Ai

For AI engineering leaders, the annual back-to-school season isn’t just a cultural milestone; it’s a market signal. It marks a massive influx of users engaging with digital tools, testing the limits of existing platforms, and revealing unmet needs. The recent “Hard Fork” podcast episode on AI in education serves as a potent source of raw user research, offering a direct line into the mindsets of educators, innovators, and the students who form the next generation of knowledge workers. ...

Thinking about the GPT-5 presentation fiasco yesterday(friends don’t let friends use Dalle for charts) and the resulting, almost overwhelmingly negative reaction to the style of the speakers and the substance. I’m wondering if what we’re seeing is less a problem with LLMs having hit a ‘wall’ and more with the ’enshittification’ of OpenAI itself? They’ve never been particularly strong on the pure research side of things. Their main strength has always been productizing scientific breakthroughs in consumer products. Take the fundamental ‘attention is all you need’ paper and transformers architecture. Neither of those were OpenAI breakthroughs. Instead, their incredibly talented early team identified ways to capitalize on those important insights with their own breakthroughs in model training and scaling. ...

You’ve been there. You and your AI coding buddy are in the zone. It’s feeding you perfect snippets of code, it understands your weirdly named variables, it’s practically reading your mind. You’ve built half a dozen functions, and the project is humming along. Then you close the window. You come back an hour later, open a new chat, and ask it to build the next piece of the puzzle. The AI stares back at you with the digital equivalent of a blank expression. It has no idea what your project is, what a user_auth_service is, or why you keep muttering about the global_config.json. It has, for all intents and purposes, become incredibly dumb. ...

Ever tried Elevator Saga? It’s that addictive JavaScript challenge where you control elevators to transport impatient virtual humans. Sure, you could spend hours crafting the perfect algorithm… or you could do what I did and let AI handle the heavy lifting. Tools Claude 3.5: Model I prefer for generating code and specifications. It’s like having a coding buddy who never sleeps. Whisper: For transcribing my ramblings into something resembling a coherent spec. LLM: A command-line tool to interact with AI models like Claude and generate code from my documentation and spec. My Lazy Developer Workflow I built a four-step AI pipeline that took me from “what even is an elevator API?” to passing the first four levels with minimal effort: ...

In a testament to the progressive march of technology, OpenAI has emerged as a herald of the AI renaissance. Recently, the distinguished AI think-tank cast a spotlight on future digital directions at its inaugural Developer Day event. This blog endeavors to capture the pivotal moments and revelations that could very well chart the course for AI’s role in our everyday lives. Custom GPTs Made Easy A remarkable stride in AI accessibility was announced, shattering the barriers to entry for custom GPT utilization. No longer confined to the realm of software engineers, the ability to customize powerful language models is now in the hands of the many. A diverse audience now holds the keys to unlock an AI that resonates with their unique needs, epitomizing a radical democratization of AI technology. ...