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All digests tagged GitHub Copilot
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AI agents have made writing code nearly free, shifting the bottleneck from coding to defining the problem. The future of engineering lies in the Product Engineer role: figuring out what 'good' means.
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Learn how to scale custom AI agents from local development to autonomous CI pipelines. Discover agentic workflows, marketplaces, and cross-repo automation using GitHub Copilot.
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Adam Cogan explores the shift from Copilot hype to agentic AI workflows. Learn how agents are reshaping the enterprise stack, improving security, and changing the developer's role from coder to prompt engineer.
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AI companies are accidentally building banks. Scaling AI requires moving beyond simple usage billing to complex financial infrastructure that checks entitlements synchronously before consumption.
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To manage AI spend, tag every resource and move beyond total cost. Focus on efficiency metrics like 'cost per thought,' 'reasoning ratio,' and 'cache hit rate' to truly understand AI ROI.
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The rise of AI agents has created a bottleneck: developers write 741% more code, but only ship 30% more software. The solution is moving review from line-by-line inspection to building automated, scalable review harnesses.
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Learn how LinkedIn scaled AI agents to thousands of tools and playbooks using a Search/Get Schema/Execute meta-tool layer, enabling reliable, context-aware automation.
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The rise of AI agents is flooding open-source projects with 'slop'—low-quality, unvetted code. Maintainers must implement new guardrails like requiring issues first and using automated systems to manage contributions.
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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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