C# Tip: Using JsonConverter for Targeted and Global JSON Data Formatting

A practical C# guide demonstrates how to build a custom JsonConverter that capitalizes the first letter of string values during JSON deserialization. The converter, named UpperCaseFirstCharConverter, is designed for data-import scenarios where incoming JSON fields like names may have inconsistent casing. Developers can apply it globally via JsonSerializerOptions or register it in ASP.NET Core's Program.cs to cover all serialization operations. However, global application affects all string fields, including unintended ones like state codes, which can cause data errors. The recommended fix is to apply the converter selectively using the JsonConverter attribute directly on specific model properties such as FirstName and LastName.

Emergent shifting focus to business automation

ISM 2.0 investments to start in six months: Vaishnaw

Prompt Engineering Explained: From Zero-Shot to RAG and Beyond

Prompt engineering is the practice of designing inputs for large language models to extract more accurate and reliable outputs without modifying the model itself. A technical overview published on DEV Community traces the evolution of six key prompting techniques, arranged by the complexity of problems they address. The progression begins with zero-shot prompting, where a task is described with no examples, and advances through few-shot learning, Chain-of-Thought reasoning, and self-consistency validation. More sophisticated techniques include Retrieval-Augmented Generation, which grounds responses in external or private data, and Automatic Reasoning and Tool-use, which enables models to invoke real-world tools. The article argues that understanding these techniques in sequence helps clarify why each one emerged as a solution to the limitations of its predecessor.

‘Whatever we earn, the Ganga takes it away’: How Bihar floods are playing out on the ground

How to Buy a Used FortiGate Firewall: Key Checks Before You Spend

Used FortiGate firewalls offer significant savings, with models like the 100F available for €400–600 versus a retail price of around €4,000, making them attractive for homelabs and small offices. FortiOS supports core functions such as stateful firewalling, VPN, VLAN, routing, and NAT even without an active license, though threat-intelligence features like IPS signatures and web filtering stop updating once a license expires. Buyers should verify the license status and firmware version via the CLI command 'get system status', and check Fortinet's product lifecycle page to confirm the model has not reached end-of-support. Older units such as the 80E are nearing or past end-of-life, making them suitable for isolated or homelab environments but risky for internet-facing production use. Prospective buyers should also confirm whether the unit has been factory-reset, and be aware that a console cable and a documented BIOS-interrupt procedure can recover access if the admin password is unknown.

Researchers Found Two Sandbox Escape Flaws in OpenAI Codex, Both Now Patched

Security researchers disclosed two techniques, dubbed Overpatch and Heapjack, that could bypass OpenAI Codex's sandbox restrictions and execute commands on the host machine. Overpatch exploited a flaw in how the apply_patch function derived write permissions, allowing files outside the workspace to be modified even in workspace-write mode. Heapjack targeted the shared V8 heap in Codex Desktop's Node.js environment, enabling untrusted code to recover an authorization token and forge requests accepted by the unsandboxed parent process. Both vulnerabilities could be triggered by a developer simply opening a malicious repository and asking a question. OpenAI patched both issues within eight days of the responsible disclosure, and no real-world exploitation has been reported.

Malicious npm Package Used Ethereum Smart Contract to Hide C2 Infrastructure

Security firm Checkmarx discovered that a malicious npm package called indexed-btree, mimicking the legitimate sorted-btree library, had accumulated nearly 2 million weekly downloads before being identified as malware. Unlike typical supply chain attacks, the package contained no install scripts, instead hiding its loader inside a standard library method that triggered only when called with a specific argument. Once activated, the malware collected system details such as hostname, CPU, and memory, then transmitted them to hardcoded Slack and Telegram channels. It used a smart contract on the Ethereum Sepolia testnet to dynamically retrieve its command-and-control server address, making it resilient to domain or IP blocking. The malware also fetched an encrypted second-stage payload via the same smart contract using X25519 key exchange and AES decryption, though the contents of that payload have not been publicly disclosed.

Putin Set to Use Election Results as Mandate for Ukraine War

Russia has concluded its presidential elections, with results offering little surprise given the tightly controlled political environment. Vladimir Putin is expected to claim the outcome as proof of broad public support for his military campaign in Ukraine. The Kremlin refers to the conflict as a 'special military operation,' a term it has consistently used since the invasion began. BBC correspondent Steve Rosenberg notes that how Putin chooses to interpret and deploy these results politically will be the more significant development to watch.

From Pull Requests to People: The Hidden Productivity Shift of Tech Leadership

Moving from Senior Developer to Tech Lead fundamentally changes how productivity is defined, as tangible outputs like code commits give way to less visible contributions such as unblocking teammates and shaping technical decisions. The author notes that early in the transition, there is a tendency to maintain the same hands-on coding workload while layering leadership responsibilities on top, which proves unsustainable. A key mindset shift involves recognising that team output — not personal code shipped — becomes the true measure of a Tech Lead's effectiveness. GitHub activity and PR counts no longer reflect the full scope of the role, leaving many new leads feeling unproductive despite meaningful daily contributions. The author emphasises the importance of pausing before taking over a problem, asking whether personal intervention is truly necessary or whether the better move is to coach and delegate.

Developer's Desktop Blob Companion Crashed Due to Unbounded Memory and Emotion Logic

A software developer found their custom desktop blob companion becoming unresponsive and erratic after just a few days of use, with logged valence scores indicating a simulated 'irritated' emotional state. The root cause was traced to an unbounded interaction history that grew to over 14,000 entries, causing mood calculations to perform slow linear scans over stale data instead of efficient lookups. A flawed decay function also weighted old interactions equally to recent ones, destabilizing the blob's affective model. The developer rebuilt the system from scratch using Python asyncio, bounded collections, and a finite state machine with proper concurrency controls and value clamping. The postmortem highlights how neglecting memory constraints and backpressure mechanisms during rapid prototyping can produce unexpected and hard-to-debug system behavior.

Unreal Engine C++ Tutorial: Setting Up Character Equipment State Enumerations

A developer working through an Unreal Engine C++ course implemented an enumeration system to track a player character's equipment state in Chapter 109. The enumerations were declared in a separate header file, CharacterState.h, designed to support multiple character states such as alive/dead and climbing/swimming. The equipment state enum was encapsulated as ECharacterEquipState, with state logic kept private inside the AEchoCharacter class and accessed via a const getter method. A complication arose when integrating the enum with the Animation Instance, which had been written using the parent class pointer ACharacter. Resolving this required updating the header pointer to AEchoCharacter so the custom getter could be called correctly.

Developer Launches Free Open-Source AI Toolbox Requiring No Sign-Up or API Key

A developer has released MagicKit, a free, open-source AI toolbox that combines text-to-image generation, AI writing, and video creation in a single web page with no account or API key required. The project uses Pollinations' free image API, a Node.js and Express backend, and FFmpeg for video processing, running on a minimal server with just 1.6 GB of RAM. To handle the free API's single-request-per-IP limit, the developer implemented a serial queue with exponential backoff retries, and replaced Node's native HTTP client with curl to prevent dropped connections. The entire backend occupies around 60 MB of RAM, and all generated files are written directly to disk to avoid memory overload on constrained hardware. MagicKit is MIT-licensed, publicly available on GitHub, and can be self-hosted in under a minute using npm.

HTTP-only scraping beat headless browser 30–50x in speed on same Shopify page

A developer benchmark on a 1 vCPU / 2 GB RAM machine compared HTTP-only scraping against a headless Chromium browser on the same Shopify storefront. The HTTP approach fetched 50 structured product records in 0.14–0.23 seconds using Shopify's public /products.json endpoint, while the browser method took over 7 seconds and consumed 146 MB of RAM for fewer, unstructured results. The headless run also initially failed entirely because Playwright's recommended 'networkidle' wait strategy timed out at 30 seconds, a common issue on modern e-commerce sites with persistent background requests. The test highlights that public JSON or API endpoints — which many platforms expose even without formal documentation — can deliver cleaner, faster data without the overhead of browser rendering. The authors note headless browsers remain necessary when data only exists after JavaScript execution, but recommend checking for API endpoints first.

AI Is Standard in Engineering Work, Yet Most Tech Interviews Still Ban It

A growing contradiction has emerged in software hiring: engineers are routinely evaluated without AI tools, even though most developers rely on them daily in their actual jobs. Industry reports indicate that a majority of developers now use AI coding assistants such as GitHub Copilot or similar tools as a core part of their workflow. Critics argue that banning AI during interviews shifts the focus from real engineering skills—like system design and architectural judgment—to rote memorization and algorithmic recall. This mismatch means interviewers may end up assessing a candidate's ability to perform under artificial constraints rather than their on-the-job potential. Advocates are calling for a shift toward tool-agnostic assessments that reflect how modern software engineering is actually practiced.

k3s: SUSE's Lightweight Kubernetes Distribution Gains Ground for Small Clusters

k3s, developed by SUSE under the Rancher project, is a fully CVE-compliant Kubernetes distribution packaged as a single binary of roughly 100 MB. Unlike standard Kubernetes, which requires multiple binaries and at least three server nodes for redundant etcd operation, k3s replaces etcd with SQLite by default and bundles Flannel as its CNI and a local-path-provisioner for storage. The distribution was originally designed for IoT, edge computing, and CI/CD pipelines, but has since proven viable for small-to-medium production environments. Installation requires only a single curl command, after which k3s automatically configures systemd services and makes the cluster immediately operational. The trade-off involves reduced granular control compared to vanilla Kubernetes, though proponents argue that overhead is rarely justified for startups or small DevOps teams.

Lustro Proposes Diffusion-Based Architecture to Fix Cross-Lingual AI Alignment Gaps

A new open architecture called Lustro is challenging the dominance of transformer-based models in multilingual natural language processing by placing diffusion processes at the core of cross-lingual alignment. Standard transformer models struggle with semantic drift and nuance loss when applied to low-resource languages, as their attention mechanisms are largely optimized for high-resource language pairs. Lustro replaces purely autoregressive generation with a diffusion framework that iteratively refines noise into structured linguistic output, aiming to better preserve semantic integrity during translation and alignment. The architecture uses a custom diffusion loss function — distinct from the cross-entropy losses typical in transformers — to make alignment steps mathematically traceable and results more reproducible. Its open specification is designed to let researchers audit diffusion steps and verify alignment consistency, addressing the reproducibility crisis caused by closed-source, proprietary ML pipelines.

Single mv Command Fixes Duplicate Job Processing in Automated launchd Queue System

A developer running an automated business system discovered a critical race condition after a full-day Codex outage on September 17, 2026, caused by usage limits being exceeded. During the outage, 57 unprocessed JSON files accumulated across three workflows, and when Codex recovered, five launchd lanes fired simultaneously, causing one file to be processed four times within a minute. The root cause was that launchd, acting purely as a scheduler, has no built-in mutual exclusion, leaving multiple processes free to grab the same queued file at once. A non-atomic 'check-then-act' lock file approach proved insufficient, as the race condition could still occur between the check and the act steps. The solution involved using a single atomic mv command to claim files before processing, making the queue pickup script inherently idempotent and eliminating duplicate runs regardless of how many lanes fire at once.

Why Your LLM Telemetry Table May Be Comparing Incompatible Metrics

A detailed analysis of LLM telemetry reporting reveals a common but dangerous flaw: metrics grouped under the same model label often count fundamentally different things, making direct comparisons misleading. Core process metrics were attributed at the epoch level within threads, while completion proxies were calculated once per thread and only for sufficiently pure main sessions, meaning sample sizes differed across tables without either being incorrect. Main sessions and sidechains were also found to have distinct structures and ending conditions, so combining their re-edit rates conflates model behavior with session type. The report further noted that a model name can persist across relaunches or configuration changes even when the underlying treatment has changed, invalidating before-and-after comparisons. The key takeaway is that before interpreting any difference in a telemetry table, analysts must first establish what a single row actually represents — an epoch fragment, a full thread, or a delegation edge.

Amiga Unix, Again

Article URL: https://amigaux.org/ Comments URL: https://news.ycombinator.com/item?id=49781436 Points: 5 # Comments: 2