Coming soon · Agentic SRE community

Reliability needs
agents before incidents.

Agentic SRE is bigger than automated RCA. We are building a community around autonomous reliability engineering across the full lifecycle — understanding systems, verifying behavior, preventing failures, responding safely, and continuously learning.

Explore the vision
For SREs, platform engineers, researchers, builders and reliability leaders.
The holistic vision

From reactive automation to
autonomous reliability engineering.

Today's market often equates Agentic SRE with incident investigation. We see a much larger discipline: agents that reason about reliability continuously — before, during and after failure.

01

Understand

Build machine-readable models of services, dependencies, user journeys and operational intent.

02

Verify

Continuously test assumptions, resilience mechanisms and service behavior under failure.

03

Prevent

Identify dangerous changes, weak dependencies and failure modes before customers experience them.

04

Respond

Investigate incidents, reason over evidence and execute safe mitigations when production breaks.

05

Learn

Convert operational outcomes into reusable memory, stronger policies and better future decisions.

The goal is not an AI that explains why the system failed.
The goal is a system that continuously makes reliability knowable, testable and improvable.
Unique focus areas

Where we want the category to go next.

AgenticSRE.ai will focus on the hard, under-explored problems beyond generic log search and RCA copilots.

01 · System intelligence

Service & architecture understanding

Agents that infer topology, ownership, dependencies, user paths, invariants and operational boundaries from code, infrastructure, telemetry and documentation.

02 · Reliability science

Failure-mode discovery

Systematic generation and prioritization of realistic failure scenarios, including cascading, correlated, metastable and control-plane failures.

03 · Before production

Autonomous reliability verification

Agent-planned experiments that exercise service behavior, inject faults, evaluate outcomes and produce evidence before a release becomes an incident.

04 · Safe autonomy

Incident response & remediation

Evidence-driven investigation, hypothesis testing and mitigation — with explicit safety boundaries, approvals and measurable confidence.

05 · Evaluation

Benchmarks for SRE agents

Reproducible environments and scenarios to measure investigation quality, recovery effectiveness, safety, cost, latency and robustness.

06 · Continuous learning

Operational memory

Learning systems that turn incidents, experiments, runbooks and engineering decisions into persistent knowledge without blindly repeating history.

What we are building

A technical community, not another AI tool directory.

The community will connect practitioners, researchers and builders around concrete engineering evidence.

01Agentic SRE Landscape — map the technologies, architectures and emerging product categories.
02Open Benchmarks — evaluate agents against realistic reliability and incident scenarios.
03Reference Architectures — document patterns for agent harnesses, tool use, memory, safety and multi-agent coordination.
04Failure Knowledge — build shared taxonomies, case studies and reusable failure scenarios.
05Research & Engineering — connect academic work with the realities of operating distributed systems.
06Community Standards — develop clearer language for autonomy, evidence, safety and evaluation in SRE agents.