Speaker
Wes Bos
Appearances over time
1 episodes
Episodes
1
Podcasts
Quotes & moments
One team reported individual contributors merging 60 PRs per release cycle (one week), spanning 20-70 files and thousands of lines of AI-generated code.
Problems that previously took 6 years to manifest — duplicated code, architecture inconsistencies, fragile implementations — are now appearing in months due to AI-generated code velocity.
Running a local AI model of the quality of Claude Opus requires far more compute than most people realize until they actually try it on their own machine.
Hammer.js, a touch-event library used by the Angular team in the episode's question, has not been updated in 7 years, illustrating the long-term risk of external dependencies.
Wes Bos described upgrading 10-year-old Bose QC35 headphones with new ear cups and a USB-C charging board from the QC45, giving them a second life without soldering.
webkit-box-reflect was added to Safari without going through any standardization process and has never been implemented by Firefox or other browsers, even after decades.
Wes Bos observed that AI-generated UI code is a major reason many AI-built apps feel poor to use — they may work technically but the interaction design and visual quality are lacking.
Git was designed for humans making deliberate commits. AI agents commit every thought. The next version control system needs to capture every operation, every keystroke, and every agent conversation — and whoever builds that wins the next era of development tooling.
Local AI is not a monolith. Thousands of small, purpose-built models on Hugging Face run excellently in the browser for specific tasks — speech detection, categorization, vectorization. But running a frontier-quality general model locally is a compute nightmare most people are not prepared for.
AI-generated backend code is often passable, but UI code is where things fall apart. Drill into smaller changes and use tab completion for UI — that's why so many AI-built apps feel terrible to use.
One team is merging 60 PRs per developer per week, spanning thousands of lines of AI-generated code with almost no meaningful human review. The result: technical debt, recurring bugs, fragile architecture, and a codebase becoming impossible to maintain.
Every software engineering problem being blamed on AI — duplication, inconsistency, fragile code — has existed for decades. AI didn't create bad practices. It just compresses 6 years of codebase decay into a few months.
Most people think 'local AI' means the software is on their machine. It doesn't. Tools like OpenCode with DeepSeek still make API calls — to servers in China. True local means the model weights run on your hardware.
Jujutsu (JJ) is Git-compatible, offers a universal undo command via its operation log, and removes the concept of branches in favor of bookmarks. But every time someone explains why they switched, Wes hears someone who was just misusing Git — not someone with a genuinely unsolvable problem.
AI reduces time spent, but that was never the right basis for pricing anyway. Charge based on value delivered to the client. Your army of agents, your tooling, your expertise — that's what you're billing for, not the hours on the clock.
webkit-box-reflect creates glossy floor reflections and has been in Safari for decades. It was never standardized because it was trendy, never proposed through the proper process, and is now obsolete — future solutions like HTML canvas will handle reflections more flexibly.
React developers pull in a library for everything. Angular developers trust the framework and resist external dependencies. In the AI era, the Angular approach looks increasingly correct — AI writes custom utils better than ever, and libraries like Hammer.js show the long-term maintenance cost of dependency sprawl.
The Bose QC35 is still the best noise-canceling headphone Wes has owned. New ear cup pads and a plug-and-play USB-C charging board from the QC45 model transform a decade-old pair without any soldering — just a little wallowing out the connector hole.
The Hugging Face and Pollen Reachy Mini is a 50-step, 2-hour build featuring cameras, microphones, motors, PCBs, and a fully open app ecosystem. Connect it to any AI provider and you have a programmable, expressive robot — Scott is already building a spelling tutor and a Warhammer 40K battlefield advisor.
Analysis
What they talk about
- Technology 89%
- Business 11%
Connections
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