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<h1><strong> TLDR Dev <span id="date">2025-12-08</span></strong></h1>
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<strong>Goodbye low test coverage and slow QA cycles (Sponsor)</strong>
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Bugs sneak out when less than 80% of user flows are tested before shipping. However, getting that kind of coverage (and staying there) is hard and pricey for any team.<p></p><p><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.qawolf.com%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=ACQ_All_Demo_Conversions__NewsletterAudience_-_Newsletter_GoodbyeLowTestCoverage_20251208-None_Experiment-FALSE%26utm_term=body-QAWolf%26utm_content=GoodbyeLowTestCoverage_ScheduleADemoToLearnMore_None_Headline%253AGoodbyeLowTestCoverageAndSlowQACycles____Newsletter-PrimaryPlacement_20251208_v1_/1/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/tEYlfntic7w618tfNtj5_d-4ULH4FOp54praw6u19Vk=434" rel="noopener noreferrer nofollow" target="_blank"><span>QA Wolf's</span></a> AI-native solution provides high-volume, high-speed test coverage for web and mobile apps, reducing your organization's QA cycle to minutes. </p>
<p>They can get you:</p>
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<li><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.qawolf.com%2Fhow-it-works%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=ACQ_All_Demo_Conversions__NewsletterAudience_-_Newsletter_GoodbyeLowTestCoverage_20251208-None_Experiment-FALSE%26utm_term=body-80PercentAutomatedE2ETestCoverageInWeeks%26utm_content=GoodbyeLowTestCoverage_ScheduleADemoToLearnMore_None_Headline%253AGoodbyeLowTestCoverageAndSlowQACycles____Newsletter-PrimaryPlacement_20251208_v1_/1/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/XDZPQalBoMdgmhO-RfuyB75CuKy9-ymNGPHoaJN_9BA=434" rel="noopener noreferrer nofollow" target="_blank"><span>80% automated E2E test coverage in weeks</span></a>—not years</li>
<li><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.qawolf.com%2Fhow-it-works%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=ACQ_All_Demo_Conversions__NewsletterAudience_-_Newsletter_GoodbyeLowTestCoverage_20251208-None_Experiment-FALSE%26utm_term=body-UnlimitedParallelTestRuns%26utm_content=GoodbyeLowTestCoverage_ScheduleADemoToLearnMore_None_Headline%253AGoodbyeLowTestCoverageAndSlowQACycles____Newsletter-PrimaryPlacement_20251208_v1_/1/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/W9eIw0D70xtLXz3rACHPIuKvN6nxYppomjvB81ZxyDU=434" rel="noopener noreferrer nofollow" target="_blank"><span>Unlimited parallel test runs</span></a></li>
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<p>The benefit? No more manual E2E testing. No more slow QA cycles. No more bugs reaching production.</p>
<p>With QA Wolf, <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.qawolf.com%2Fcase-studies%2Fdrata%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=ACQ_All_Demo_Conversions__NewsletterAudience_-_Newsletter_GoodbyeLowTestCoverage_20251208-None_Experiment-FALSE%26utm_term=body-DratasTeamOfEngineers%26utm_content=GoodbyeLowTestCoverage_ScheduleADemoToLearnMore_None_Headline%253AGoodbyeLowTestCoverageAndSlowQACycles____Newsletter-PrimaryPlacement_20251208_v1_/1/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/BWfgg92zfVIRNlLQEsh_kFzJrzkkrNKfMsz9A-xwqOY=434" rel="noopener noreferrer nofollow" target="_blank"><span>Drata's team of engineers</span></a> achieved 4x more test cases and <strong>86% faster QA cycles</strong>.</p>
<p><a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.qawolf.com%3Futm_source=tldr%26utm_medium=newsletter%26utm_campaign=ACQ_All_Demo_Conversions__NewsletterAudience_-_Newsletter_GoodbyeLowTestCoverage_20251208-None_Experiment-FALSE%26utm_term=cta-ScheduleADemoToLearnMore%26utm_content=GoodbyeLowTestCoverage_ScheduleADemoToLearnMore_None_Headline%253AGoodbyeLowTestCoverageAndSlowQACycles____Newsletter-PrimaryPlacement_20251208_v1_/1/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/JxoxMx7oLQrjlKssB0tTH4PCqHJQuqqxwArEN4sxsfA=434" rel="noopener noreferrer nofollow" target="_blank"><span>Schedule a demo to learn more</span></a>
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TanStack AI launched this week in alpha. It features a clean architecture, deep type safety, tight ecosystem integration, and few assumptions about user platforms. While it is less production-ready than Vercel's AI SDK, TanStack AI is the more interesting bet for the future due to its architectural decisions. This post looks at both TanStack AI and Vercel AI SDK and compares their current features.
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Elio used Claude Code to migrate 970 test files (6,000+ tests) from React Testing Library v13 to v14 in just one week. Its team had Claude build a detailed migration guide first. They created an AST codemod to handle mechanical changes, then let Claude iteratively migrate 10 tests at a time while automatically running tests and checking coverage.
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Great engineering is less about perfect code and more about understanding users, working well with people, and avoiding common traps. It's better to ship messy prototypes instead of debating perfect architectures forever, write clear code instead of clever code, and remember that your work doesn't speak for itself. People advocate for you in rooms you're not in.
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<strong>My Thoughts on Claude Opus 4.5 (10 minute read)</strong>
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Claude Opus 4.5 is a generational "unlock" in AI. It is the best model for both code and agents. Users should treat Opus 4.5 as a trusted coworker, use Claude Code for programming, and build impactful agents using the SDK.
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🛠️ As Brex scaled to 800+ microservices and 100s of engineers, they hit a testing wall. Engineers waited 30-60 minutes for environments and infrastructure costs ballooned. With <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.signadot.com%3Futm_source=tldr%26utm_medium=sponsorship%26utm_campaign=q4_25_sponsorships/1/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/wJOxYGm4BI3UfaG78g-kqi4eNxLVmtuYJsN6gk0Gxow=434" rel="noopener noreferrer nofollow" target="_blank"><span>Signadot</span></a>, they cut preview times by 80% and costs by 99%. Find out how they did it. <a href="https://tracking.tldrnewsletter.com/CL0/https:%2F%2Fwww.signadot.com%2Fcase-studies%2Fbrex-uses-signadot-to-scale-developer-testing-across-100s-of-engineers%3Futm_source=tldr%26utm_medium=sponsorship%26utm_campaign=q4_25_sponsorships/2/0100019afdf3df17-b0c5ecac-7889-4b45-b1bd-a0023b8179e4-000000/eMFNasovTKw-HWWVIroIzu1j4najcZYpQckLHQQf-2A=434" rel="noopener noreferrer nofollow" target="_blank"><span>Check out the case study</span></a>
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Apptron is a local-first development platform. It creates a full Linux environment inside the browser with a VS Code-based editor that developers can do whatever they want with. Apptron can be used as a development environment and editor, a sandbox for AI and experiments, an editor to publish static sites, an embeddable software playground, or as a way to run and share Linux software on the web. It is fully extendable, customizable, and self-hosted.
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<div style="text-align: center;"><strong><h1>Miscellaneous</h1></strong></div>
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Data management systems have historically been built around the notion of pull queries. This approach of pulling data works well, and it matches how people think and operate. However, there are some challenges with the approach: performance, data formats, data shape, and data location. These problems can be overcome with the help of materialized views. By materializing views incrementally and efficiently, you make your data available for pull-based querying in the right format and shape, at the right location.
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This dev tried to use Claude to precisely recreate the 1996 Space Jam website from a screenshot and assets, but found that it consistently failed to achieve pixel-perfect accuracy. Claude struggled with exact spatial positioning, admitting it couldn't measure pixel coordinates precisely. Claude's vision system likely processes images too coarsely to capture fine-grained spatial relationships.
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<h1><strong>Quick Links</strong></h1>
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<strong>The Anatomy of a macOS App (9 minute read)</strong>
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This post goes over the historical evolution of macOS application anatomy.
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Oxide encourages the use of LLMs but emphasizes that employees must always retain full human responsibility for all outputs.
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<strong>Why the Sanitizer API is just setHTML() (4 minute read)</strong>
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Sanitizing HTML is the practice of taking a piece of HTML and removing some unwanted elements and attributes.
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<strong>Lessons from a Swift Interview (6 minute read)</strong>
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This post contains advice on Swift algorithm design and how to approach technical interviews.
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