DEV

Managing checkpoints in a continual learning pipeline is one of those engineering problems that feels like housekeeping — until it isn't. When a production model misbehaves at 2 a.m. and your checkpoint directory is a graveyard of files named "final_really_this_time.pt," the cost of poor versioning becomes very real, very fast. This episode walks through the key ideas from this deep-dive on managi...

Getting a deep learning model to perform well in training is one challenge — getting it to run efficiently in production is a different beast entirely. This episode of Development tackles that gap head-on, exploring the powerful combination of ONNX and TensorRT as a practical path to faster, leaner inference. The discussion is grounded in this in-depth guide to runtime optimization of ONNX models...

Modern AI models have grown far beyond what a single GPU can hold in memory — and that's not a problem you can optimize your way out of on one device. This episode of Development tackles the architecture, tooling, and practical considerations behind multi-GPU training, using Microsoft's DeepSpeed framework as the focal point. It's grounded in this in-depth guide to multi-GPU training with model pa...

Shipping an LLM-powered product is one thing — keeping it responsive when traffic spikes is another challenge entirely. This episode of Development digs into a foundational infrastructure decision that separates hobby demos from production-grade AI services, drawing on this practical deep dive into async LLM serving architecture published on DEV. If your service handles user-submitted prompts sync...

Large Transformer models like BERT and GPT have redefined what's possible in natural language processing — but their enormous parameter counts create serious deployment headaches. Memory constraints, sluggish inference, and ballooning cloud costs can make shipping a production-ready model feel like an engineering wall. This episode of Development digs into weight clustering, a compression techniqu...

Inheriting a messy, multi-language codebase is one of those challenges that used to mean hours of manual archaeology. This episode of Development explores a more intelligent approach: a static AI code assistant powered by abstract syntax trees (ASTs) and Tree-sitter. The discussion is grounded in this practical deep-dive on building a static AI code assistant , and it covers everything from the fo...

Edge ML deployments have a nasty habit of exposing a fundamental tension: the models that would benefit most from rich training data are often running on devices that can't collect it — blocked by privacy regulations, hardware limits, or unreliable connectivity. This episode of Development tackles that problem head-on, walking through a structured engineering approach to building a GAN-powered syn...

Finding a JavaScript developer who can actually ship clean, maintainable code is harder than it looks. This episode of Development draws on this practical hiring guide for JavaScript roles to walk hiring managers and technical leads through a structured, no-fluff approach — from vetting core language fundamentals all the way through final-round interview tactics. Here's what the episode covers: No...

For many businesses, the gap between a great software idea and an actual software product comes down to one thing: resources. White label development has emerged as a compelling way to close that gap — but like any strategic shortcut, it comes with fine print worth reading. This episode of Development walks through the full picture, drawing on the pros and cons of white label software development...

C++ powers some of the most demanding software on the planet — from automotive braking systems and high-frequency trading engines to medical devices and AAA game physics. When internal teams are stretched thin or domain expertise simply doesn't exist in-house, outsourcing can be a smart strategic move. But the stakes of choosing poorly are uniquely high with C++, and the evaluation process deserve...

Running out of GPU memory is one of the most common — and most frustrating — walls a deep learning engineer can hit. This episode of Development explores a powerful architectural fix that most developers never reach for: reversible residual networks. Drawing on this in-depth guide to building memory-efficient backprop with RevNets , the episode breaks down the math, the trade-offs, and the practic...

Picking a JavaScript framework isn't just a technical decision — it shapes how you hire, onboard engineers, structure your codebase, and maintain software years down the line. This episode of Development tackles one of the most debated questions in front-end development head-on, drawing on the React vs. Vue vs. Angular framework comparison from DEV to cut through social media noise and deliver a g...

JavaScript has spent thirty years defying expectations — born as a browser novelty, it now underpins cloud infrastructure, mobile apps, and real-time platforms at organizations of every size. This episode of Development uses this breakdown of top JavaScript use cases for startups and enterprises as its jumping-off point, making the case that JavaScript's dominance is less about trend-chasing and m...

Despite a constant parade of newer languages grabbing headlines, C++ continues to underpin some of the most performance-critical software on the planet — from high-frequency trading systems to AI inference engines to AAA game engines. This episode of Development cuts through the hype to examine the concrete, technical reasons why C++ isn't just surviving in 2025, but thriving. The discussion draws...

Repetitive AI tasks — pulling data, prompting a model, cleaning the output, posting it somewhere — eat developer time without delivering proportional value. This episode of Development explores how n8n, an open-source visual workflow engine, changes that equation by letting teams prototype and ship AI automations without spinning up infrastructure from scratch every time. The discussion is grounde...

Python isn't just surviving the era of Rust evangelism, Go's cloud-infrastructure push, and a never-ending parade of JavaScript frameworks — it's thriving inside the world's most demanding enterprise environments. This episode of Development digs into the analysis behind why enterprises are still choosing Python for backend development , unpacking a convergence of forces that make the language a u...

Every few years, a new language is crowned the future of systems programming. Yet when the stakes are highest — financial systems measured in microseconds, medical devices where latency is a safety concern, or AI backends crunching tensors at scale — engineering teams keep reaching for C++. This episode of Development examines the case for C++ as a top choice for high-performance software in 2025...

Systems-level programming demands more from a language than raw speed — it demands predictability, safety, and a codebase that someone can still reason about years down the line. This episode of Development puts C++ and Rust side by side across the dimensions that actually matter in production, drawing on the C++ vs. Rust comparison published at DEV . Rather than declaring a winner, the episode gi...

Training your own large language model might sound like something only well-funded research labs can pull off — but the open-source ecosystem, rentable cloud compute, and publicly available datasets have changed that calculus dramatically. This episode of Development unpacks this step-by-step guide to building a custom LLM , walking through every major decision point a developer will face on the j...

Where JavaScript executes isn't just a technical footnote — it's one of the most consequential architectural decisions a developer makes. This episode of Development digs into the fundamental divide between client-side and server-side JavaScript, tracing the language's evolution from a browser-only scripting tool into a full-stack runtime, and unpacking why the execution environment shapes everyth...

Content moderation for large language models is often treated as an afterthought — a filter bolted on after the model has already finished speaking. This episode of Development makes the case that timing is everything, and that catching harmful output as it forms, token by token, is a fundamentally different and more defensible approach. The discussion is grounded in this in-depth guide to creatin...

Choosing the right Python library for machine learning isn't just a technical decision — it's a strategic one. With the ecosystem evolving rapidly, this episode of Development cuts through the noise to spotlight the tools that are genuinely delivering in 2025, drawing on this in-depth overview of Python's top ML libraries to give developers a clear-eyed view of what's worth learning and what's wor...

Picking a Python web framework isn't just a technical checkbox — it shapes how fast a team ships, how easily new developers ramp up, and how cleanly a codebase handles growth over time. This episode of Development digs into one of the most debated questions in the Python ecosystem, drawing on the Flask vs. Django framework comparison published at DEV. Rather than declaring a winner, the episode gi...

Java has been written off more times than anyone cares to count, yet it continues to underpin some of the world's most critical software — from banking infrastructure to global logistics platforms. This episode of Development takes a clear-eyed look at the state of enterprise Java in 2025, drawing on this deep-dive into enterprise Java tools and trends to map out what's actually changed, what's st...

Choosing a C++ framework is one of those decisions that looks straightforward on the surface but quietly shapes everything that follows — your architecture, your team's velocity, your licensing obligations, and your long-term maintenance burden. This episode of Development draws on this guide to choosing the right C++ framework to walk through a structured, requirements-first approach that cuts th...