InHacking AnalyticsbyJulien Kervizic·Jun 1Agentic FinOps: Why Traditional Observability Fails in the Age of AIThe Engineering Guide to LLM Observability: Workflows, Guardrails, and Unit Economics
InHacking AnalyticsbyJulien Kervizic·May 21The Trust Tragedy: How AI Inverts the Economics of the EnterpriseThe economics of synthetic abundance: Why local productivity gains are creating massive global externalities.
InHacking AnalyticsbyJulien Kervizic·May 18Gold chains and the road to Gas TownInference, Orchestration, and the Economics of Artificial Intelligence
InHacking AnalyticsbyJulien Kervizic·May 11Moving away from the Unit Test: Engineering in a Probabilistic WorldHow Machine Learning and GenAI are making it more complex to test applications
InHacking AnalyticsbyJulien Kervizic·May 6Agentic FinOps: Why AI Engineers Must Learn Cost DisciplineBuilding AI systems where quality, latency, and cost must coexist
InHacking AnalyticsbyJulien Kervizic·May 4The Return of Structure: Data Architecture Lessons for the Agentic WorkforceMoving Beyond Hallucinations: Building a Gold Standard for the Agentic Workforce
InHacking AnalyticsbyJulien Kervizic·Apr 30AI, Constraints, and the Future of Software EngineeringHow cost, infrastructure, and data constraints are reshaping the future of software engineering
InHacking AnalyticsbyJulien Kervizic·Dec 15, 2025Lessons learned from Speedrunning through the Cursor’s free trialProducing 100k lines of code in the span of 4 days
InHacking AnalyticsbyJulien Kervizic·Jul 24, 2025The Distinction between Data Engineering and Software Engineering RolesData Engineers are software engineers who work with data, right? Well, yes and no, the truth isn’t that simple. There are notable…
InHacking AnalyticsbyJulien Kervizic·May 28, 2022Taming the Kaniko beastKaniko brings about a lightweight way to build container images on Kubernetes— it may need however some taming before becoming usable.A response icon1A response icon1