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ProgrammingDEV Community ·

Zerodha, Upstox, Dhan, Angel One or Groww: Which Trading App Suits You in 2026?

India's five leading discount brokers — Zerodha, Upstox, Dhan, Angel One, and Groww — all charge zero brokerage on equity delivery and ₹20 per order for futures and options in 2026. The key differences lie in API access, platform quality, and target user profiles rather than headline brokerage rates. Zerodha leads on education and charting tools but charges ₹500–2,000 per month for its Kite Connect API, while Dhan and Angel One offer free API access, making them attractive for algorithmic traders. Hidden costs such as depository charges of ₹13–15 per scrip per sell, call-and-trade fees, and securities transaction tax can significantly erode returns, especially for active traders. Beginners are generally steered toward Zerodha or Upstox for stability and ease of use, while options and algo traders may find Dhan the most cost-effective choice.

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ProgrammingDEV Community ·

Why SVG Path Interpolation Fails for Rotating Shapes and How to Fix It

Design engineer James Coombs spent a week diagnosing why a seemingly straightforward SVG animation between two illustration states produced broken, exploding-fragment visuals. The core problem is that interpolating raw path coordinates works for translations but fails for rotations, since points should travel arcs governed by sine and cosine, not straight lines. Rather than animating hundreds of individual coordinates, Coombs found the correct approach is to describe the entire rigid motion — rotation, scale, and translation — as a single transform matrix applied to the whole shape group. He solved this using a least-squares fit based on the Procrustes shape-alignment problem, requiring only four unknowns and no external math library. He also flagged a separate build-pipeline issue that corrupts SVG shapes before any morphing library even processes them, compounding the visual breakdown.

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ProgrammingDEV Community ·

Why AI Agents Cannot Simply Set a Status in Jira, Linear, or GitHub

Work tracking tools like Jira, Linear, and GitHub are increasingly treating AI agents as first-class entities, but writing to these systems is far more complex than updating a simple status field. GitHub Issues use a flat open/closed model with no native concept of epics or workflows, meaning any richer structure must be emulated through labels — a silent convention invisible to outside readers. Linear's workflow states are team-specific and typed via an unversioned string field, making it impossible to map abstract statuses like 'In Review' to a universal type without referencing state IDs per team. Jira goes furthest: moving an issue requires first querying permitted transitions — which vary by project, issue type, and current state — and then posting the correct transition ID, sometimes with additional required fields attached. Agents that assume status updates are simple field writes risk partial failures and broken workflows across all three platforms.

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ProgrammingDEV Community ·

How EU AI Act Compliance Is Reshaping TypeScript Autonomous Agent Architecture

As developers increasingly build autonomous AI agents that can browse the web, manipulate files, and execute network tools, these systems have crossed from simple text generators into active operational agents with real-world impact. The European Union AI Act now places such systems under strict legal mandates, particularly when deployed in high-risk domains like employment, finance, critical infrastructure, or law enforcement. Developers using TypeScript-based agentic runtimes combined with the Model Context Protocol and vision-driven computer-use frameworks must treat compliance as a foundational architectural requirement, not an optional add-on. The regulation demands structural safeguards such as continuous monitoring, real-time data redaction, and mandatory human oversight to prevent failures like database corruption or PII exfiltration caused by hallucinations or prompt injection. Industry analogies to industrial robotics safety standards and corporate delegated authority frameworks help illustrate why hard guardrails must be embedded at both compile time and runtime.

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ProgrammingDEV Community ·

MCP Protocol Drops Session IDs, Shifts State Visibility to the Model

The July 2026 revision of the Model Context Protocol eliminated the initialize handshake and Mcp-Session-Id header, making every request self-describing by embedding protocol version and client info directly in each call. Previously, session state was negotiated once at connection time and held invisibly inside a server process, entirely out of reach of the AI model doing the reasoning. Under the new design, servers that need to track state across calls return an explicit handle — such as a basket_id — as a tool result, which the model then passes back as a normal argument on subsequent calls. This means stateful workflows are still supported, but the state is now visible to, and reasoned over by, the model rather than hidden in the transport layer. A notable side effect is that stateless requests can be routed to any server instance, making MCP servers compatible with serverless infrastructure and standard load balancers.

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ProgrammingDEV Community ·

Meta Releases Muse Glimmer, a 30B Open-Weight AI Model Designed for Local Agents

Meta Superintelligence Labs released Muse Glimmer on August 10, 2026, a 30-billion-parameter AI model optimized for local agent workflows running on consumer hardware. The model is open-sourced under the Apache 2.0 license, with weights available on Hugging Face and integrations for llama.cpp, MLX, and ExecuTorch expected shortly. Unlike cloud-dependent AI agents, Muse Glimmer operates offline on a single consumer GPU in a Mac or PC, addressing privacy concerns and eliminating per-token API costs. The model was trained in three phases — pre-training via logit distillation, mid-training on agent-heavy data, and post-training using supervised fine-tuning and reinforcement learning. Key capabilities include reliable tool calling, multi-step reasoning, long-context memory, and the ability to recover from failed tool calls rather than halting execution.

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ProgrammingDEV Community ·

Claude Opus 5 Silently Resolves Conflicting Instructions Based on File Position

When an AI agent like Claude encounters two contradictory instructions in a configuration file, it silently commits to one without issuing any warning to the user. Controlled experiments show that position within the file is the dominant factor — the rule placed lower in the file wins roughly 90% of the time, regardless of which rule the developer intended to take priority. Unlike older Claude models that would inconsistently flip between conflicting rules across runs, Opus 5 picks one side and sticks to it every time, eliminating the only visible symptom that a conflict existed. This behavioral change means developers lose the run-to-run inconsistency that previously hinted something was wrong, making silent instruction conflicts harder to detect. The practical risk is that an exception or override rule placed high in a file may be completely ignored by the model, with no error or alert to indicate the problem.

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ProgrammingDEV Community ·

Walter MCP Lets Developers Replace AI Humanizer Boilerplate With a Single Prompt

Developers building AI content pipelines traditionally write significant boilerplate code to handle authentication, retry logic, rate limiting, and response parsing when integrating humanizer APIs. Walter's Model Context Protocol (MCP) server, connected to an LLM like Claude, aims to eliminate this overhead by shifting orchestration logic away from the developer's codebase. Instead of maintaining custom integration code, developers can instruct the LLM in plain language to draft, detect, and humanize text in a single prompt. The MCP server is configured once with a URL entry, after which the host manages authentication and retries at the protocol level rather than requiring per-request handling in application code. The approach is positioned as reducing long-term maintenance burden for teams running content pipelines at scale.

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ProgrammingHacker News ·

Security Researchers Demonstrate AI Hijacking Attack on Zoom's AI Features

Security researchers at PromptArmor have disclosed a vulnerability affecting Zoom's AI capabilities. The attack method allows a malicious actor to take control of Zoom's AI assistant through a technique known as prompt injection. By embedding hidden instructions into meeting content, an attacker could manipulate the AI into performing unintended actions or leaking sensitive information. The findings were published on PromptArmor's website and have drawn attention from the cybersecurity community on Hacker News.

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ProgrammingDEV Community ·

GitHub Repo Offers Growth Hacking Strategies Tailored for AI Agents

A new GitHub repository called 'awesome-growth-hacking-skills' has emerged, outlining growth hacking strategies designed specifically for AI agents like ChatGPT and Claude. The project aims to help developers bridge the gap between technical AI capabilities and real-world business objectives such as user engagement and sales growth. It has attracted notable interest, accumulating 817 stars on GitHub. Unusually, the repository is built using Shell scripting, a language more commonly associated with workflow automation than AI development, which some may find limiting. The project reflects a broader trend in the developer community toward combining marketing thinking with technical AI expertise.

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ProgrammingDEV Community ·

OpenAI Launches Daybreak to Cover Full AI Cybersecurity Cycle From Detection to Fix

OpenAI announced Daybreak in May 2026, a cybersecurity initiative that uses frontier AI to handle the complete defensive workflow — from vulnerability discovery and exploit validation to patch generation and remediation verification. The program bundles several components, including GPT-5.5-Cyber, Codex Security, and Daybreak Red, each targeting a distinct stage of the security process. A collaboration with Trail of Bits called Patch the Planet aims to deliver fixes directly into open-source projects, while a Cyber Partner Program allows trusted vendors to integrate Daybreak capabilities into their own security products. OpenAI has already used the initiative to identify and responsibly disclose previously unknown vulnerabilities in major software engines, including Google's V8 JavaScript engine. The initiative is designed to address a common gap in AI-assisted security, where a high volume of alerts holds limited value unless teams can also reliably prioritize and resolve the underlying issues.

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ProgrammingGitHub Blog ·

GitHub Releases Copilot SDK for Java, Enabling Native AI Integration

GitHub has launched a Copilot SDK tailored specifically for Java developers. The SDK allows enterprise Java developers to integrate GitHub Copilot directly into their applications using idiomatic Java code. It supports modern Java features such as annotations and virtual threads, making AI-driven functionality more accessible within the Java ecosystem. The release is aimed at helping enterprise teams build Copilot-powered workflows natively in Java.

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ProgrammingDEV Community ·

Electrical Engineer Joins DEV to Share Battery Safety and Thermal Management Insights

Mohammad Rezwan Khan, an Electrical R&D Engineer and PhD researcher specializing in battery thermal management and lithium-ion safety, has introduced himself to the DEV Community. His work sits at the intersection of electrical engineering, thermal science, controls, data, and software. Khan plans to publish practical posts on battery systems, energy storage, modeling, and AI-assisted engineering tools. His stated goal is to make technical content accessible to both domain specialists and developers from other fields. He is also seeking to connect with others working on batteries, embedded systems, and adjacent engineering disciplines.

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ProgrammingDEV Community ·

Meta and RealPage Releases Highlight Where AI Agent Decision Logic Should Reside

Meta released Muse Glimmer, a 30-billion-parameter open model built to run on consumer hardware for local, always-on agent workflows supporting tool use and long-running tasks. Separately, enterprise software firm RealPage launched the Lumina AI Suite, which combines AI agents with a governed knowledge graph and institutional intelligence for real-estate operations. Together, the two releases highlight a growing architectural question: as AI models become deployable anywhere, where should an organization's actual decision-making criteria be stored and enforced. Analysts and developers are drawing a distinction between an agent knowing organizational facts and an agent knowing how the organization makes judgments, such as when to approve a vendor or escalate a decision. A proposed framework called the Judgment Pack Specification aims to make organizational decision criteria explicit and separately owned from both data infrastructure and the underlying AI model.

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ProgrammingDEV Community ·

Developer Completes Network Layer for Custom Java GUI Framework

A developer building a GUI framework for Java has completed the network layer as part of the project's second devlog. The layer serves as an abstraction over REST and WebSockets, allowing seamless switching between the two communication protocols during an active session. It treats both connection types as a single logical connection, firing connect and disconnect events only when a user's last remaining link to the server is established or closed. The implementation is designed to be swappable, with a Jetty-based server and a mock version for testing already created. Although it will largely remain internal to the framework, the network layer is built as a standalone module that can be reused in other projects requiring protocol-agnostic user connections.

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ProgrammingDEV Community ·

Developer warns how layered Google account security can lead to a lockout risk

A software developer shared how two decades of progressively hardening his Google account — adding two-factor authentication, app-based codes, and a KeePass password manager — inadvertently created a dangerous circular dependency. Because all passwords are stored in a KeePass vault synced to Google Drive, and the vault's access relies on the Google account itself, losing the phone could block entry at every level. His phone serves as the primary 2FA device not only for Google but also for his mobile carrier account, meaning a lost device could make reclaiming even his phone number nearly impossible. The situation highlights a growing risk for security-conscious users: stacking authentication layers without a tested recovery plan can make accounts harder for owners to access than for attackers. The developer used the experience as a cautionary reminder to audit recovery options before a crisis, not after.

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ProgrammingDEV Community ·

DockAMP Launches Browser-Based Docker Web Stack Manager with Multi-Server Support

DockAMP is a browser-based web stack management tool available on Docker Hub that allows users to manage Apache or Nginx servers with automatic PHP version discovery and support for MySQL, MariaDB, and PostgreSQL databases. The platform offers a management interface in both English and German, along with integrations for Nginx Proxy Manager, phpMyAdmin, and Adminer. It includes features such as live visitor monitoring, container log overviews, file browsing, and direct file uploads through the browser. DockAMP also handles backup and restore operations for Docker volumes and host-mounted storage, covering configuration, site files, and database data. Additionally, the tool automatically exports Docker Compose files, ensuring containers can be run independently without DockAMP if required.

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ProgrammingDEV Community ·

How Manual Payment Capture Works in Production: Buffers, Splits, and Hold Limits

Manual payment capture in production involves authorizing an estimated amount and capturing the final amount later, with the gap between the two being a common source of bugs. Developers are advised to authorize a buffered amount above the estimate to absorb minor variances and avoid triggering a second payment step at fulfillment. When store credit and card payments are split, the card portion must meet Stripe's per-currency minimum or the transaction fails, so the split should be rebalanced before the API call is made. On capture day, three outcomes are possible: void if no card charge is needed, partial or full capture if the final amount is within the authorized limit, or a fallback flow if the final total exceeds the buffer. Card authorization holds expire automatically after roughly seven days, making timely capture essential to avoid failed settlements.

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ProgrammingDEV Community ·

Developer builds Chrome extension to help non-native speakers soften code review tone

A developer whose first language is not English realized their blunt code review comments were being perceived as rude, even when no offense was intended. Comparing their own terse remarks to more diplomatically worded feedback from a native-English-speaking colleague highlighted the gap in perceived professionalism. To address this, the developer began using AI tools to rewrite messages, but found the constant tab-switching disruptive to their workflow. They built a Chrome extension called Softly, which rewrites text directly inside any text field using selectable tones suited for PR reviews, team chats, or formal communication. The tool is now available on the Chrome Web Store and, according to the developer, also reduced self-censorship by lowering the effort cost of writing in English.

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ProgrammingDEV Community ·

NexFlow's First CLI Should Validate Manifests, Not Execute Agents

The NexFlow project is proposing a validation-only command-line interface (CLI) as its first tool, deliberately excluding any agent execution or runtime capabilities. Draft RFC-0011 outlines four commands — validate, inspect, graph, and init — each designed to help contributors review and trust manifest definitions without triggering workflows or provider calls. The rationale is that launching agents too early would lock in implementation choices before the specification has fully matured, making defaults difficult to reverse. Currently, the NexFlow repository covers 17 schema-backed manifest kinds and 113 schema-backed manifests, with structural validation implemented but semantic checking still partial. The proposed CLI aims to put existing checks behind a stable interface and improve diagnostics while remaining transparent about what it does not verify.

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