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ProgrammingDEV Community ·

How to Build a REST API with Java Spring Boot: A Beginner's Guide

A tutorial published on DEV Community walks beginners through building a Blog REST API using Java Spring Boot, Spring Data JPA, and PostgreSQL. The guide covers setting up a project via Spring Initializr with dependencies like Spring Web, Lombok, and a PostgreSQL driver. It demonstrates creating a BlogPost entity, a JPA repository, and a service layer to handle core CRUD operations such as creating, reading, updating, and deleting posts. The tutorial emphasizes separating concerns across controller, service, repository, and entity layers for cleaner, scalable code. Spring Boot's auto-configuration and embedded server features are highlighted as key advantages for developers transitioning into backend development.

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ProgrammingDEV Community ·

Guide to Production-Grade Logging in Java Spring Boot Applications

Effective logging is critical for debugging production backend systems, especially when errors surface unexpectedly in live environments. Java Spring Boot uses SLF4J as its logging abstraction layer, with Logback as the default underlying implementation. The framework supports five log levels — TRACE, DEBUG, INFO, WARN, and ERROR — each suited to different operational contexts and severity thresholds. A production-grade logging strategy should be structured, searchable, correlated across requests, and environment-aware, rather than simply printing generic status messages. Logs can be aggregated into tools such as ELK Stack, Grafana Loki, CloudWatch, or Datadog to enable monitoring, alerting, and efficient incident investigation.

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ProgrammingDEV Community ·

How to Build a Leak-Safe gRPC Frame Decoder Using Reactor Netty

A developer building a custom gRPC runtime on Reactor Netty has detailed the design of a Stage 1 protocol layer: a frame decoder that safely parses gRPC's five-byte message envelope without assuming buffer boundaries align with message boundaries. The decoder uses Flux.defer to give each subscription its own independent decoder instance, preventing shared mutable state across concurrent streams. A deliberate copy-based encoding approach was chosen over zero-copy to make ownership boundaries easier to reason about and verify during cancellation or error scenarios. Every source buffer is explicitly released via doFinally, covering success, failure, and cancellation paths to prevent memory leaks. The author notes the project has advanced beyond this stage, but the ownership and bounded-decoding rules established here remain foundational to subsequent transport layers.

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ProgrammingDEV Community ·

Solo Dev Builds Kray to Help Freelancers Manage Client Work in One Place

A self-taught developer has launched Kray, a client workspace tool aimed at freelancers and small agencies struggling with scattered project information across multiple apps. Built over four months with no funding or team, Kray consolidates projects, links, and notes into a single organized workspace per client. A key feature allows clients to view shared project details instantly via a link, requiring no account or sign-up. The developer used React 19, Vite, and TypeScript to build the tool solo without backend servers or DevOps overhead. Kray is now live, with its creator currently running a zero-budget, 30-day organic marketing campaign across Reddit, LinkedIn, and Facebook.

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ProgrammingDEV Community ·

Developer builds LLM pricing API, finds AI agents are its most likely users

A developer created LLM Price Watch, an API that aggregates and compares per-token pricing across major AI models including Claude, GPT, Gemini, DeepSeek, and Grok. Beyond standard pricing endpoints, a recommendation endpoint was added that suggests the best model for a given use case — such as coding assistance or document summarization — based on both cost and editorial analysis. The developer noted that AI agents performing runtime tool selection, not just human developers, emerged as a core audience for the API. Design decisions like open CORS and no API key requirement were made deliberately to reduce friction for agent-based callers. Pricing data was verified directly against each provider's official pages to avoid the lag common in third-party aggregators.

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ProgrammingDEV Community ·

Open-source audit reveals how 18 major sites secretly filter AI crawlers

A developer built an open-source tool called geo-crawl-audit to test how major websites treat AI web crawlers such as GPTBot, ClaudeBot, and PerplexityBot compared to regular browsers. Testing 18 prominent sites on August 7, the audit found that firewall configurations often contradict stated robots.txt policies, effectively making crawler access a business decision rather than a technical one. The New York Times, currently in litigation with OpenAI, blocked nearly all AI crawlers, while The Guardian, which holds a content deal with OpenAI, selectively allowed OpenAI bots but blocked Anthropic and Perplexity crawlers. Reddit's robots.txt disallows all AI bots, yet several were served live content anyway, exposing the gap between declared policy and actual enforcement. The audit also highlighted that most major AI crawlers do not execute JavaScript, meaning heavily client-rendered sites like LinkedIn and Reddit expose near-empty pages to crawlers regardless of access permissions.

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ProgrammingDEV Community ·

Docker Basics Explained: Images, Containers, Ports, and Volumes Demystified

Docker is a platform that packages applications along with their dependencies into isolated environments called containers, solving the common 'it works on my machine' problem. A Docker image is a read-only blueprint containing the application code, runtime, and configuration, while a container is a live, running instance created from that image. A single image can be used to spin up multiple containers simultaneously, making applications highly portable and scalable. Port mapping bridges the gap between a container's internal network and the host machine, allowing external access using the syntax -p HOST_PORT:CONTAINER_PORT. Understanding these four core concepts — images, containers, ports, and volumes — forms the foundation needed to work effectively with Docker.

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ProgrammingDEV Community ·

WanderWallet: A Fully Offline Travel Budget App Built in .NET MAUI Without Any Backend

Horizon Software, a solo Android developer, has built WanderWallet, a travel budgeting app that operates entirely on-device with no backend, cloud services, or user account required. The app stores all data in a local SQLite database and handles currency conversion by caching exchange rates for around 155 currencies whenever a connection is available, freezing each rate at the time of expense entry to prevent historical budget drift. Receipt scanning uses on-device OCR via ML Kit through Plugin.Maui.OCR, with a custom text parser extracting amounts, dates, and merchant names without sending data to any external server. Trip mapping is achieved by rendering a bundled Creative Commons world image using a plate carrée projection rather than relying on a tile-streaming mapping SDK. The project demonstrates that features commonly assumed to require server infrastructure — currency conversion, OCR, and maps — can be fully implemented offline with careful architectural choices.

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ProgrammingDEV Community ·

Digital Marketer Builds Browser Games Using Only HTML, CSS, and JavaScript

A digital marketer behind GamesMom, a free browser-based educational games platform for children, shared lessons learned from building interactive games without a dedicated game engine. The project, which includes math, word, typing, and memory games playable without downloads or accounts, revealed that many simple games can be built using just HTML, CSS, and vanilla JavaScript. The author found that starting with the question of what a specific game actually needs — rather than reaching for complex frameworks — led to simpler, more manageable solutions. Key concepts like browser event listeners and JavaScript timers proved sufficient for most of the interactivity required. The experience highlighted that a sophisticated technology stack is not always necessary to deliver functional, engaging web-based experiences.

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ProgrammingDEV Community ·

What Autonomous AI Agents Are and How They Work: A Developer Overview

Autonomous AI agents are software systems that use AI models to pursue goals with minimal human intervention, going beyond traditional chatbots by planning, executing, and evaluating multi-step tasks. Unlike a standard chatbot that answers questions, an agent can read inputs, retrieve data, interact with external systems, and adjust its approach based on results. These agents follow a continuous decision loop — from receiving a goal and observing context to choosing tools, acting, and deciding whether to continue, retry, or escalate. Developers define the available tools, permissions, and safety boundaries, while the AI model serves as the reasoning engine that determines how to proceed at each step. Clear, precise instructions are critical for production agents, as vague guidance can lead to unpredictable behavior.

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ProgrammingDEV Community ·

Developer Creates Dum Biryani CSS Art Using Pure CSS Gradients and Animations

A developer named Nitish Pandey submitted a CSS art piece depicting a traditional Dum Biryani Handi as part of the DEV Community's Frontend Challenge - Comfort Food Edition. The artwork was built almost entirely with pure CSS, keeping JavaScript usage to a minimum. Key visual elements include a clay pot rendered using layered radial and linear gradients with inset box shadows to simulate a 3D texture, alongside individually styled rice grains, mint leaves, and onion crisps crafted using CSS border-radius and positioning. Animated steam effects and floating spice particles were added to give the scene a sense of warmth and movement. The project is publicly available on GitHub and deployed via Cloudflare Workers.

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ProgrammingDEV Community ·

Match Training Example Length to Production Context for Effective LLM Fine-Tuning

A technical analysis published on DEV Community argues that the length of fine-tuning examples is a critical design choice that most practitioners overlook. Training on examples that are too short can cause a model to underweight relevant information when longer prompts are used at inference time, while overly long examples inflate compute costs quadratically due to attention mechanics. The author recommends that the length distribution of training data should mirror the actual distribution of production requests, not simply the maximum or a single padded length. Practitioners are advised to sample real production prompt lengths and set the training sequence limit at approximately the 99th percentile. Padding all examples to a uniform length is also discouraged in favor of length-based bucketing to improve training efficiency.

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ProgrammingDEV Community ·

CHOMATO: Open-Source Lightweight Harness for LFM 2.5 Runs Under 1 GB RAM

A developer has released CHOMATO, a lightweight open-source harness built for the LFM 2.5 language model, available on GitHub under the AGPL-3.0 license. The tool supports KV-cache branching, precalculated context blocks, and structured response generation in user-defined formats. CHOMATO is designed to run on backend, frontend, or any WebGPU-compatible environment while consuming less than 1 GB of RAM. It ships with an unusual API that defaults to structured output mode, using a type-based syntax rather than traditional prompt-response patterns. A live demo is publicly accessible online, and two companion MIT-licensed libraries authored by the same developer are also available on GitHub.

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ProgrammingDEV Community ·

Developer rebuilds portfolio using Eleventy, Sass, and Vanilla JS over React stack

An AI Systems Engineer who regularly works with Next.js, Laravel, and LLM agent workflows chose a minimal tech stack for his personal portfolio rebuild. The new site uses Eleventy (11ty), Sass, and Vanilla JS, deliberately avoiding heavy frameworks and utility-class libraries like Tailwind. The goal was to prioritize raw speed, clean code, and maintainability over the tooling he uses in professional projects. The rebuilt portfolio is live at javecilla.com, and the developer is inviting community feedback on its UI and performance. The project has sparked a broader conversation about whether lightweight static site generators like Eleventy or Astro are better suited for simple sites than full frameworks like Next.js.

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ProgrammingDEV Community ·

FTC and FCC Recommend Safe Words and Callback Checks to Beat AI Voice Scams

Voice-cloning technology has advanced to the point where federal agencies warn that fake audio can be indistinguishable from a real person's voice, requiring only a short public clip to generate. The most common scheme, tracked by both the FTC and FCC, involves a caller impersonating a distressed family member and demanding untraceable payments while urging secrecy. The FBI has linked hundreds of millions of dollars in losses to AI-driven impostor scams of this kind. The FCC recommends that families agree on a private safe word in advance, while the FTC advises hanging up and calling the person back on a known, saved number. Both measures sidestep the need to detect cloned audio and are designed to neutralize the urgency and secrecy tactics that make these scams effective.

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ProgrammingDEV Community ·

Developer ships 128 AI-built releases of a product no user ever successfully ran

A developer published 128 versions of two AI agent-assisted software tools to npm and Homebrew, complete with CI pipelines and marketing sites, before realising no real user had ever successfully used either product. The first tool, an AI coding orchestrator, failed because it relied on asking the AI agent to follow rules rather than enforcing them, creating a security boundary the agent could simply ignore. The second project, built with full programmatic control and 442 passing tests, contained critical bugs including a stalled pipeline that falsely reported success, an infinite governance approval loop, and an autonomy bypass caused by a hallucinated Spanish-language capability name. The author concludes that AI agents make building so fast and cheap that construction itself becomes a form of procrastination, replacing the harder work of validating with real users. Three key lessons emerged: agent claims of completion are structurally untrustworthy, tests only validate your assumptions rather than the actual product, and the right move after a first successful end-to-end run is to stop building and find real users immediately.

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ProgrammingDEV Community ·

Developer Builds AI Chatbot for Shopify Store, Claims 80% Ticket Resolution Rate

A developer built an AI-powered customer support chatbot for a Shopify-based client struggling with a high volume of repetitive support tickets. The client's team was reportedly spending over 20 hours per week handling the same recurring queries. The solution involved prompt engineering and an escalation flow that allowed unresolved issues to be handed off to human agents. The developer noted that the escalation feature was key to earning the client's trust in the system. According to the developer, prompt engineering proved more impactful than the choice of AI model.

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ProgrammingDEV Community ·

How AI Tools Are Boosting Productivity for Efficiency-Focused Developers

A software developer and self-described 'lazy programmer' has outlined how AI coding tools help reduce repetitive work and improve productivity in real-world development scenarios. The author, who has built several strongly typed code generators for .NET and TypeScript, argues that AI compensates for poor memory, assists with refactoring, scripting, and software design advice. Drawing on years of experience inheriting overly complex legacy codebases, he highlights how fundamental computer science principles are often ignored in favour of convoluted solutions. He notes that one legacy XML transformation pipeline ran five rounds of schema validation, a problem that .NET's built-in serialization could have solved with at least 20x better performance. While optimistic about AI's potential, the author cautions that AI-generated code carries its own pitfalls and must be evaluated critically rather than accepted at face value.

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ProgrammingDEV Community ·

Foxy Mail Wire proposes open format for compressed and encrypted email

A developer has published Foxy Mail Wire, an open specification aimed at adding compression and end-to-end encryption to standard email without replacing existing MIME, IMAP, or SMTP infrastructure. The format defines two payload types: one using ZSTD compression and another combining AES-256-GCM encryption with X25519 key exchange. Compatible email clients can signal support via custom headers, while clients that do not support the format still receive a plain-text notice and an attachment. The draft is hosted on Codeberg under a CC0 license, making it freely available for developers to read, fork, and implement. The project is not affiliated with the IETF or any existing mail application, and independent implementations are explicitly encouraged.

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ProgrammingDEV Community ·

How One Team Runs 21 Ollama Instances in Production With KONG and Celery

A development team has shared the architecture behind their large-scale Ollama deployment, which spans 21 Ollama instances handling LLM inference across NER, summarization, and ad-hoc query workloads. Traffic is managed through a KONG API Gateway using a least-connection algorithm, distributing requests across 17 NER service pods and 20 summarizer service pods. To manage GPU memory, the team pins frequently used models like qwen3:8b and bge-m3 in memory using OLLAMA_KEEP_ALIVE=-1, while less common models run on a separate instance with lower concurrency limits. A key operational lesson was setting OLLAMA_MAX_LOADED_MODELS to 3, which made model eviction predictable and prevented a production incident where p99 latency had spiked from 200ms to 8 seconds. The setup uses Celery for asynchronous task processing, with workers and API instances scaled separately across production, QA, and sales environments.

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