5 min read
AI handles incidents, engineers lose touch with their systems
AI-assisted incident response can lower MTTR while leaving engineers less prepared for the complex incidents automation cannot solve.
Topic
Incident Management
My writing, talks, podcasts, and projects about Incident Management.
Writing on this site
Selected work
Article
The New Stack
LLMs Broke the SRE Runbook. Now What?
AI-generated code is outpacing traditional runbooks. How SRE teams are adapting their incident response playbooks for the LLM era.
Talk
SREcon EMEA 2025
From Vibes to Outages: Riding the AI Code Wave
AI-assisted coding is exploding — but acceleration doesn't mean reliability. Real examples of hard-to-trace LLM bugs, hallucinated dependencies, and operational fallout for lean SRE teams.
Article
LeadDev
Is AI-assisted coding an incident magnet?
AI-generated code ships faster but introduces subtle bugs that are harder to trace. What engineering leaders need to know about the reliability trade-offs.
Podcast
Engineering Futures
AI Fails Like We Do
Sylvain Kalache went looking for the new ways AI breaks software. Every one turned out to be a habit we've had for years.
Podcast
Humans of Reliability
Nir Soudry — Head of R&D at 7AI
AI vs. AI — how autonomous attackers are scaling phishing and malware, how defenders can use agents to cut alert noise, and where accountability belongs when AI investigates and remediates incidents.
Talk
Incident Fest 2026
More Code, More Incidents? Staying Reliable When AI Writes the Code
Speaking on the Incident Fest Main Stage about staying reliable as AI-assisted development increases the rate at which software is created.
Podcast
Humans of Reliability
Eran Kampf — VP of Engineering at Twingate
Why Twingate stopped shipping features to rebuild reliability — from active-active multi-region architecture and smaller blast radiuses to preserving human ownership as agentic coding accelerates delivery.
Talk
AIOps Summit 2026
AIOps Summit
Meta-hosted summit in Menlo Park focused on applying AI, LLMs, and agents to software incidents and response.
Podcast
Humans of Reliability
Hamed Silatani — Co-Founder and CEO at Uptime Labs
Every pilot trains for engine failure, but most engineers face their first major incident unprepared — why communication, coordination, and decision-making need deliberate simulation practice.
Talk
DevOpsDays Austin 2026
The Science of On-Call Burnout: Why "How Are You Doing?" Always Gets "Fine"
Why traditional burnout detection fails in engineering teams. Connecting Maslach's burnout research and the Copenhagen Burnout Inventory to observable on-call metrics, and demonstrating that observed data outperforms subjective self-reporting.
Podcast
Humans of Reliability
Gandhi Kumar — Principal Incident Commander at Twilio
The golden hour — why the first 15 minutes of an incident decide everything, from mitigation strategy to customer trust, and why human psychology matters more than tools.
Podcast
Humans of Reliability
Cliff Snyder — Senior SRE at Multimedia LLC
From 600 to 6,000 — an 18-month transformation replacing legacy tooling with a purpose-built incident management platform, scaling operational responsibility from 600 SREs to 6,000 engineers across the org.
Podcast
Reliability Rebels
Reliability Rebels Podcast — Guest Appearance
Reliability Rebels Guest appearance to discuss reliability engineering, AI, and modern incident response.
Podcast
The Rollback Café
How AI is Changing Incident Response (SRE Deep Dive)
From faster detection to smarter debugging — where AI delivers practical value in incident response, its limitations in production environments, and how teams can integrate AI while maintaining reliability standards.
Talk
Conf42 Site Reliability Engineering 2026
From Vibes to Outages: When AI Writes the Code You Debug
LLM-assisted development introduces hard-to-trace bugs, AI-generated tests that mirror flawed logic, and hallucinated dependencies. Exploring operational consequences and actionable strategies from AI-powered incident tools to incident vibing.
Podcast
Humans of Reliability
Will Wilson — CEO at Antithesis
The incident you never had — deterministic simulation testing, why conventional testing misses bugs that cause real outages, and how simulation-based approaches improve software reliability.
Talk
Google SRE NYC Tech Talks
Google SRE NYC Tech Talk — On-Call Health
The science behind responder overload and introducing On-Call Health, an open-source tool for detecting incident responder fatigue. At Google NYC Pier 57.
Podcast
Humans of Reliability
Stephen Townshend — SRE Team Lead at isDown
Burnout doesn't ask permission — the physiology of burnout from an incident responder's perspective, warning signs, recovery, and the systemic changes the industry must make.
Talk
OpenClaw Demo Night
OpenClaw Demo Night w/ Rootly AI, Convex, Sentry & DigitalOcean
An evening of AI demos and networking in Toronto — presenting Rootly AI alongside teams from Sentry, Red Brick Labs, Convex, and DigitalOcean.
Podcast
Humans of Reliability
Dileshni Jayasinghe — VP of Technology at commonsku
Democratizing reliability — empowering non-engineers with operational power, incident management as a muscle, and AI-powered postmortems.
Panel Moderation
Rootly AI Labs
MCPs and the Next Wave of Reliability w/ Rootly AI, WorkOS, Block, Microsoft & Groq
Panel at the AWS GenAI Loft in San Francisco on MCPs, incident automation, observability, and generative AI tooling for reliability.
Talk
AI Security Demo Night
AI Security Demo Night w/ Rootly AI, Okta, Panther, Tailscale & More
Live demos at Okta HQ in San Francisco — presenting Rootly AI alongside cybersecurity startups tackling identity, endpoint security, and threat response.
Podcast
Techstrong TV
Exploring AI's Role in Incident Management
Interview with Alan Shimel at PlatformCon NYC 2025 on how AI applies to incident management and reliability engineering — triage, root cause analysis, and why AI enhances rather than replaces engineers.
Panel Moderation
Rootly
Rootly Roundtable: From Weak Signals to Confident Fixes
Invite-only roundtable on filtering alert noise, enriching alerts with automated ownership context, and streamlining bug validation workflows.
Panel Moderation
Rootly
Rootly Roundtable: Centralized vs. Distributed Incident Teams
Invite-only roundtable comparing centralized specialist responders with distributed on-call models — which strategy works for your org.
Podcast
Adventures in DevOps
Incident Vibing: The Self-Healing System
Tracing the arc from ingesting logs at LinkedIn/SlideShare to LLM-driven RCA today. How fine-tuning, MCP, and incident vibing are reshaping SRE.
Article
The New Stack
Vibe Coding Is Here — But Are You Ready for Incident Vibing?
If developers are vibe coding, SREs are now incident vibing. What happens when AI-generated code meets production reality.
Podcast
Humans of Reliability
Dan Slimmon — Incident Response Trainer
Training teams for incident response — chaos engineering, game days, and building organizational muscle memory.
Panel Moderation
Rootly
Rootly Roundtable: The State of AI in Incident Management
Invite-only roundtable examining AI's role in incident response — separating practical applications from hype with industry leaders.
Project
GitHub
Rootly-MCP-server
An MCP server for Rootly — enabling AI agents to interact with incident management workflows via the Model Context Protocol.
39
Podcast
Humans of Reliability
Sean Goedecke — Staff Software Engineer at GitHub
Reliability at GitHub scale — incident management, deployment practices, and engineering culture.
Project
GitHub
SRE-skills-bench
A benchmark suite for evaluating AI agents on real-world SRE tasks — incident diagnosis, runbook execution, and infrastructure troubleshooting.
12
Project
GitHub
On-Call-Health
Detects early warning signs of on-call engineer burnout by pulling data from Rootly, PagerDuty, Linear, GitHub, and Slack.
32
Talk
DevOpsDays Austin
AI-Driven Incident Resolution — Hype or Reality
A grounded look at what LLMs can and can't do in an incident response workflow today, drawn from real production experiments at Rootly AI Labs.
Article
Linux.com
How DevOps Failed 60K Users
A postmortem on a DevOps failure that affected 60,000 users — lessons in monitoring gaps, deployment practices, and incident response.