[music] How's everybody doing. Still awake. >> Okay, great.So like the robot voice said, I have been doing developer experience for a very long time and I have never in my life seen anything like the last 12 months. The you know about every 2 to 3 weeks software engineers been making this face on the screen. Okay.And if you work in developer experience the problem is even worse. You're like this guy on the screen every few weeks. You're like, "Oh yeah, yeah, yeah, yeah, yeah. Here's the new hotness." And th ...

An MCP server that detects production-grade code quality issues in real-time!Even though AI is now generating code at light speed, the engineering bottleneck has just moved from writing to reviewing, and now devs spend 90% of their debugging time on AI-generated code.AI reviewers aren't that reliable either because they share the same fundamental blind spots as AI generators do:- They pattern match, not proof check.- They validate syntax, not system behavior.- They review code, not consequences.I have been ...

when the junior dev leaves a comment on your code https://t.co/p5zNj0P5DD ...

RT Avi Chawla (@_avichawla)You're in a tech lead interview at Google.The interviewer asks:"AI generates 30% of our code now.But our engineering velocity has only increased by 10%.How would you fill this gap?"You: "Using AI code reviewers will solve this."Interview over!Here's what you missed:Many engineers think the solution to AI bugs is more AI.Their mental model is simple: "If AI can write it, AI can review it."But if AI could catch these issues, why didn't it write correct code in the first place?There' ...

You're in a tech lead interview at Google.The interviewer asks:"AI generates 30% of our code now.But our engineering velocity has only increased by 10%.How would you fill this gap?"You: "Using AI code reviewers will solve this."Interview over!Here's what you missed:Many engineers think the solution to AI bugs is more AI.Their mental model is simple: "If AI can write it, AI can review it."But if AI could catch these issues, why didn't it write correct code in the first place?There's enough evidence to sugges ...

AI Coding Impact on Software Engineering - The speaker believes predictions of massive software engineer job losses due to AI coding are likely wrong, not because AI coding isn't important, but because those making predictions haven't worked on production systems recently [2] - AI code generation at 30% in very large codebases may not be as impactful as perceived due to existing architectural constraints [3] - The industry believes software engineers will still be needed to fix, examine, and understand the nuances of code in complex systems, even with AI assistance [6] - The speaker draws a parallel to the DevOps transformation, suggesting AI will abstract work, not eliminate jobs, similar to how tractors changed farming [7] Production Software Considerations - Production code requires "four nines" availability, handling thousands of users and gigabytes of data, which "vibe coding" (AI-generated code without examination) cannot achieve [10] - The speaker emphasizes that code is an artifact of software development, not the job itself, which involves making decisions about software architecture and dependencies [11] - The best code is no code, as every line of code introduces maintenance and debugging burdens [12] - AI's text generation capabilities do not equate to decision-making required for complex software architectures like monoliths vs microservices [15] - Changing software safely is the core job of a software engineer, ensuring functionality, security, and data integrity [18] AI Adoption and Best Practices - Professional software engineers are observed to be slower in adopting AI compared to previous technological shifts [20] - The speaker suggests documenting standards, practices, and reproducible environments to facilitate AI code generation [22][23] - Code review is highlighted as a critical skill, especially with AI-generated code, but current code review tools are inadequate [27][28] - The speaker advises distrusting AI's human-like communication, as it may generate text that doesn't accurately reflect its actions [32] - The speaker recommends a "create, refine" loop for AI-assisted coding: create a plan, have AI generate code, then refine it [35][36][37]