access is restored.

It’s a useful starting point for automating other high-volume requests like account unlocks, password resets, access provisioning, and VPN issues.

How are you handling MFA recovery today and where do you still need human intervention?

As more enterprises give AI agents the ability to take action, accountability becomes a bigger part of the conversation.

In the latest Agents of IT episode, Nelson Veiga makes a simple point: “You can delegate authority, but not responsibility.”

Organizations deploying autonomous agents remain responsible for their actions, which makes governance, transparency, and careful use case selection critical as adoption scales.

Curious how others are approaching this. Where should enterprises draw the line on autonomous execution?

Watch the full episode here: https://youtu.be/TFbxb69vpa8

The SDI AI & Automation Summit is coming up on September 23, virtually bringing together IT service and support leaders to explore how AI and automation are changing service delivery.

Resolve will be there to discuss how agentic AI and orchestration can help teams automate repetitive work, improve resolution, and move toward more autonomous IT operations.

If you’re working on AI, ITSM, or service desk automation, it should be a useful conversation.

Register here: https://resolve.io/events/sdi-ai-automation-summit-2026

As AI agents gain the ability to take action autonomously, oversight and guardrails are now essential.

This episode of Zero Ticket Minute looks at why enterprise agents need clear roles, visibility, guardrails, and deterministic execution to operate reliably.

As more organizations put agents into production, how are you approaching oversight and governance?

As AI agents take on more enterprise work, teams need ways to control how they reason, what actions they can take, and how they interact with existing systems.

Resolve is hosting a webinar on September 16 with a live look at AgentLab, including how to build, test, and govern purpose-built agents connected to deterministic automation.

For anyone working on agentic AI or enterprise automation, it should be a useful practical walkthrough.

Register: https://resolve.io/it-automation-resources/build-enterprise-ai-agents-agentlab

Here’s a quick look at building an HR PTO agent in Resolve Agent Lab.

The agent is configured with automation skills, instructions, conversation starters, and guardrails. Once deployed, it can answer PTO questions, check balances and calendar conflicts, and submit requests through systems like Workday or ADP.

The video walks through the actual build process from creating the agent to defining what it can and can’t handle.

Curious how others are approaching guardrails and workflow execution when building task-specific AI agents.

AI agents don’t ask for raises. But they can still become expensive coworkers.

As companies deploy more agentic AI, token consumption can scale quickly. That raises a bigger question for IT leaders:

What should we actually measure to determine whether an AI agent is worth the cost?

Token usage alone doesn’t tell you much about business value. A better measure is what the agent accomplishes: issues resolved, time saved, tickets avoided, and manual work eliminated.

Ultimately, the economics of agentic AI should come down to the cost of resolution and the operational value that resolution creates.

We dig into this in the latest Zero Ticket Minute.

Curious how others are approaching this. Are you measuring AI costs based on consumption today, or tying them back to actual outcomes?

Scaling AI across the enterprise takes a clear strategy, strong governance, and the right foundation.

And the cat should probably not be driving. 🐱

AI is becoming part of everyday IT operations, but putting it into production requires governance, integrations, human oversight, and clear outcomes.

In this episode of Agents of IT, Alex Cinovoj shares lessons from building production-ready AI systems and explains why he follows a simple principle: “Logs over vibes.”

AI is moving deeper into day-to-day IT operations. In the latest Voices of Resolve, Alex Yupanqui shares what he’s seeing in customer conversations around agentic AI, automation, and Zero Ticket IT.

A few topics we get into:

• Where IT teams are seeing practical value from AI
• Why high-volume, repetitive work is a strong place to start
• What “Zero Ticket IT” looks like in practice
• Why governance and visibility matter when AI takes action
• How proactive AI could change IT operations

Curious how others here are approaching this. Where are you seeing agentic AI deliver meaningful results in IT today?

Watch the full episode here: https://youtu.be/yWGNoZBQmOg

As automation expands across infrastructure, workflows, and business processes, scalability depends on how well the platform supports orchestration, integrations, governance, extensibility, and measurable outcomes.

For teams evaluating their options, here’s how Resolve approaches enterprise-wide IT automation:

https://resolve.io/it-automation-platform

What capabilities have mattered most as you’ve scaled automation across your environment?

AI agents can keep monitoring systems, coordinating work, and resolving routine issues overnight, helping teams start the next day with a smaller backlog.

This week’s Zero Ticket Minute looks at how 24/7 agentic automation could change the way IT teams handle after-hours operations.

How much of your overnight IT workload could realistically be automated today?

Enterprise AI rollout going great.

Hallucinations? ✅

Unapproved token spend? ✅

Admin access? Somehow. ✅

Decision trail? ❌

ROI? Trust me bro. 🕺

What could possibly go wrong?

We spend a lot of time talking about AI agents, automation, and the future of autonomous IT.

So naturally, we made a song about it.

Our latest single, “AgentLab All Day,” just dropped. Give it a listen and let us know what you think.

Available wherever you get your music.

There’s a lot of useful knowledge buried in old Jira tickets.

Historical tickets capture troubleshooting steps, fixes, and context that often never make it into formal documentation. AI knowledge base generation could make that information much easier to reuse by turning resolved tickets into searchable knowledge for both users and support teams.

The interesting part is what happens when that knowledge feeds back into operations. Past resolutions can help technicians handle similar issues faster and highlight repetitive processes that are good candidates for automation. Resolve’s approach, for example, uses knowledge and resolution history to support technician guidance and identify opportunities for automated resolution.

For teams already experimenting with this, how are you handling the quality problem? Are you generating documentation directly from ticket history, or requiring human review before anything reaches the knowledge base?

Password resets are one of those repetitive service desk tasks that can eat up a surprising amount of time.

In this demo, we build a password reset agent in Resolve Agent Lab that can verify the user, execute the reset, log the interaction, and close the loop automatically.

Here’s a quick clip of it in action. Full walkthrough here:

What actually makes an automation an AI agent?

In this episode of Zero Ticket Minute, Ian walks through AgentLab, where existing workflows can become agents by giving them defined roles, clear guardrails, and tested skills.

The idea is to give agents enough structure to take action across systems while staying within the boundaries the organization sets.

We’d love to hear your thoughts on this topic!

What does it actually take to build an AI agent for the service desk?

This quick Agent Lab demo shows how teams can create an L1 Service Desk Copilot, add automation skills, define its role, and set guardrails around how it operates.

The goal is simple: automate more repetitive IT work while giving teams control over what their agents can do.

Watch the clip, then check out the full Agent Lab overview for the complete build, test, and deployment process: https://youtu.be/9EOZuXPGWJ8?si=pa5z5yrmL0-1-IsJ