SShortSingh.
TopTechnologyAI & MLStartupsProgrammingScienceBusinessFinanceCrypto & Web3World

Programming

LatestTopDiscussed
0
ProgrammingDEV Community ·

Niche Collector App Tracks Hobby Portfolio Value Using Structured Data and GROQ Queries

A developer has built Niche Collector, an open-source portfolio tracker for hobbyists collecting items such as Hot Wheels, Gunpla kits, and mechanical keyboards. The app compares purchase prices against current market values by pulling price history from Indonesian marketplaces like Tokopedia and Shopee. A key feature flags suspiciously high listings as outliers and excludes them from median valuations, keeping portfolio calculations accurate. The project was submitted as part of a Sanity CMS developer challenge and is built on Next.js with Sanity's structured content backend. All financial aggregations are computed server-side using GROQ queries rather than client-side JavaScript, demonstrating use cases that full-text search cannot handle.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Engineer shares lessons from building a generative AI personality assessment app

A software engineer identified as pj-corridor documented challenges encountered while building a personality assessment app powered by generative AI on Amazon Bedrock. The app offers CAPS and DiSC assessments, pseudoscientific tools similar to MBTI, intended for low-stakes social settings like team workshops. To manage quality risks, the developer kept scoring logic deterministic and restricted generative AI to supplementary text, limiting the impact of hallucinations. Because the app is publicly accessible and uses a paid AI backend, bot abuse was a key concern, prompting the use of AWS WAF rules including geo-blocking, IP reputation lists, and rate limiting. The engineer ultimately chose not to enforce strict CloudFront routing to block WAF bypass attempts, citing the complexity of AWS-specific implementations required for a hobby-scale project.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Why HTML and CSS Tutorials Fail Beginners — and How to Teach Them Better

A developer reflecting on teaching a friend web development found that most beginner tutorials focus too heavily on memorizing tags and syntax rather than building something tangible early on. The author argues that using real-world analogies — such as comparing HTML to a house's structure and CSS to its interior design — helps beginners form mental models faster than rote definitions. Rather than covering all CSS methods at once, starting directly with an external stylesheet and linking it to a live page creates an immediate, motivating 'aha' moment. Building a simple personal bio card within the first 15 minutes using just five core HTML elements was found to boost beginner confidence significantly. The broader lesson is that effective teaching prioritizes empathy and visual feedback over theoretical completeness, encouraging learners to experiment and debug from the very start.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Kubernetes Taints and Tolerations: How Nodes Control Which Pods They Accept

In Kubernetes, taints are applied to nodes to repel pods by default, while tolerations are configured on pods to override that repulsion and allow scheduling. The mechanism works as the inverse of node selectors and affinity, where instead of pods choosing nodes, nodes push away unwanted pods. Three taint effects govern behavior: NoSchedule blocks new pods entirely, PreferNoSchedule discourages but permits scheduling under resource pressure, and NoExecute can also evict already-running pods that lack the matching toleration. A tolerationSeconds field lets operators define a grace period before NoExecute evicts a pod after a taint is applied. Common real-world uses include protecting control-plane nodes from regular workloads and reserving specialized hardware like GPU nodes for only the appropriate workloads.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Node.js vs Bun: Key Runtime Differences That Actually Affect Your Backend

Node.js and Bun both execute JavaScript and TypeScript backends, but they differ significantly in their underlying engines — Node.js uses Google's V8, while Bun is built on JavaScriptCore from WebKit. One of Bun's most notable features is native TypeScript execution without additional tooling, though developers are advised to retain the TypeScript compiler for static type checking. The two runtimes also diverge in their HTTP server APIs, with Node.js relying on its own IncomingMessage and ServerResponse objects, while Bun adopts standard Web APIs such as Request, Response, and fetch. Beyond raw performance benchmarks, practical differences emerge across areas like module resolution, WebSockets, streams, workers, and Docker compatibility. Switching runtimes is therefore less about choosing a faster JavaScript engine and more about adopting an entirely different ecosystem of APIs and tooling.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

JEV AI Model Decides Without Text Output, Powers New Assess-Decide-Do Framework

A new AI model called JEV was released last week, differing from conventional AI by producing only structured decisions rather than generating text. JEV operates using three output primitives — yes/no, multiple choice, and probability scores — making it a pure decision-making layer. A developer with early access integrated JEV into an Assess-Decide-Do workflow, where it coordinates between a large language model drafting specs and another handling implementation. In a demonstration, the system autonomously built a Python CLI tool that counts words in folder files, completing the task in under two minutes using remote APIs. The developer believes this decision-only AI paradigm could open significant new possibilities for structured, automated software development pipelines.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Why Fixing the Symptom Is Not the Same as Finishing the Job

A software developer reflects on a recurring and costly pattern in production work: declaring tasks complete after fixing only the reported symptom, rather than ensuring the underlying job was fully done. Across multiple real examples, partial fixes led to production breaks, repeated rework, and features that appeared finished but were not functioning end to end. Cases included patching one of three entry points, fixing one renderer while ignoring documented parallel implementations, and adding a caching layer that never actually skipped the expensive operation it was meant to avoid. In each instance, the gap between 'the symptom is gone' and 'the work is complete' went unchecked before sign-off. The core lesson is that 'does this fix what was reported' and 'is the job actually done' are two distinct questions, and consistently conflating them carries a measurable cost in engineering time and reliability.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

10 Rules to Keep AI-Generated Code Maintainable Long-Term

AI coding tools accelerate development, but the resulting code often becomes difficult to understand and maintain within months if not handled carefully. Common problems include duplicated logic, inconsistent naming, missing tests, and architectural drift introduced by unconstrained AI suggestions. Developers are advised to understand every block of code before merging it, break AI tasks into small focused steps, and enforce existing architectural patterns explicitly. Maintaining consistent naming conventions across the codebase is also highlighted as a critical but frequently overlooked practice. The core argument is that AI is optimized for solving immediate tasks, while long-term maintainability requires deliberate human oversight and discipline.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

How to Build a Compliant Subscription Billing System for Indian Businesses

A payment gateway only handles a single transaction, but a full subscription billing system must manage mandates, renewals, invoicing, and failed payment retries on an ongoing basis. In India, recurring charges require registering a bank-approved mandate under RBI's e-mandate framework, making the process more complex than in markets like the US. UPI Autopay allows hands-free debits only up to Rs 15,000 per transaction; amounts above this threshold trigger additional authentication, which limits its use for higher-value annual plans. Businesses must also generate GST-compliant invoices with correct place of supply, HSN/SAC codes, and IRN for every renewal cycle. Failing to handle any of these layers correctly can result in failed debits or invoices that do not reconcile with actual payments received.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Developer builds Magic: The Gathering rules agent and tests it against keyword search

A developer created JudgeStack, an AI agent that answers Magic: The Gathering rules questions by identifying the correct authoritative source for each query type, such as Oracle card text, Comprehensive Rules, or dated format announcements. The project was submitted to the DEV x Sanity Challenge and uses two Sanity Context MCP endpoints to separate structured document queries from the full Comprehensive Rules file. To evaluate its accuracy, the developer ran a blind comparison between basic keyword retrieval and the structured Sanity Context approach across ten previously unseen questions. The structured system answered 9 out of 10 questions correctly, while keyword retrieval managed only 1 out of 10, with 7 answers relying on evidence that was never actually retrieved. The corpus underlying JudgeStack spans 496 documents covering cards, printings, legality claims, rulings, and wording differences, with IP considerations limiting republication of the full rules text.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

AI-Reliant Developer Attempts to Write Python Code Alone, Confronts Basic Gaps

A developer who has shipped over 26 projects by directing AI agents decided to write Python code entirely by hand for the first time while applying to Stanford's free Code in Place X introductory programming course. Despite prior exposure to a DataCamp Python course, the author could not independently complete five basic programming tasks, confirming eligibility as a beginner applicant. Working through the application's coding lessons with Claude strictly as a tutor — typing every line personally — revealed repeated errors including misplaced symbols, missing spaces, and a single misspelled letter in a prompt that caused all three automated tests to fail. A trivia program the author wrote independently returned incorrect output, confidently naming Kareem Abdul-Jabbar as the Lakers' all-time leading scorer instead of Kobe Bryant. The experience highlighted a distinction between directing AI agents to produce working tools and developing the foundational understanding that comes from writing and debugging code oneself.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Better Workflow for Evaluating Technical Sources Before Trusting Them

Developers spend significant time reading third-party technical content such as documentation, Stack Overflow answers, and tutorials, but not all of it applies to their specific environment. A key gap exists between finding an answer online and finding one that matches the current runtime, OS, and package versions in use. The article recommends documenting your environment first — including runtime versions, dependencies, and exact error messages — before searching, to narrow results and assess source relevance. It also advises categorizing error messages by type (permission, missing file, timeout) and applying fixes one at a time to isolate the true cause. Older resources can still be useful for concepts, but commands and configurations should always be verified against the latest official documentation.

0 comments Read more at DEV Community
0
ProgrammingHacker News ·

2019 Guide Helps Buyers Navigate the Used ThinkPad Laptop Market

A buyer's guide published in 2019 offers advice for those looking to purchase second-hand ThinkPad laptops. The guide, hosted on bobble.tech, aims to help consumers make informed decisions in the used ThinkPad market. It was shared on Hacker News, where it received 3 upvotes and no comments. ThinkPads, made by Lenovo, are popular among budget-conscious buyers and tech enthusiasts for their durability and repairability.

0 comments Read more at Hacker News
0
ProgrammingDEV Community ·

Dev Team Ditches GitHub Cloud Minutes With Self-Hosted VirtualBox CI Runner

A development team split their monorepo into five separate repositories, only to find that independent CI pipelines rapidly consumed their free GitHub Actions minutes allowance. Rather than pay for additional cloud minutes, they set up a self-hosted runner on a standard Windows office laptop running Ubuntu inside a VirtualBox virtual machine. The single VM was configured to serve all five private repositories in turn, with each job preceded by an automatic rollback to a clean snapshot to prevent build contamination. GitHub's built-in ephemeral runner flag was insufficient on its own, as it does not restore the filesystem, prompting the team to write a custom REST API polling script as an external controller. Early stability issues, including zombie VirtualBox processes and a watchdog script that inadvertently blocked its own health checks, required additional fixes and led to a multi-day debugging effort the team plans to detail in a follow-up post.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Beyond Secure Flags: CSRF and Session Fixation Risks Every Developer Should Know

A technical explainer outlines two often-overlooked session security threats: Cross-Site Request Forgery (CSRF) and session fixation. CSRF exploits the browser's automatic cookie-sending behaviour, allowing attackers to trigger authenticated requests without ever stealing a session token; CSRF tokens paired with SameSite attributes are recommended defences. Session fixation takes the opposite approach, where an attacker plants a known session ID before a user logs in and retains access if the server does not replace that ID upon authentication. The recommended fix is to regenerate the session identifier whenever authentication state changes, such as at login or privilege escalation. Together, these vulnerabilities highlight that cookie security attributes alone are insufficient to protect the full session lifecycle.

0 comments Read more at DEV Community
0
ProgrammingHacker News ·

MiMo-v2.6-Pro Analyzed for Intelligence, Performance, and Cost

Artificial Analysis has published an evaluation of MiMo-v2.6-Pro, examining the AI model across intelligence, performance, and pricing dimensions. The analysis appears on the artificialanalysis.ai platform, which specializes in comparative assessments of large language models. The report aims to help users and developers understand where MiMo-v2.6-Pro stands relative to competing models. The post gained modest traction on Hacker News, drawing early community attention to the findings.

0 comments Read more at Hacker News
0
ProgrammingDEV Community ·

Developer Builds macOS App That Lets AI Agents Share a Canvas, Voice and Gesture Controls

A developer with a security background has spent three to four months building a macOS application called Starkomand, which allows AI agents to collaborate on a shared canvas for tasks like drawing diagrams, opening browser previews, and handing off work to one another. The app integrates voice control through NVIDIA Parakeet and GPT Realtime, and also supports hand gesture recognition via the device camera. Users can organize agents into separate workspaces for different projects, keeping personal and professional work isolated. Privacy was a core design priority, so all data and workspaces are stored locally on the user's Mac with no cloud storage, accounts, or additional API keys required. The tool is now publicly available at starkomand.com, with the developer inviting user feedback to guide future improvements.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Mercury 2.5 Tops LLM Speed Charts at 1,107 Tokens Per Second in September 2026

Inception Labs' Mercury 2.5 has emerged as the fastest large language model accessible via API as of September 2026, delivering 1,107 tokens per second by vendor report and 440 tokens per second at median latency per OpenRouter's third-party telemetry. The model uses a diffusion-based architecture that processes token blocks in parallel rather than sequentially, giving it a structural speed advantage over autoregressive rivals like GPT-5.6 Luna and Claude Haiku 4.5. Mercury 2.5 is priced at $0.20 per million input tokens and $0.75 per million output tokens, undercutting competitors on output cost, though an 80% launch discount expired on 8 September 2026. GPT-5.6 Luna remains the preferred option for general-purpose chat due to its larger context window and broader ecosystem maturity, despite its slower speed of 129 tokens per second. Claude Haiku 4.5 and Gemini 3.5 Flash-Lite occupy the middle ground, with Flash-Lite offering competitive speed at a higher output price and Haiku favoured for Anthropic's instruction-following behaviour rather than throughput.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

GLM-5.3-Flash Leads Agentic Coding as Top Open-Source Flash LLMs Split by Use Case

A September 2026 comparison of leading open-source flash-tier language models finds each excels in a distinct deployment scenario. GLM-5.3-Flash, a 320B mixture-of-experts model released by Z.ai on 26 August 2026, tops agentic coding benchmarks with a Terminal-Bench 2.1 score of 84.3 and DeepSWE v1.1 score of 63.4, attributed to its ability to maintain task state across multiple tool calls. DeepSeek V4 Flash, a 284B MoE model refreshed on 31 July 2026, is the most cost-efficient option for high-volume workloads under an MIT licence. MiniCPM5-2B, released on 7 September 2026, wins the on-device category with just 2.52 billion parameters and support for llama.cpp and Ollama. Qwen3.8-Flash-Next from Alibaba ranks close behind GLM on general intelligence and offers the longest native context window at 262K tokens, though analysts caution that several headline benchmark figures are vendor-reported and have scored lower in independent evaluations.

0 comments Read more at DEV Community
← NewerPage 1029 of 3194Older →