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<div style="display: none; max-height: 0px; overflow: hidden;">With core context engineering principles and frequent intentional compaction, current AI models can be great at handling large, detailed codebases </div>
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<h1><strong> TLDR Web Dev <span id="date">2025-09-24</span></strong></h1>
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<strong>Getting AI to Work in Complex Codebases (20 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
With core context engineering principles and frequent intentional compaction, current AI models can be great at handling large, detailed codebases. AI can rarely produce correct code in one shot in large code bases, so it needs steps before implementation to do research on the codebase and plan its steps.
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The "thundering herd" problem occurs when a cache miss leads to a large number of concurrent requests hitting the database for the same record, overwhelming it. There are two solutions: using a distributed lock to allow only one request to access the database, or using in-process synchronization with (as an example) Java's `CompletableFuture` and `ConcurrentHashMap`. While the distributed lock works across multiple nodes, the in-process synchronization avoids network calls but doesn't coordinate across nodes.
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<strong>How Infobip's Infrastructure Team Handled 10 Billion Messages in a Day (7 minute read)</strong>
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Infobip's infrastructure team handles 10 billion messages daily. They overcame issues like email overloads, data center failures, and scaling for WhatsApp Business by using cloud solutions, re-architecting systems, and adopting Kubernetes. A critical decommissioning mistake in 2024 led to the implementation of delayed destructive actions, preventing data loss.
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<strong>I tried HTMX, then ditched it (16 minute read)</strong>
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Serving appropriately sized images for different screen sizes avoids wasting bandwidth and compute power. This can be done by using the `srcset` and `sizes` attributes on the `img` tag to specify multiple image sources and their intended widths based on viewport size.
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Devs should test their websites without JavaScript enabled to check accessibility and resilience. JavaScript can fail due to slow networks, browser extensions, or user settings, so sites should use progressive enhancement, starting with semantic HTML that works without JS and adding JavaScript features as enhancements.
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TanStack Start has reached its v1.0 Release Candidate. This version includes type-safe routing, server-first functions, built-in streaming, and URL-as-state primitives, all while offering flexibility for both SPA and SSR architectures.
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The AI Data Generator helps users generate sample data with various input parameters, export it in various formats, and explore it within Metabase.
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