verron

Dad, husband, technologist. I build things, then break, fix, rinse and repeat...

[Bart Mol @Bart_Mol]

Me explaining AI to friends

[DAN KOE @thedankoe]

https://t.co/kNfAIZcqin

[Boris Cherny @bcherny]

I'm Boris and I created Claude Code. Lots of people have asked how I use Claude Code, so I wanted to show off my setup a bit.

My setup might be surprisingly vanilla! Claude Code works great out of the box, so I personally don't customize it much. There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it, and hack it however you like. Each person on the Claude Code team uses it very differently.

So, here goes.

[verron @v3rron]

@karpathy Here’s why:

[Andrew Ng @AndrewYNg]

There’s a new breed of GenAI Application Engineers who can build more-powerful applications faster than was possible before, thanks to generative AI. Individuals who can play this role are highly sought-after by businesses, but the job description is still coming into focus. Let me describe their key skills, as well as the sorts of interview questions I use to identify them.

Skilled GenAI Application Engineers meet two primary criteria: (i) They are able to use the new AI building blocks to quickly build powerful applications. (ii) They are able to use AI assistance to carry out rapid engineering, building software systems in dramatically less time than was possible before. In addition, good product/design instincts are a significant bonus.

AI building blocks. If you own a lot of copies of only a single type of Lego brick, you might be able to build some basic structures. But if you own many types of bricks, you can combine them rapidly to form complex, functional structures. Software frameworks, SDKs, and other such tools are like that. If all you know is how to call a large language model (LLM) API, that's a great start. But if you have a broad range of building block types — such as prompting techniques, agentic frameworks, evals, guardrails, RAG, voice stack, async programming, data extraction, embeddings/vectorDBs, model fine tuning, graphDB usage with LLMs, agentic browser/computer use, MCP, reasoning models, and so on — then you can create much richer combinations of building blocks.

The number of powerful AI building blocks continues to grow rapidly. But as open-source contributors and businesses make more building blocks available, staying on top of what is available helps you keep on expanding what you can build. Even though new building blocks are created, many building blocks from 1 to 2 years ago (such as eval techniques or frameworks for using vectorDBs) are still very relevant today.

AI-assisted coding. AI-assisted coding tools enable developers to be far more productive, and such tools are advancing rapidly. Github Copilot, first announced in 2021 (and made widely available in 2022), pioneered modern code autocompletion. But shortly after, a new breed of AI-enabled IDEs such as Cursor and Windsurf offered much better code-QA and code generation. As LLMs improved, these AI-assisted coding tools that were built on them improved as well.

Now we have highly agentic coding assistants such as OpenAI’s Codex and Anthropic’s Claude Code (which I really enjoy using and find impressive in its ability to write code, test, and debug autonomously for many iterations). In the hands of skilled engineers — who don’t just “vibe code” but deeply understand AI and software architecture fundamentals and can steer a system toward a thoughtfully selected product goal — these tools make it possible to build software with unmatched speed and efficiency.

I find that AI-assisted coding techniques become obsolete much faster than AI building blocks, and techniques from 1 or 2 years ago are far from today's best practices. Part of the reason for this might be that, while AI builders might use dozens (hundreds?) of different building blocks, they aren’t likely to use dozens of different coding assistance tools at once, and so the forces of Darwinian competition are stronger among tools. Given the massive investments in this space by Anthropic, Google, OpenAI, and other players, I expect the frenetic pace of development to continue, but keeping up with the latest developments in AI-assisted coding tools will pay off, since each generation is much better than the last.

Bonus: Product skills. In some companies, engineers are expected to take pixel-perfect drawings of a product, specified in great detail, and write code to implement it. But if a product manager has to specify even the smallest detail, this slows down the team. The shortage of AI product managers exacerbates this problem. I see teams move much faster if GenAI Engineers also have some user empathy as well at basic skill at designing products, so that, given only high-level guidance on what to build (“a user interface that lets users see their profiles and change their passwords”), they can make a lot of decisions themselves and build at least a prototype to iterate from.

When interviewing GenAI Application Engineers, I will usually ask about their mastery of AI building blocks and ability to use AI-assisted coding, and sometimes also their product/design instincts. One additional question I've found highly predictive of their skill is, “How do you keep up with the latest developments in AI?” Because AI is evolving so rapidly, someone with good strategies for keeping up — such as reading The Batch and taking short courses 😃, regular hands-on practice building projects, and having a community to talk to — really does stay ahead of the game.

[Original post: https://t.co/I3alxNs0vn ]

[verron @v3rron]

@levelsio Same here in Toronto. Drivers don’t know the city at all, not friendly, old cars, no charging/water/tissues. Everybody drives Toyota Corolla. Don’t ask about temperature. Only follow their broken GPS, and don’t speak English anymore. Total 180 from last year. Well done, Uber.

[Elon Musk @elonmusk]

Trust those who return the shopping cart

[verron @v3rron]

@zeeg That’s exactly why I’m stuck with writing APIs in Ruby. Node platform just doesn’t have a good framework to work on the backend. Everything just looks like a god damn hack.

[David Cramer @zeeg]

web scale

[Barrett @SledgeDev]

scrum masters moving the project along. dont know what we would do without them

[verron @v3rron]

@khoidaooo I’ve had the exact opposite, when I asked for directions in English, looking 100% like a tourist, at least 3 people started describing for 2 minutes how to get there in FRENCH, with hand gestures and everything, knowing full well I don’t understand a word of what they’re saying.

[verron @v3rron]

@din0s_ @sama I still listen to it every other morning: https://t.co/1KAKVtKx3V

[verron @v3rron]

@AbuAliEnglishB1 Why didn’t he just shout himself in the foot? Could have save the climb.

[Jamon @jamonholmgren]

My son is learning React

[verron @v3rron]

@noobde Everything is top notch… except Cyrax should have been the main and Frost is cameo

[verron @v3rron]

@noobde Strongly disagree. Cyrax was my absolute favorite character in MK3

[verron @v3rron]

@noobde Words can't describe the feelings. It's just absolutely beautiful. The setting, the atmosphere, the character faces, the music. It's gonna be epic! Can't wait...

[verron @v3rron]

@esankiy If you really want to clear all doubts, show us the polygons

[verron @v3rron]

@dhh

[verron @v3rron]

@M_devv It's been patched. Thanks for reporting.