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ProgrammingDEV Community ·

A Step-by-Step Checklist for Diagnosing Broken API Requests Using Browser Tools

A developer-focused guide outlines a structured approach to debugging common API request failures, including 401, 400, and empty response errors. The checklist recommends first isolating the request using curl to determine whether the issue lies in the API or the calling code. It then walks through interpreting HTTP status codes, decoding JWT tokens locally to check expiry and audience fields, and correctly encoding URL parameters. The guide also cautions against pasting live credentials or production tokens into online tools, advising the use of test values or local alternatives instead. Each step is paired with reusable code snippets to make troubleshooting faster and more systematic.

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ProgrammingDEV Community ·

Developer Releases Free Open-Source J1939 CAN Bus Emulator to Replace Costly Tools

A developer has published an open-source J1939 CAN bus ECU emulator on GitHub, designed to replace expensive commercial tools like Vector CANoe that can be prohibitive for startups and solo developers. The emulator is built on Python's python-can library and runs as both a CLI and a browser-based GUI compatible with Windows, Linux, and macOS. It supports core J1939 protocol features including PGN broadcast, DTC injection, VIN transmission, and address claiming, with configurable timing throughout. The tool can run inside a Docker container, making it compatible with CI/CD pipelines and cloud-based integration testing, and requires no physical CAN hardware thanks to virtual bus support. The project also includes a YouTube tutorial series and documentation aimed at helping developers learn J1939 protocol internals without prior deep expertise.

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ProgrammingHacker News ·

Most Data Centers Withhold Water and Electricity Consumption Figures

A majority of data centers are declining to disclose how much water and electricity they consume, raising transparency concerns. This information gap makes it difficult for regulators, researchers, and the public to assess the environmental impact of the rapidly growing industry. The refusals have been reported as of late September 2026, highlighting an ongoing accountability challenge. The lack of disclosure is particularly notable given increasing scrutiny over data centers' strain on local power grids and water supplies.

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ProgrammingDEV Community ·

Developer builds 175+ browser-based tools, shares hard lessons on Google indexing

A developer built PlainToolbox, a free collection of over 175 browser-only utilities including calculators, converters, and text tools, all running without a backend or user sign-up. The project uses a shared data-driven engine in Next.js, where each tool is defined as a single object that automatically generates its page, schema, sitemap entry, and FAQ content. Despite initial crawling, Google dropped nearly all tool pages, flagging them as 'Crawled, currently not indexed,' prompting the developer to remove generic tools, add answer-first content blocks, and avoid fake freshness timestamps. The developer noted that on a new domain, technical SEO only establishes eligibility to rank, while backlinks and real-world mentions carry far greater weight. Notably, the site's earliest traceable traffic came from AI assistants rather than traditional search, suggesting niche single-purpose pages may find an audience through that channel first.

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ProgrammingDEV Community ·

Shopify to Support Multiple Barcodes Per Variant, But API Still Returns One

Shopify is preparing to expand its barcode field to hold up to 20 values per product variant, a significant change from the current single-string limitation. The update matters because GS1 standards require distinct GTINs for each packaging level — individual units use EAN-13 barcodes, while cases and cartons require separate ITF-14 identifiers. A purchase order for 240 units, for example, correctly generates 240 item labels, 24 inner labels, and 2 carton labels — three different outputs from one input figure. Until the API is updated to return multiple values, developers are storing inner and carton GTINs in Shopify metafields, which hold the data but enforce none of the packaging hierarchy logic. Using a fallback GTIN across packaging levels is flagged as a critical error, since a mislabeled carton scanning as a single unit can cause downstream warehouse mistakes.

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ProgrammingDEV Community ·

Base Bridge Rated 8/10 Risk: Critical Bugs and Governance Flaws Flagged in $3.15B Protocol

A security assessment of Base Bridge, the primary asset-transfer gateway between Ethereum mainnet and the Base L2 rollup, has assigned it a cumulative risk score of 8 out of 10, classifying it as high risk. The bridge holds approximately $3.15 billion in total value locked, making it a high-value target for potential attackers. Researchers identified critical smart contract vulnerabilities including a re-entrancy flaw in the withdrawal function, missing input validation, and improper nonce handling that could enable replay attacks and double-spending. Governance weaknesses were also flagged, notably an upgradeable proxy contract lacking a multi-signature timelock and an admin key controlled by a single externally owned account. The assessment, prepared by a senior DeFi security researcher and dated September 30, 2026, also highlighted economic design gaps and insufficient monitoring as contributing factors to the bridge's overall systemic risk.

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ProgrammingDEV Community ·

How to Actually Clarify System Design Requirements in Technical Interviews

A software engineering guide published on DEV Community breaks down how to effectively clarify requirements during system design interviews, going beyond the generic advice of simply 'asking for requirements.' The piece uses a URL shortener as a running example to show how targeted questions — such as whether users are authenticated or what the read-to-write traffic ratio is — directly shape architectural decisions. The author distinguishes between functional requirements, which define what users can do, and non-functional requirements, which set performance, availability, and latency constraints. Rather than treating these as abstract checklists, the guide frames each question as a way to uncover consequences that drive design choices, such as separating analytics from the critical redirect path. The core takeaway is that good requirement clarification follows a chain of reasoning: requirement leads to consequence, which leads to architecture.

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ProgrammingDEV Community ·

How to Automate Git Commit Messages Using Custom AI Prompts

Developers often struggle with writing consistent, meaningful Git commit messages, which can result in cluttered and hard-to-navigate project histories. A tutorial published on DEV Community outlines how to set up a custom AI-powered tool to auto-generate commit messages based on staged code changes. The approach uses a command-line utility integrated with LLM APIs such as OpenAI, Anthropic, or Google Gemini, configured via environment variables or a local config file. A carefully crafted prompt file instructs the AI to follow standards like Conventional Commits, enforcing rules around message format, length, and tone. Developers can then review the AI-suggested message and commit it manually or via a shell variable for a more streamlined workflow.

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ProgrammingDEV Community ·

Kev: Open-Source Decision-First AI Model Runs Locally as Jev Alternative

Kev is an open-source project designed as a locally runnable alternative to Jev, an AI model built to make fast, structured decisions rather than generate text. Unlike Jev, which was not released as an open-source model, Kev allows developers to download, inspect, modify, and run it on their own hardware. A hands-on evaluation tested four Kev checkpoints — 0.5B, 0.6B, 0.8B, and 4B parameters — on Apple Silicon using a support-ticket workload, finding that larger models did not simply increase confidence but meaningfully shifted probability distributions, uncertainty, and latency. Kev takes a state and typed questions as input and returns structured decisions with associated probabilities, making it suited for application logic rather than conversational use. The project is available on GitHub and Hugging Face, with larger checkpoints such as Kev-8B and 9B planned for follow-up testing.

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ProgrammingDEV Community ·

A Minimal Go Loop Reveals How CPUs, Threads, and Memory Really Work

A developer running a near-empty infinite loop in Go observed surprising system activity — 100% CPU usage, 5 threads, 22,000 context switches, and over 400 GB of virtual memory — despite writing almost no code. The CPU spikes because the loop never blocks or sleeps, keeping the goroutine perpetually runnable and the processor constantly busy. The 5 OS threads were not created explicitly in the source code; they are part of the Go runtime's internal machinery, which manages goroutines, scheduling, memory, and garbage collection automatically. Above the Go runtime sits the OS scheduler, which arbitrates CPU access among all threads from every running process, causing the thousands of context switches observed. The experiment illustrates that a Go program is far more than its source code — the runtime and OS together handle the low-level work that developers never have to write themselves.

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ProgrammingDEV Community ·

Five Enterprise AI Gateways That Lead Multi-Model Routing in 2026

As enterprise AI deployments grow more complex, AI gateways have become critical infrastructure that sits between applications and multiple LLM providers, centralizing routing, governance, and observability. No single model can optimally balance cost, speed, and capability for every task, making multi-model routing strategies essential for production systems. Bifrost leads for high-performance, self-hosted or in-VPC deployments, while LiteLLM is favored for its broad provider support in open-source environments. Kong, Cloudflare, and Vercel serve teams already embedded in their respective ecosystems, offering AI routing at the API or edge layer. Key evaluation criteria for enterprises include routing strategy, deployment model, latency overhead, governance controls, and observability features.

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ProgrammingDEV Community ·

How a Single Malicious Commit Can Compromise a Vite-React-TypeScript App

A security analysis explores what happens when a malicious commit reaches production in a Vite, React, and TypeScript frontend application. Once hostile JavaScript is deployed, it runs under the site's origin in every affected visitor's browser, giving it the same privileges as the legitimate app — enabling keystroke capture, storage access, API calls, and data exfiltration. Beyond the browser, malicious repository code can also execute during CI/CD build steps, potentially exposing secrets, cloud credentials, and deployment tokens through npm lifecycle hooks. The research outlines a tiered threat model ranging from read-only repository access to full backend compromise, depending on CI permissions and API security. The findings serve as a threat-modeling and audit guide for frontend teams to assess and reduce their supply-chain exposure.

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ProgrammingDEV Community ·

How Spain's DNI and NIE check letters are calculated using modulo 23

Spanish national ID numbers (DNI) include a final control letter derived from a simple mathematical operation: dividing the 8-digit number by 23 and mapping the remainder to a fixed 23-letter table published by the Interior Ministry. Four letters — I, O, Ñ, and U — are excluded from the table to avoid visual confusion and to keep the total at 23, a prime number that enables error detection. Foreign resident IDs (NIE) follow the same logic, but their leading letter (X, Y, or Z) is first substituted with 0, 1, or 2 respectively before applying the same modulo calculation. The current NIE format was standardised by Order INT/2058/2008, which introduced the nine-character structure and defined the sequential use of Y and Z as the X series became exhausted. The control letter can catch single-digit typos and transposition errors, though it does not verify whether the document actually exists in any official registry.

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ProgrammingDEV Community ·

Developer Completes Spring Security Module in Open-Source Spring Learning Project

A developer has completed Module 01 on Spring Security as part of 'Spring by Example V2', an open-source project designed to teach Spring framework concepts through small, focused code examples. The project aims to cover a broad range of the modern Spring ecosystem, including Spring Data, Reactive Spring, Spring Batch, Spring AI, and more. Module 01 addresses key Spring Security topics such as authentication, authorization, JWT, OAuth2, CSRF protection, and session management. The developer's stated goal is not just to demonstrate features in isolation, but to show how the various components interconnect within the security filter chain. With Spring Security now complete, the project will move on to Module 02, which will focus on Spring Data.

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ProgrammingDEV Community ·

Solo Tech Founder Delegates Entire Marketing Operation to AI Agent

A solo technical founder with no marketing background has handed his go-to-market operations to a persistent AI agent called Muse to promote VayReach, his WhatsApp follow-up CRM for real-estate teams. The agent runs daily scheduled tasks including LinkedIn publishing, Instagram content scheduling, lead prospecting, and outreach drafting across NCR cities, building a 464-row prospect sheet without direct founder input. A strict approval boundary is enforced, meaning the agent never sends direct messages, connection requests, or emails without explicit human sign-off. The founder credits the setup with saving him from a potential WhatsApp number ban and maintaining consistent marketing output he could not sustain alone. He acknowledges the system has yet to convert customers and that it provides consistency rather than a substitute for product quality or human judgment.

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ProgrammingDEV Community ·

Hybrid Search RAG Cuts Missed Retrievals by 30–40% in Internal Doc Systems

A production guide published on DEV Community details how combining vector and keyword search in a Retrieval-Augmented Generation (RAG) pipeline significantly improves retrieval accuracy over internal documents. The approach runs dense vector search (embeddings) and sparse keyword search (BM25 via Elasticsearch) in parallel, then fuses their normalized scores to surface the most relevant results. One team at LogicLoop reported a 22% improvement in MRR@10 after switching from vector-only to hybrid search on their engineering wiki, with benchmark tests across 500,000 Confluence pages and Jira tickets showing hybrid search achieving an MRR@10 of 0.50 versus 0.41 for vector-only. The tradeoff includes roughly 30ms of additional latency and doubled storage overhead from maintaining two indexes simultaneously. A notable edge case was identified for very short queries of one to two words, where keyword search tends to dominate, prompting the team to route such queries to keyword-only search via a simple length check.

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ProgrammingDEV Community ·

Top LLM Observability Platforms for Enterprises Compared Ahead of 2026

As enterprises scale AI agents from prototypes to production, standard monitoring tools have proven inadequate for tracking the unique challenges of large language model applications. A new category of specialized LLM observability platforms has emerged to provide visibility into prompts, responses, latency, cost, and output quality. Key evaluation criteria for these platforms include end-to-end tracing, root cause analysis, data curation, and enterprise-grade security and scalability. Leading options in 2026 include Maxim AI, LangSmith, Langfuse, and Arize, each offering distinct strengths suited to different team needs and existing toolchains. The right platform choice ultimately depends on an organization's scale, technical ecosystem, and the complexity of the AI agents it deploys.

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ProgrammingDEV Community ·

How to Connect Power BI to Local and Cloud PostgreSQL Databases via Aiven

Power BI can be connected to PostgreSQL databases both locally and via cloud-hosted services like Aiven, following a structured setup process. For local connections, users configure DBeaver with localhost credentials before linking Power BI Desktop through the Get Data option using the default port 5432. Cloud connections through Aiven require an additional SSL step, where a CA certificate downloaded from the Aiven dashboard must be imported into Windows' Trusted Root Certification Authorities. Once the certificate is successfully imported, the Aiven cloud database behaves similarly to a local connection within Power BI. After either setup, users can model data, write DAX formulas, and build live dashboards reflecting the latest database content.

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ProgrammingDEV Community ·

How to Build Production-Ready AI Agents with FastAPI and OpenAI SDK

A developer with over a year of running AI agents in production has shared a practical guide to building them using FastAPI and the OpenAI Python SDK. The tutorial covers a minimal FastAPI setup that accepts prompts and returns OpenAI responses, handling common errors like rate limits and timeouts. It then demonstrates how to enable tool use, allowing the agent to call external functions such as internal APIs, with the OpenAI SDK managing the function-calling loop. The guide also addresses stateful agents, recommending Redis for persisting chat history and user preferences across sessions using Pydantic models. The author emphasizes avoiding manual state machine implementations in favor of letting the SDK handle the tool call and response cycle for reliability.

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ProgrammingDEV Community ·

Power BI Basics: How Relationships, Schemas, and Joins Work Together

A beginner Power BI user shares lessons learned after struggling to connect multiple tables in their first multi-table assignment. Unlike Excel's single-sheet approach, Power BI encourages splitting data into separate tables linked by common ID columns, reducing repetition and mirroring real database design. Relationships are created in Model view by connecting shared columns, with one-to-many being the most common type. The star schema — one central fact table surrounded by dimension tables — proved simpler to manage than the more complex snowflake schema for beginner projects. In Power Query, joins like Left Outer and Inner merges allow tables to be combined before loading into the model, with Left Outer recommended as a safer default to avoid unintended data loss.

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