AI productivity is showing up in the data
Average throughput across all projects on CircleCI increased 59% YoY.
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Alert fatigue, AI triage, and incidents: Lessons from observability experts at Cyera, PlayHQ & NAB
Observability looks perfect in a slide deck – in practice, it's messier. In this panel, engineering leaders from Cyara, PlayHQ, and National Australia Bank share what really happened when they scaled observability: unexpected cloud bills, alert fatigue, a weekend database outage caught by an AI-assisted triage agent, and a vendor dispute settled by a single chart. They also cover moving beyond legacy tooling, using AI to close the PromQL skills gap, and what's next – from agentic SDLC integration to continuous profiling. Real stories, real numbers, real lessons.
Claude Code sped up the wrong part of your job
#claudecode #optimization #aicoding #observability
AI speeds up delivery. Here's how IT leaders manage the risk when AI-generated code hits production.
AI can accelerate speed to market, but for IT leaders it also raises a harder question: can you prove how an AI-generated change reached production? Chris Yates (SVP, Managing Director of Data & Architecture, Republic Bank) explains how his team builds a full evidence trail for every change, using version-controlled deployment tooling like Redgate Flyway Enterprise, so governance becomes a guardrail rather than a brake on speed.
Why AI Adoption Fails Without Operational Maturity First
Most MSPs are already experimenting with AI in some form, and every vendor at every conference has an AI for MSPs pitch ready. Few have stopped to check whether their own operations are solid enough to scale. Our 2026 IT Trends Report found that three-quarters of IT leaders believe they have an AI policy, while fewer than half of help desk staff agree. That’s the real risk: AI doesn’t fix drift, unclear ownership, or gaps between what’s documented and what’s actually happening.
Find Resilience Risks Automatically, Then Confirm Them | Harness Blog
Resilience Testing (RT) Agents scan your CD pipelines and Kubernetes workloads for resilience risk before it reaches production, then generate and run the chaos experiments or load tests needed to confirm it.
Build your own Bits Agent with Datadog Bits Agent Builder
Datadog Bits Agent Builder lets you build AI agents that use your observability data to automate operational tasks. In this walkthrough, see how to build an agent that analyzes monitor and alert activity, identifies patterns, and provides actionable recommendations to improve your monitoring strategy. With Bits Agent Builder, you can give agents access to Datadog data and tools, customize their instructions and models, and run them automatically to continuously analyze and act on your environment.
AI Red Team Agents Automate Attacks on your AI Agents. Runtime Policies Automate their Defense.
The AI red teaming market grew up fast this year. OpenAI bought Promptfoo, Cisco and Microsoft shipped automated attack suites, and a seed-stage startup publicly compromised 50 of 55 live customer service bots. These platforms find real problems at a scale no human team can match. But when you read the findings closely, a pattern emerges: agents talked into refunds, transfers, and data leaks they had standing authority to perform. Patching the prompt fixes one phrasing until the next model update.
Open Source Is Good Marketing
Summary: Jean-Jérôme Schmidt-Soisson, marketing lead at VictoriaMetrics, shows that open source and marketing are not opposites. Open source itself can be a powerful growth engine through trust, community, content, documentation, and discoverability. The article explains VictoriaMetrics’ pull-based marketing strategy, anchored in open-source values, to support adoption and business growth. This is our second article on the relationship between open source and marketing.
Built to amplify: how Lumen is rethinking teams and technology in the AI era by Greg Freeman | AIFNL
Last year, Lumen shared its AIOps roadmap. This year: two updates. First, how Lumen's thinking on AI-era org design has shifted — including why the instinct to cut junior headcount is a trap, and what sustainable team structures look like instead. Second, what Lumen built as a result: a single AI core (AskGreg) extended into a customer-facing email agent (NORA), a chatbot, and an in-progress voice agent — all leveraging the same modular platform. Live video demos show the system diagnosing network problems from alarm data and driving real-time network decisions. The closing thesis ties it together.