Operations | Monitoring | ITSM | DevOps | Cloud

How Long Does Deep Research Take? We Timed 5 Tasks With & Without AI

How long does deep research take? That's a million dollar kind question if you've ever lost a weekend to digging through sources for a report. You already know the pain of hours of searching, reading, and synthesizing, only to wonder if you missed something crucial. We gathered experiment data comparing traditional research methods against modern AI tools across five common professional tasks. The exact time savings we measured might surprise you, and they reveal how AI is quietly redefining what it means to be a deep researcher.

How Developers Build a Meaningful Career in the Age of AI

What does a meaningful developer career look like in the age of AI? We brought together four experts to answer exactly that. In this GitKon panel, GitKraken CMO Kate Adams moderates a conversation with Leon Noel (Managing Director of Engineering, Resilient Coders), Danny Thompson (Director of Technology and host of The Programming Podcast), Maggie Hunter (Recruitment Lead, GitKraken), and Dimitry Fonarev (CEO, Testkube) to explore how software engineers can future-proof their careers, grow their skills, and navigate an industry that is changing fast.

Why Generic AI Fails in Ops: What Trustworthy Actually Requires

Enterprise operations reached a point where complexity outpaced human interpretation and outgrew the capabilities of generic AI. As environments became more distributed and interdependent, every incident, anomaly, and degradation produced ripple effects across systems that require context, lineage, and reasoning. Yet most AI models were not built for this reality. They were trained for general knowledge tasks, not the deeply connected operational truths that define enterprise performance.

How to Reduce MTTR with AI-Powered Runtime Diagnosis

Reducing Mean Time to Resolution (MTTR) in production systems requires understanding failure behavior in real time. While AI code agents significantly accelerated software development and deployment, incident resolution has remained constrained by incomplete pre-captured telemetry. AI SRE tools improve signal correlation, but MTTR reduction requires runtime-verified diagnosis that confirms execution behavior directly in production systems.

Evaluating Observability Tools for the AI Era

Every observability vendor has an AI story right now. Most have an MCP. Many have a chatbot. All have a demo where the AI finds the root cause of an incident in thirty seconds and everyone in the room nods. In the context of a public demo, these tools look almost identical. Ask the AI a question, the tool returns an answer, and the engineer fixes the bug. Impressive. But if you buy based on the demo, you may end up with an AI layer that looks great on a call and disappoints in production.