Your AI agents are lost: give them a graph

Bigger models cannot fix missing context. The real advantage may belong to teams that teach agents where to look, what to remember, and when to learn.

AI vs. AI: From Alert Fatigue to Agentic Cybersecurity

AI is making cyberattacks faster, smarter, and more autonomous. Nir Soudry explains how defenders can fight back with agents of their own.

We Stopped Shipping Features for a Quarter — Here's Why It Saved Us

When incidents pile up fast enough, every part of the company bleeds: support is fielding angry customers, AEs are on apology calls, and engineering is burning cycles on retrospectives instead of shipping. For Eran Kampf, VP of Engineering at Twingate and co-founder of Monday.com, that was the moment he made a call most engineering leaders won't: stop all feature work for a quarter and fix reliability.

"Hey Claude, where's my database?": How an AI agent nuked production

Alexey Grigorev teaches Terraform in his courses. That didn't stop an AI agent from running terraform destroy against his live production database. He walks through the outage with unusual candor, refuses to blame the AI, and explains the guardrails and trade-offs that separate moving fast from losing everything.

Every pilot is ready for engine failure: are your engineers?

Every pilot who's never had an engine failure is still ready for one. The same can't be said for most software engineers facing their first major incident. How can we bridge that gap?

LLM Observability: Lessons From MLOps

For nine years, Maria was shouting about monitoring. Nobody cared too much, until LLMs arrived.

The golden hour: Why the first 15 minutes of an incident decide everything

From 600 to 6,000: Federating incident response across an engineering org

AI didn't change the game, it just exposed your bottlenecks

Fear, identity and flaky tests: AI in reliability

The incident you never had: Deterministic simulations

Burnout doesn't ask permission: Recognizing, recovering, and rebuilding

Code is cheap, reliability isn’t: Owning production in the AI era

Democratizing reliability: Empowering non-devs

99%+ accuracy on a moving target: Model deprecation and reliability

The reality of GenAI in production

It’s never different this time: LLM reliability without the hype

You can’t fix what you don’t mneasure: Observability in the age of AI

The end of “good code”? AI, throughput, and reliability

Frontline reliability: Protecting user journeys with SLOs

Balancing reliability at the crypto-finance frontier

Command under pressure: Incident leadership and human-centered reliability

AI at the frontlines of healthcare reliability

Trust is the product: Building reliable billing in the AI era

The Golden Path to Nowhere: When Platforms Undermine Reliability

AI can boost developer productivity, if used right

Why reliability in the AI era starts

Metrics that matter: Measuring developer productivity in the AI era

Are AI and platforms making SRE obsolete?

Scientific Incident Management

How AI broke serverless and what to do about it

I want my shoes fast! Observability, SRE burnout, and OTel

AI in production

The domino effect of outages

Five questions with Tristan Watson

Five questions with Matt Gowie

Five questions with Adama

Five questions with Tony

Five questions with Stefan

Five questions with Chris

Five questions with Kolton

Five questions with Mason

Five questions with Ricardo

Five questions with Krishna

Five questions with Dennis

Five questions with Nathen

Five questions with Zameel

Five questions with Jessica

Five questions with Reggie

Five questions with Sebastian

Five questions with Dinesh

Five questions with Sal

Five questions with Hazel

Five questions with Colin

The reliability diagnosis: Debugging and incident response

Five questions with Hannah

Five questions with Gastón