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Episode
430
Interview
Web News

Never Ending Updates | AI Models, Cursor, Frameworks

Recorded:
November 17, 2025
Released:
December 2, 2025
Episode Number:
430

The web development world never stops moving - frameworks push new versions, browsers release new features, dependabot keeps chiming in, and AI tools like Cursor and the latest LLMs drop at a dizzying pace. In this episode, Mike breaks down why everything updates so fast, how he personally decides what’s worth upgrading, and how he stays sane with the nonstop stream of patches, releases, and AI model announcements. From security fixes to real productivity gains, Mike shares practical strategies for keeping your workflow stable without falling behind.

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Who’s in This Episode?

Show Notes

Introduction

  • It feels like every day (sometimes multiple times a day) I get notifications about needing to update my development tools
  • Some of those can come from my IDE, others from dependabot/frameworks and also the industry constantly updating.
  • New AI models are coming out daily that seemingly ‘change the way we code’ yet most of them are incremental changes and need to be used in certain ways to get the most out of them
  • In this episode we’ll talk about how I stay sane with the never ending updates in the web development ecosystem

Why Everything Updates So Fast

  • Web dev is built on layers of abstraction, each with its own update cadence
  • • Browsers
  • • Frameworks
  • • Build tools
  • • Dependencies
  • • AI tooling
  • Competitive pressure drives rapid releases
  • Security patches and CVEs force quick turnarounds
  • The open source model rewards fast iteration, sometimes at the cost of stability

The Mental Load of Constant Updates

  • Update notifications become “ambient noise” that’s easy to ignore
  • Every update carries the fear of breaking changes
  • Adds decision fatigue
  • Makes new developers feel inadequate, like they’re always behind
  • Creates a false sense that “everyone else” is fully up to date

When You Should Update

  • Security patches
  • • Especially if dealing with authentication, payments, or storing sensitive data
  • Critical dependency updates with performance wins
  • Hotfixes for major frameworks
  • Updates that directly impact your daily workflow
  • IDE or LLM assistant updates that offer real productivity gains

When You Shouldn’t Update (Yet)

  • Major version bumps with unclear migration paths
  • Minor updates that trigger test failures or breaking changes
  • Updates in production week, launch week, or during a crunchy sprint
  • New AI model hype that doesn’t map to your use case
  • “Just because it’s available” updates

Strategies for Staying Sane

  • Group updates into a weekly or biweekly batch
  • Maintain a dedicated “update & maintenance” branch
  • Let CI, tests, and staging environments take the risk for you
  • Use Dependabot, Renovate, or similar tools with custom rules
  • Pin versions strategically
  • Keep a changelog reading routine, not a panic button reaction
  • Treat AI models like dependencies
  • • Evaluate
  • • Test
  • • Integrate intentionally

The Industry vs. Your Reality

  • Twitter, Reddit, and tech blogs highlight every new release
  • Real businesses usually move slower and value stability
  • Most companies don’t upgrade frameworks every month
  • Production systems prioritize uptime over novelty
  • Being “behind” by a version or two is completely normal


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