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All digests tagged Platform Engineering
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AI is making PRs bigger and more numerous, turning CI/Code Review into a bottleneck. Discover agentic validation: an automated system that reviews, autofixes, and auto-merges PRs, keeping your development velocity high.
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Scaling development with AI requires more than just generating code. Learn how automated code review, Jev classifiers, and robust CI/CD guardrails are essential to manage the flood of AI-generated PRs and maintain system reliability.
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Scaling automation requires shifting focus from fixing agent-produced code to improving the underlying system. Success depends on establishing centralized, reusable platforms and mandates for context authoring.
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The talk outlines how building robust AI agents requires moving beyond simple LLM calls. Key guardrails include whitelisting tools, using Knowledge Graphs over RAG, and enforcing structured citations.
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AI is revolutionizing drug discovery by building end-to-end platforms that accelerate R&D. Speakers discuss how LLMs and specialized models are compressing the 10–15 year timeline for drugs through 'zero shot' molecular design.
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Patrick Debois maps AI-native development maturity, outlining a progression of patterns (Prompting $\rightarrow$ Context $\rightarrow$ Harness $\rightarrow$ Loop) and emphasizing that organizational success requires platform enablement and measuring shared component contributions.
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Patrick Debois discusses scaling autonomous coding agents, arguing that success requires shifting focus from individual code fixes to improving the underlying system and platform architecture.
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Platform engineering must evolve to manage Generative AI. The key is building a robust 'harness'—a system of guides and sensors—to ensure consistency, mitigate vulnerabilities, and guide agents toward high-quality outcomes.
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