Thoughts, ideas, and code snippets from the void.
OpenAI's latest model, GPT-4o, debuted with a jaw-dropping real-time audio demo. I jumped on the API to build with it, and my production experience reveals why the immediate developer reality is far different from the keynote sizzle, especially for true conversational agents.
Everyone's talking about GPT-4o's incredible multimodal capabilities. I spent 9 days throwing its vision mode at real-world analysis problems, and while it's a beast in some ways, its true power—and its often-overlooked limitations—are completely misunderstood.
I spent weeks trying to make Llama 3 8B classify complex legal documents with precision. Here’s why, despite the undeniable power of the base model, the real grind still comes down to data and ruthless evaluation.
Anthropic just dropped Claude 3.5 Sonnet, and I've been jamming with it for the past 9 days. What I found: it’s not just a cheaper, faster option; it's actually smarter for many critical tasks, making its premium sibling, Opus, an increasingly tough sell.
OpenAI’s GPT-4o promises blazing speed, and for good reason. But after weeks of banging on its API, my production metrics show a different story: it’s fast, sure, but the P95 latency for multimodal is still a beast you need to tame for real-time applications.
I dove into Next.js 15 RC and the much-hyped React Compiler for a real-world project. It's cool, it's progress, but don't expect a magic wand for your legacy performance issues.
I dove headfirst into Pydantic V2, expecting a clean performance win. What I got instead was a brutal 11-day fight against unexpected latency spikes and the hard truth about 'just upgrading.'
Apple's vision for AI at WWDC 2024 wasn't just about on-device models. Their 'Private Cloud Compute' is a radical bet on trust, and it's going to reshape how every other app developer approaches AI.
OpenAI's latest model promises raw speed and multimodal prowess, but after running it on our production text tasks for the past few weeks, I've got some notes. Turns out, faster doesn't always mean better for nuanced, high-volume generation.
Anthropic's latest Sonnet release is radically shifting what's possible for everyday AI workflows, making us rethink where we deploy our more expensive models. It’s a genuine leap, and it’s going to make a difference to your budget.
OpenAI's GPT-4o isn't just a faster model; it's a re-think of how we integrate AI into real workflows. I'm seeing immediate, measurable shifts in project velocity and cost that demand a rapid re-evaluation of existing pipelines.
Forget the benchmarks for a second. I put Llama 3 8B through its paces on a real-world internal tool, and what I found will make you rethink your proprietary model spend.
The GPT-4o voice demo felt like science fiction, but after real-world testing, I've got a much sharper take on its current utility. Don't mistake a slick presentation for shipping code.
Meta's Llama 3.1 just hit with a 400K context window. I pushed it on a data preparation workflow that normally sucks up 96 hours of manual review. It cut that down by 38 hours. This isn't just about bigger numbers; it's about what we can actually *do* with that much space.
The recent Tinygrad benchmarks against PyTorch aren't just about raw speed gains; they expose a fundamental design tension in deep learning frameworks that matters for anyone shipping production models.
Anthropic's new Claude 3.5 Sonnet isn't just a speed bump; it's a quantum leap in accessible LLM performance. I put it through its paces on real-world data parsing, and the results are frankly astonishing, especially when you consider the price tag.
Notes on layering a global background, a sticky sidebar, and backdrop-blur to make the admin feel like a native app.
A practical guide to choosing between Next.js server actions and API routes, with examples from this very project.
Prisma is great — but for a small project with a known schema, a thin query helper was faster to ship and easier to reason about.
A walkthrough of how I built this portfolio with Next.js App Router, Tailwind, and a MySQL-backed admin panel.