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If you are a software engineer, no doubt you’ve seen some astounding new model or prompt posted to twitter, or some shamelessly fraudulent product demo and felt your blood run cold, your wizardly coding powers draining from your fingers.

The reality, however, is that Full Stack engineers are quite a bit closer to the modern AI engineering role today than they might think. Machine learning

“In numbers, there’s probably going to be significantly more AI Engineers than there are ML engineers / LLM engineers. One can be quite successful in this role without ever training anything.” – Andrej Karpathy

AI engineering is no longer Deep Learning

The field of AI *used* to be an offshoot of Machine Learning (i.e. AI is what we used to refer to as Deep Learning), and at the bottom end of the stack, that is what it is. And certainly, if you want to build models from scratch, that’s what it takes. A little as a year ago, my feeling was that the way to approach AI was via the one I had take – via the fundamentals first: walk through the Fast.ai lesson series, getting a working understanding of Machine Learning processes as they relate to Deep Learning and build on that.

But, the systems and abstractions over the Deep Learning layer are now so powerful (and complex) that building them and using them takes an entirely different skill set. AI is being absorbed into actual engineering, and becoming an engineering field of its own. And, as such, what used to be the most direct and immediately applicable skills have changed. Moreover, as that has happened, the distance between “Full Stack” engineer and “AI” engineer has been falling over time.

Notice where the lines being drawn here? It’s not between you and AI engineering. And, AI is going to continue moving to the right on the line above: if the stack is entirely composed or managed by AI, a “Full Stack” engineer, who can’t also implement and manage AI pipelines, isn’t going to be all that “Full Stack” any more.

All in all, it’s just another tool in the tool box.

The Faustian bargain we made for a job creating shiny new toys was a never-ending supply of new shiny toys. And, AI appears particularly Faustian, in that (for now) that there’s a never-ending supply of new shiny AI tools, along with FOMO.

“We have no idea what large language models are going to be good at or bad at over any sense of time… The amount we don’t know because of how quickly this has developed is at an all time high, that lets us experiment and have a sense of play, and do things and not know how the result is going to be, which is fun. – Dan Becker @dan_s_becker

I’m working at Say Mosaic as Systems Architect of their flagship product: Smart Home in a Box. This has involved designing their cloud infrastructure, and helping improve their home-grown NLP/NLU AI systems. Today, we’re trending on product hunt.

I could get used to this trend of trending 🙂

I released a repo on Github on Sunday. And it’s trending today!

All the way down there in the middle 🙂

Every time I find myself feeling a little silly being buoyed by a small bunch of internet points, I remember all the repos I’ve cloned or required, and where they got me 🙂

I don’t know – you tell me.

Yesterday, my wife met someone in a pool ride who explained he was working at a start up that displayed pictures of the food in a restaurant, so you would choose which restaurant you would got to depending which pictures of food you liked. Yes – they are building Tinder for plates of food.

She asked him how they were going to take all the pictures, since most fancy restaurants are going to be switching out their menu once or twice a month. 

Dear Alice and Ryan,

Congratulations on your new fondleslabs, and welcome to the 90% of humanity that now spend all their time staring at their phones. Since I am also too busy staring at my phone to talk to you, I thought that you might appreciate a list of the things I am usually staring at, so you can stare at them too.

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So, I’m working on a new app to go in my portfolio. It’s called Schmoozr (until I find out that name is taken).

Say you go to some event, and meet someone there, and decide you want to exchange emails, so you can continue you the discussion further later on. Instead of handing them your email or typing their email into your phone, you open schmoozr, and it has a simple form for name, email, and perhaps a note they might want to leave for you about your conversation.

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I’ve created an add-on for Jasmine, that allows you to iterate a set of Jasmine tests or suites through an array of test data. So, you can create a set of edge cases for whatever you are are trying to test, and then run them through this.

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