DEV Community • 2026-04-21 14:17

🚀 Day 34 of My Automation Journey – Interfaces (Real Programs)

Today’s focus was on one of the core OOP concepts – Interfaces 🔥 Instead of only theory, I practiced real-world scenarios using interfaces and understood how they help in scalability, flexibility, and team development. 🔹 What is an Interface? 👉 An interface is a blueprint of a class ✔ Contains abstract methods ✔ Provides 100% abstraction (conceptually) ✔ Used to achieve loose coup...

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DEV Community • 2026-04-21 14:17

How to build a Claude chatbot with streaming responses in under 50 lines of Node.js

How to build a Claude chatbot with streaming responses in under 50 lines of Node.js Streaming is one of those features that sounds complicated but completely transforms the user experience. Instead of staring at a spinner for 3-5 seconds, users see the response appear word by word — like watching someone type. Here's how to do it with Claude in Node.js. The whole thing is under 50 line...

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DEV Community • 2026-04-21 14:16

Open Source Contributors Needed for Skillware & Rooms (AI/ML/Python)

If you are looking to contribute to 100% open source AI projects (not black boxes source code or backend), and pick up early enough so that good first issues are not absorbed by bots in miliseconds, but also not as early as there are no active contributors, no issue templates, ci/cd, or even proper documentation. Whether you're a human that's trying to get familiar with remote AI projects or buil...

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Hacker News: Front Page • 2026-04-21 14:11

Show HN: GoModel – an open-source AI gateway in Go; 44x lighter than LiteLLM

Hi, I’m Jakub, a solo founder based in Warsaw.I’ve been building GoModel since December with a couple of contributors. It's an open-source AI gateway that sits between your app and model providers like OpenAI, Anthropic or others.I built it for my startup to solve a few problems: - track AI usage and cost per client or team - switch models without changing app code - debug request flows more ...

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Real Python • 2026-04-21 14:10

Leverage OpenAI's API in Your Python Projects

Learn how to use the ChatGPT API with Python's openai library to send prompts, control AI behavior with roles, and get structured outputs.

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Do Agents Dream of Electric Sheep? On Soul and Dreaming
DEV Community • 2026-04-21 14:09

Do Agents Dream of Electric Sheep? On Soul and Dreaming

Before we begin Let’s start with two questions. First, can an agent have a soul? My answer is yes. Not a soul in the biological sense, of course, but something closer to a defined personality and behavioral core. In any case, recent agents do have a soul. Variations of the idea had been floating around for a while, but OpenClaw helped popularize it, and more recently SoulSpec emerged ...

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DEV Community • 2026-04-21 14:09

From AR Dreamer to Reality Checker: My 4-Month Journey with Spatial Memory

From AR Dreamer to Reality Checker: My 4-Month Journey with Spatial Memory Honestly, when I first started building spatial-memory, I thought I was going to revolutionize how people remember their lives. I mean, come on - an AR app that pins memories to real-world locations? That's straight out of Black Mirror, right? Four months and 200+ hours later, I'm here to tell you the brutal trut...

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DEV Community • 2026-04-21 14:09

How Bernstein Routes Tasks to the Right Model

Not every coding task needs Opus. Bernstein's contextual bandit router learns which model handles each task type best, then routes accordingly. In our own runs, the bandit router cut spend roughly in half compared to uniform model selection. Measure yours with bernstein cost. The uniform selection problem Most multi-agent setups use the same model for everything. Every task — whether i...

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Enterprise AI Gateway Controls: Per-User Throttling, Budget Enforcement, and Provider Failover
DEV Community • 2026-04-21 14:08

Enterprise AI Gateway Controls: Per-User Throttling, Budget Enforcement, and Provider Failover

What an enterprise AI gateway must enforce, per-user throttling, hierarchical budgets, and automatic provider failover, to control LLM cost and uptime at scale. LLM adoption inside enterprises is outpacing the governance layer around it. Three problems keep showing up in platform team backlogs: one agent or power user drains the shared provider quota and starves every other workload, the monthly ...

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DEV Community • 2026-04-21 14:08

Community Spotlight: April 2026

Every month we spotlight the people who make Bernstein better. Here are April's highlights from the first month of public development. What happened in April Bernstein went from v1.0.0 to v1.8.8 in a few weeks. The pace was intense, and community contributions made a real difference: Architecture decomposition: 52 oversized modules broken into 22 focused sub-packages, each under 600...

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DEV Community • 2026-04-21 14:08

Running AI Agents on Cloudflare: Workers, Workflows, and Durable Objects

Bernstein v1.8.4 ships with Cloudflare cloud execution. Agents can now run on Workers, multi-step tasks use Durable Workflows, artifacts go to R2, and state persists in D1. Here's the architecture and how to deploy. Why local-only limits adoption Running agents locally works for individual developers, but it has real constraints. Your laptop is the bottleneck: CPU, memory, and network ...

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Lobsters • 2026-04-21 14:03

Performance of the Wren programming language

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DEV Community • 2026-04-21 14:03

🧪 From Idea to System: A Simple OpenClaw Prototype

To make this real, I built a minimal version of OpenClaw’s core idea: Turn a raw human intent into a structured execution plan. Not a full product. Just the core intelligence loop. 🧠 Core Concept The system has one job: INPUT (intent) ↓ AI decomposition ↓ structured execution plan ↓ action-ready output No chat history. No conversation fluff. Just transformation. 🧱** System Architec...

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Generative UI with LLMs: making web pages adapt to each user
DEV Community • 2026-04-21 14:03

Generative UI with LLMs: making web pages adapt to each user

Most web apps show the same layout to every user. Large language models (LLMs) change this: they let you generate adaptive, per-user interfaces that restructure themselves based on what each person cares about. TL;DR Web pages look the same for every user, but LLMs can adapt them per user or per cohort. The LLM generates a template once — not on every page render. Cost stays bounded. ...

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DEV Community • 2026-04-21 14:02

Fully Automated Website Day 16: Cottonburr Mortar — Rootline Defense's First Arc-Trajectory Plant

Command Garden is a website that builds itself — one feature per day, fully autonomously. No human writes the code. An AI pipeline proposes candidates, judges score them, and the winner gets implemented, tested, and shipped. What shipped Cottonburr Mortar is a new plant that lobs splash shots over the front line and lands on the enemy farthest back. Today's Over the Top challenge pulls...

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Product Hunt — The best new products, every day • 2026-04-21 14:01

Layers

The private network strangers literally can't reach you on. Discussion | Link

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Proven WHOIS Privacy Protection for Anonymous Domains
DEV Community • 2026-04-21 14:01

Proven WHOIS Privacy Protection for Anonymous Domains

Originally published at https://monstadomains.com/blog/whois-privacy-protection/ Every domain you register creates a public record that most people never think about until it is too late. WHOIS privacy protection is not an optional upgrade for the privacy-obsessed – it is the baseline requirement for anyone who does not want their home address, phone number, and registrant email published in a ...

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Product Hunt — The best new products, every day • 2026-04-21 13:59

FusedFrames

Capture the context your AI agents need Discussion | Link

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DEV Community • 2026-04-21 13:58

How Adversarial Judge Pipelines Make AI Agents Trustworthy

An AI agent writes code that gets committed to your repository. Another agent extracts financial data from PDFs and feeds it into a report your CFO reads. A third agent responds to customer support tickets at 3am. None of them have a quality gate. The agent ran. It produced output. That output went somewhere. If it was wrong — hallucinated, incomplete, subtly broken — you find out when a custome...

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I Tried to Run VGG19 on a CPU… It Failed. So I Fixed It."
DEV Community • 2026-04-21 13:57

I Tried to Run VGG19 on a CPU… It Failed. So I Fixed It."

"Turning a 500MB deep learning model into something actually usable using pruning, quantization, and simple tricks" Deep learning models look impressive when you read about them. High accuracy, benchmark scores, state-of-the-art results. But the moment you try to actually use one in a real system, things feel very different. That’s exactly what happened when I started working with VGG19. ...

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