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“When you get a demo and something works 90% of the time, that’s just the first nine.” — Andrej KarpathyThe “March of Nines” frames a common production reality: You can reach the first 90% reliability with a strong demo, and each additional nine often requires comparable engineering effort. For enterprise teams, the distance between “usually works” and “operates like dependable software” determines adoption.The compounding math behind the March of Nines“Every single nine is the same amount of work.” — Andre
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Presented by EdgeverveSmart, semi‑autonomous AI agents handling complex, real‑time business work is a compelling vision. But moving from impressive pilots to production‑grade impact requires more than clever prompts or proof‑of‑concept demos. It takes clear goals, data‑driven workflows, and an enterprise platform that balances autonomy, governance, observability, and flexibility with hard guardrails from day one. From pilots to the “operational grey zones”The next wave of value sits in the connective tissue Read more ›
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Presented by AWSAutonomous agents are compressing software delivery timelines from weeks to days. The enterprises that scale agents safely will be the ones that build using spec-driven development.There’s a moment in every technology shift where the early adopters stop being outliers and start being the baseline. We’re at that moment in software development, and most teams don’t realize it yet.A year ago, vibe coding went viral. Non-developers and junior developers... Read more ›
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The software industry is racing to write code with artificial intelligence. It is struggling, badly, to make sure that code holds up once it ships.A survey of 200 senior site-reliability and DevOps leaders at large enterprises across the United States, United Kingdom, and European Union paints a stark picture of the hidden costs embedded in the AI coding boom. According to Lightrun's 2026 State of AI-Powered Engineering Report, shared exclusively... Read more ›
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Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with unstructured content, sales figures alongside customer reviews or citation counts alongside academic papers, break single-turn RAG systems. New research from Databricks puts a number on that failure gap. The company's AI research team tested a multi-step agentic approach against state-of-the-art single-turn RAG baselines across nine enterprise knowledge tasks and reported gains... Read more ›
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17.04.2026 01:14
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