SShortSingh.
TopTechnologyAI & MLStartupsProgrammingScienceBusinessFinanceCrypto & Web3World

Programming

LatestTopDiscussed
0
ProgrammingDEV Community ·

SQL Tutorial: Identifying 'Power Purchasers' Using Two-Level GROUP BY Logic

A DEV Community article breaks down a hard-rated SQL interview problem tagged to Apple, focused on identifying 'power purchasers' in an app store dataset. A power purchaser is defined as a customer who made at least three in-app purchases in each of April, May, and June 2023. The solution requires two rounds of grouping: first by user and month to count qualifying months, then by user to confirm all three months are met. A HAVING clause is used instead of WHERE, since the filter depends on aggregated counts rather than raw row values. The final query joins results back to the users and purchases tables to return each qualifying user's ID, email, and total spending for the period.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Outside-In Monitoring Can Catch Website and Email Failures Before Clients Do

Expired SSL certificates, missing MX records, and lapsed domains can make websites and email addresses unreachable to customers even when internal systems appear fully operational. By the time a client reports such a failure, it has typically been discovered first by their own customer, causing reputational damage and eroding trust in the technical team or agency responsible. Agencies and MSPs need not directly manage the affected infrastructure to provide early warnings — spotting a DNS change or certificate failure allows them to alert the client and direct the issue to the right team before it escalates. The article argues that the solution is not more AI-driven alerts or bundled security tools, but focused outside-in monitoring that tracks public DNS records, served certificates, and domain expiry states. This approach checks what external users can actually reach, rather than relying on provider dashboards or internal configurations that may not reflect real-world accessibility.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

AegisCrawler open-sources governance-first browser scraping architecture

Developers behind AegisCrawler have open-sourced a web scraping framework designed to address long-term maintenance failures rather than just initial scraper creation. A Chrome extension records user interactions and DOM snapshots, which are processed by a deterministic rule generator to produce versioned, human-readable YAML scraping rules. Each rule must pass a replay verification step and receives a checksum-linked version history before it can be activated, ensuring full auditability. Optional LLM assistance is available strictly to propose rule patches, which require human approval and a security scan before taking effect — the model is never a live runtime dependency. The backend, built in Go with SQLite as a single binary, manages execution through lease-based job queuing, capped retries, tiered rate limiting, and per-site circuit breakers tied to immutable approved rule versions.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

AI Writes Frontend Code, But Developers Still Need Core Skills to Thrive

AI tools can now generate functional frontend components in seconds, prompting debate about what skills developers still need to master. Experts argue that foundational knowledge of HTML semantics, CSS layout, JavaScript behavior, and browser internals remains critical for evaluating and correcting AI-generated code. Real-world projects demand far more than writing code — they require understanding UX, architecture, accessibility, performance, and debugging. AI may suggest multiple fixes for a problem, but a developer who understands concepts like CORS or render pipelines can diagnose issues far more efficiently. Rather than replacing core knowledge, AI tools make it more important for developers to reason critically about the code they accept and ship.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Why AI Chatbots Confidently Choose the Wrong Tool When Options Are Ambiguous

When AI systems are connected to multiple external tools, a critical failure point emerges in how the model decides which tool to use for a given request. Unlike obvious requests, real-world user queries are often ambiguous enough to appear valid for more than one tool, causing inconsistent routing decisions. The consequences are frequently subtle — the wrong tool may still return a response, just a less accurate or less useful one — making such errors difficult to detect through standard monitoring. The stakes rise sharply when routing confusion involves tools with side effects, such as payment processing or booking changes, where an incorrect selection can trigger irreversible actions. Developers are urged to treat tool-selection logic as a critical system component rather than a trivial default, particularly when read-only and write-capable tools coexist.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

LLMs Belong Inside Recommendation Stacks, Not on Top of Them

Recent 2025-2026 research papers, including RecoChain and RRCM, argue that large language models should function within specific layers of a recommendation system rather than replacing the entire pipeline. A standard production recommender operates across four layers: data and features, candidate retrieval, ranking, and feedback, with LLMs contributing only to retrieval and semantic feature extraction. Strict latency requirements, typically around 100 milliseconds end-to-end, make it technically infeasible to place a generative model call in the critical request path for large catalogs. Engineers are advised to precompute or cache LLM outputs, such as item embeddings and query understanding, and always maintain a deterministic fallback when model calls fail. A commonly overlooked data practice is logging impressions alongside clicks, which is essential for computing click-through rates, correcting position bias, and enabling offline ranker evaluation.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

IQueryable vs IEnumerable: How Your LINQ Choice Decides Where Filtering Happens

In C#, IEnumerable and IQueryable share identical LINQ syntax but execute filtering in fundamentally different places — memory versus database. IEnumerable processes data inside the application after fetching all rows, while IQueryable builds an expression tree that gets translated into SQL and executed at the database level. A common anti-pattern involves returning IEnumerable from a repository method, which silently forces the entire table into memory before any filtering occurs, causing severe performance issues at scale. Developers are advised to keep IQueryable as long as possible in the query chain and only switch to IEnumerable via AsEnumerable() when applying custom C# logic that cannot be translated to SQL. Calling ToList() or AsEnumerable() marks the boundary where database execution ends and in-memory processing begins.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Developer sells polished personal finance PWA codebase due to lack of time to launch

A developer has completed building a personal finance progressive web app using React 19, TypeScript, Vite, and Firebase, featuring a Liquid Glass UI design system, PIN/biometric app lock, and a multi-currency real-time dashboard. Despite the app being fully functional and launch-ready, the developer cited an demanding full-time job as the reason they cannot commit to marketing or user acquisition. Rather than abandoning the project, they have decided to sell the full source code and intellectual property rights to an interested buyer. The app is described as ready for monetization, with potential to add a premium subscription tier or be packaged for iOS and Android app stores via Capacitor. The developer is inviting interested parties to reach out for a video walkthrough or access to a live demo account.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Jev Decision Model Claims 40–200x Speed Gain Over LLMs Across 7 Real-World Use Cases

TypeSafe launched Jev in mid-September, a structured decision model designed not to generate text but to return typed, confidence-scored answers to multi-choice questions. According to official figures, Jev processes repeated decision tasks 40 to 200 times faster and at a fraction of the cost compared to large conversational models. A developer named Nokka compiled over 100 real-world projects from the community list awesome-jev alongside 18 official TypeSafe recipes, organizing them into seven practical categories. Use cases span email triage, AI output validation, malware detection, multi-agent guardrails, and bulk content auditing, all relying on three core query types: binary confidence checks, single-choice selection, and scaled scoring. One user-reported benchmark showed classifying 1,000 emails across seven dimensions took six seconds at roughly nine cents, compared to five minutes and 62 cents using a leading chat model.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

React Is Not the Right Tool for Every Website, Developers Argue

A growing conversation in the frontend development community questions the default use of React for all web projects, regardless of complexity. React is well-suited for applications with dynamic UI needs such as e-commerce platforms, admin dashboards, and apps requiring shared state management. However, simpler sites like portfolios, small business pages, or static blogs can often be built effectively with plain HTML, CSS, and JavaScript. Using React for straightforward projects introduces unnecessary complexity, including build tools, dependency management, routing, and deployment configuration. The core argument is that architectural choices should match the actual problem at hand, not follow industry habit.

0 comments Read more at DEV Community
0
ProgrammingHacker News ·

Elektron Machinedrum Drum Machine Recreated as Browser-Based Tool

A developer has built a browser-based recreation of the Elektron Machinedrum, a classic hardware drum machine. The project is accessible online via a dedicated web page, allowing users to interact with the instrument without any physical hardware. The Elektron Machinedrum is a well-regarded piece of music production equipment known for its complex sound design capabilities. The project was shared on Hacker News, where it received modest attention with 7 points and no comments at the time of posting.

0 comments Read more at Hacker News
0
ProgrammingDEV Community ·

Why Offline Readiness in Mobile Apps Requires a Full State-Machine Design

A technical analysis published on DEV Community argues that building reliable offline support in mobile applications goes far beyond simply caching the last successful server response. The author contends that once an app depends on runtime configuration, developers must define a complete state machine covering states such as uninitialised, resolving, live-ready, fallback-ready, and unavailable. A key distinction is drawn between transient failures — like timeouts or dropped connections — which may justify serving cached data, and authoritative server responses like 404 or 410, which should invalidate the cache entirely. The piece also warns that cached data must be validated against its original source, age limits, and clock skew before it can safely be used as a fallback. The author recommends documenting the reasoning behind cache policies so future engineers can distinguish reliability-critical changes from superficial ones.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Unsupervised Learning Explained: Clustering and Dimensionality Reduction Basics

Unsupervised machine learning allows algorithms to find patterns, groups, and relationships in data without predefined labels or answers. It is particularly valuable when large datasets exist but lack annotated information, helping organizations uncover hidden insights. Clustering, one of its core techniques, groups similar data points together and has applications ranging from customer segmentation and fraud detection to healthcare analysis. Hierarchical clustering, which includes agglomerative (bottom-up) and divisive (top-down) approaches, organizes data into nested groups visualized through tree-like diagrams called dendrograms. DBSCAN is another clustering method that groups data based on density, treating isolated points as noise or outliers.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Four Ways ABAC Authorization Fails in Production and How to Fix Them

A software engineer running an ABAC authorization system for a healthcare platform serving over 25 million users across 1,000+ sites has outlined the real-world failure modes that emerge after deployment. Unlike common comparisons that stop at model selection, the article focuses on what actually breaks in production: stale attributes, policy rule explosion, missing enforcement points, and silent access decisions. Stale attributes are particularly dangerous because a correctly written policy evaluated on outdated data returns wrong decisions without any obvious error. The engineer recommends assigning a source of truth and maximum accepted age to every attribute, enforcing a fail-closed posture, requiring named owners and regression tests for all policies, and routing every code path through a single authorization gate. Comprehensive logging of every access decision is also stressed as non-negotiable, especially in regulated environments where audit trails are a compliance requirement.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Vercel Integrates with OpenAI Agents API for Serverless AI App Deployment

Vercel announced on September 10, 2026, an integration designed to simplify building and deploying applications using the OpenAI Agents API. Under this architecture, OpenAI handles the agent loop and session state, while Vercel connects each session to isolated sandbox environments for code execution. The setup follows a scale-to-zero model, meaning no always-on workers or containers are required, making it cost-efficient for bursty or asynchronous workloads. The OpenAI Agents API is currently in public beta, so developers should expect ongoing changes to its capabilities and interfaces. This shift signals a broader trend in AI engineering, where production systems are built around managing autonomous agent runtimes rather than simply calling language model endpoints.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Mercado Libre Blocks Public Search API; Memory Boost Lifts Scraper Success Rate to 90%

Mercado Libre has permanently shut down anonymous access to its public search API, returning a 403 Forbidden error consistently across all proxy types, including datacenter and residential connections. The HTML search page remains accessible but serves a proof-of-work challenge only to residential IPs, while other connections receive a deceptive 200 response containing a decoy asset bundle with no real results. Scraping attempts were failing not due to bot detection but because containers ran out of RAM mid-challenge, as Mercado Libre's search page renders a 3.3 MB DOM. Doubling Actor memory from 4 GB to 8 GB raised the challenge-clearance rate from 50% to 90%, with failures at lower memory caused by out-of-memory kills rather than blocks. The updated scraper now runs at 8,192 MB, clears the challenge once per session, and retrieves up to nine pages of results at a cost of $5.20 per 1,000 results.

0 comments Read more at DEV Community
0
ProgrammingHacker News ·

Grim Fandango's 1996 Internal Puzzle Design Document Surfaces Online

A puzzle design document created internally for the 1996 LucasArts adventure game Grim Fandango has been made available online as a PDF. The document offers a behind-the-scenes look at how the game's puzzles were planned and structured during development. It was shared via a game-focused archival site, drawing attention from gaming history enthusiasts on Hacker News. Such design artifacts are considered rare primary sources for understanding classic game development processes.

0 comments Read more at Hacker News
0
ProgrammingHacker News ·

Far-Left Party Wins Berlin Election on Housing Nationalisation Platform

A far-left party has won a Berlin election, according to a Reuters report dated September 20, 2026. The party ran on a pledge to nationalise housing in the German capital. Berlin has faced prolonged housing affordability pressures, making it a politically charged issue. Further details about the winning party, vote share, and coalition prospects were not available in the provided source text.

0 comments Read more at Hacker News
0
ProgrammingDEV Community ·

How Microsoft Foundry's Code Interpreter Actually Runs Python Inside a Sandbox

Microsoft Foundry's Agent Service includes a Code Interpreter tool that spins up an isolated Python container to perform deterministic computations, rather than relying on a language model to reason through calculations. The system addresses a core weakness of large language models, which are prone to errors in arithmetic, string manipulation, and large dataset operations. When an agent invokes the tool, Foundry lazily provisions a sandboxed container, stages files through Azure Storage, executes the code, and returns verified output with no network access to external infrastructure. Three key components govern the system: the tool definition, the container environment, and the session, which is a billable, time-limited runtime unit. Understanding the distinction between auto-managed and explicitly managed containers, as well as the difference between prompt agents and hosted agents, is critical for developers deploying the feature at production scale.

0 comments Read more at DEV Community
0
ProgrammingDEV Community ·

Atlassian Forge JSM Portal Panel Silent Submit Bug Traced to Wrong Payload Shape

Developers using Atlassian's Forge platform encountered a silent failure when submitting data via the jiraServiceManagement:portalRequestCreatePropertyPanel module, where issue properties returned as undefined without any error or warning. The root cause was an incorrectly shaped payload passed to the view.submit() call, which the @forge/bridge package's loosely typed submit signature — accepting any object — failed to catch at compile time. Atlassian's own manifest-reference page documents the required shape: an object with a fields array of key-value objects and a required isValid boolean. Developers are advised to consult this documentation before writing their submit handler, as the package types alone will not flag a malformed payload. A separate, still-unresolved challenge involves populating a real Jira custom field from the stored property value after submission.

0 comments Read more at DEV Community
← NewerPage 1075 of 3216Older →