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ProgrammingDEV Community ·

How open-source projects can achieve SOC 2 readiness without spending a dime

Achieving SOC 2 compliance is typically associated with costly vendors and consultants, but the P31 approach offers a zero-budget alternative for open-source projects. The framework is built on four pillars: an automated evidence collector, a CycloneDX 1.5 Software Bill of Materials (SBOM), a public Trust Center, and artifact signing using an in-house dual scheme. Each component is script-driven, allowing teams to map and document controls without third-party tools. Importantly, this approach delivers SOC 2 readiness rather than formal certification, which still requires an official audit. The method is aimed at open-source maintainers seeking to demonstrate security and compliance posture on minimal resources.

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ProgrammingHacker News ·

Finance veteran builds local-first AI workflow tool Ekselio for accounting tasks

KD, a finance and M&A professional with 20 years of experience, has launched Ekselio, an AI-powered tool designed to automate finance workflows using a local-first architecture. Unlike typical AI coding tools, Ekselio runs workflow execution directly in the browser without repeated LLM calls, keeping infrastructure costs low. The platform supports saved workflows that can be re-run on demand, and outputs audit-ready Excel data packs with M code for full reproducibility. It integrates with QuickBooks Online, the FRED macroeconomic database covering roughly 800,000 data series, and live stock data. The project is currently a work in progress, built as a side project, with the creator seeking user feedback on architecture and usability.

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ProgrammingDEV Community ·

KV Cache, Not Model Size, Is Why Your Local LLM Crashes Mid-Conversation

Developers running large language models locally often encounter out-of-memory crashes not at startup but deep into a conversation, which can make the failure seem random or unexplained. The root cause is a second, largely overlooked memory consumer called the KV cache, which grows with every token the model reads or generates during a session. Most setup guides focus only on fitting the model's weights into available VRAM — a fixed number calculated from parameter count and quantization level — while ignoring the KV cache entirely. Unlike model weights, the KV cache is dynamic and expands continuously as the conversation lengthens, eventually exhausting the GPU memory that appeared sufficient at load time. Understanding and budgeting for KV cache growth alongside model weights is essential for stable long-context inference on consumer hardware.

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ProgrammingDEV Community ·

Scripta 3.4.7 lets macOS users schedule local meeting recordings with no cloud involvement

Scripta, a macOS app that records and transcribes meetings entirely on-device, has released version 3.4.7 introducing a scheduled recording feature. Users can now set a meeting title, start time, and duration in advance, allowing the app to automatically begin and stop audio capture without manual intervention. All transcripts and session metadata remain stored locally, consistent with the app's privacy-first design, and no data is sent to external servers. The scheduler runs within the app process itself, meaning Scripta must be open at the scheduled start time; if it is not, a local notification prompts the user to launch it. Features such as calendar import, multi-device sync, and background daemon recording are planned for future releases.

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ProgrammingHacker News ·

Researcher Trains AI World Model to Play Pokemon From Scratch

A developer has published a technical blog post detailing an experiment in training an AI world model to play the classic Pokemon video game. World models are AI systems that learn an internal representation of an environment to predict future states and make decisions. The project explores how such a model can learn game mechanics, navigation, and strategy through interaction with the Pokemon environment. The work contributes to ongoing research into model-based reinforcement learning applied to complex, structured games. The post was shared on Hacker News, where it attracted early discussion from the AI and developer community.

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ProgrammingDEV Community ·

How SaaS Teams Should Build Durable Retry and Failure Records for Background Jobs

A technical guide recommends that SaaS engineering teams treat each scheduled or queued job execution as a durable evidence record rather than a simple log entry. The approach calls for assigning stable identifiers to logical jobs, individual attempts, and customer operations separately, then writing state transitions and sanitized error summaries to a persistent store like Postgres. Retries should append new attempt rows rather than overwrite previous failure data, preserving a full ordered history for incident investigation. Security considerations are central: sensitive data such as tokens, passwords, and database credentials must never be stored in error records, in line with OWASP logging guidance. The design also needs to account for data retention and deletion obligations under regulations like GDPR, requiring clear classification of operational evidence versus customer payload data.

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ProgrammingDEV Community ·

How Temperô debugged a weeks-long iFood integration mystery involving missing cancel events

Temperô, a multi-tenant SaaS platform for restaurant management built on Node/TypeScript and PostgreSQL, developed a direct integration with the iFood marketplace to automatically route delivery orders into its kitchen and payment workflows. Rather than using webhooks, the system relies on iFood's polling API, queried every 15 seconds via a Node.js setInterval loop with an overlap-prevention flag. The team chose iFood's 'Centralised' credential model, requiring a mid-project refactor of the OAuth2 token cache from per-unit to a single in-memory store with both proactive and reactive renewal logic. Menu mapping was deferred, so iFood order items enter the system without an internal product ID, using names and prices directly from the payload. The article details several bugs encountered during the build, including a prolonged investigation into why order-cancellation confirmation events sometimes never arrived.

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ProgrammingDEV Community ·

How Temperô integrated iFood orders into its restaurant SaaS — and the bugs found along the way

Temperô, a multi-tenant restaurant management SaaS built on Node/TypeScript and PostgreSQL, set out to automatically route iFood marketplace orders into its internal kitchen, payment, and delivery workflows without requiring staff to operate two systems simultaneously. Because iFood does not support inbound webhooks, the team implemented a polling mechanism that calls iFood's Order API every 15 seconds using a flag-guarded setInterval loop to prevent overlapping executions. The platform adopted iFood's 'Centralised' credential model — a single OAuth2 client_credentials token filtered per merchant — which required mid-project refactoring of the token cache from a per-unit to a shared in-memory store. Version one of the integration covers delivery orders only; takeout and dine-in requests arriving via the marketplace are automatically cancelled, and menu items are ingested using name and price directly from the payload rather than being mapped to Temperô's internal catalogue. The article also details a prolonged investigation into why cancellation-confirmation events occasionally never arrived, tracing the issue to subtle differences between the iFood event fields 'code' and 'fullCode'.

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ProgrammingDEV Community ·

How to Track DORA Metrics and SLOs Using Only Cloudflare Workers

A Cloudflare Workers-based approach allows engineering teams to monitor DORA metrics and Service Level Objectives without relying on external tools like Prometheus or third-party observability platforms. The setup logs every API request — including method, route, and status code — into a local database table called api_usage. SQL queries then roll up that data to calculate availability and error rates against a 99.9% uptime SLO, which permits roughly 43 minutes of downtime per 30-day window. Latency is tracked at the p95 and p99 percentiles, with Cloudflare cron triggers automating the rollup and feeding results to a status page. The author recommends starting with three core SLOs — availability, p95 latency, and p99 latency — treating everything beyond that as optional refinement.

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ProgrammingDEV Community ·

Dev proposes 'Spoon Dial' to make financial UIs accessible for neurodivergent users

A developer has proposed a cognitive-capacity-aware design model called the 'Spoon Dial' aimed at making financial dashboards more accessible for neurodivergent users. The concept draws on spoon theory, using a 0–5 scale to represent a user's available mental energy at any given time. When capacity is low, the interface simplifies to show only the three most essential widgets, reducing cognitive overload through progressive disclosure. The implementation relies on a small set of CSS custom properties and a single state machine, making it relatively lightweight to build. The proposal challenges the density-first approach common in mainstream fintech design, which typically assumes users are operating at peak attention.

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ProgrammingDEV Community ·

BitMEX and CoinEx Closures Expose Critical Gaps in Trading Bot Design

BitMEX halted all trading on September 23, 2026, while CoinEx announced on September 15 that it will shut down on December 22, marking two major crypto exchange closures within days of each other. Both exchanges reported fully backed reserves and kept withdrawals open, making the wind-downs orderly for human users. However, developers running automated trading bots or treasury scripts face a series of cascading API failures as each closure moves through phases such as reduce-only mode, product halts, deposit freezes, and final account closure. The most costly risk for automated systems is not a failed withdrawal but a script that continues sending funds to deposit addresses that no longer credit them. Developers are advised to implement kill switches for deposits, treat unrecognized API rejection codes as alerts rather than retries, and continuously sweep excess funds to self-custody wallets to reduce exposure to any single venue.

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ProgrammingDEV Community ·

Google Expands Gemini 3.8 With Expressive TTS, Live Avatar and Notebook Integration

Google has rolled out a set of updates to Gemini 3.8 covering three distinct capabilities: expressive text-to-speech models, a Live Avatar feature for visually grounded conversations, and deeper notebook integration across Gemini and NotebookLM products. The Flash TTS and Flash-Lite TTS models, aimed at API developers, were announced in early September 2026 and enable more natural spoken output for customer-facing and internal AI applications. Gemini 3.8 Live with Live Avatar, introduced in mid-September 2026, adds near real-time visual presence to conversational AI interactions. Notebook integration connects source material from NotebookLM and related tools directly into Gemini conversations, supporting knowledge-work use cases. The updates were released across multiple Google product surfaces rather than as a single unified launch, targeting developers, enterprise users, and general Gemini consumers.

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ProgrammingDEV Community ·

Crystals: A Push-Based Agent Memory System That Delivers Notes Before Actions Run

Developers at DEV Community have introduced a concept called 'crystals' — a push-based agent memory mechanism that injects relevant notes into an AI agent's context immediately before a specific action executes, rather than waiting for the agent to query for help. Unlike traditional retrieval-augmented systems where memory is only fetched when the agent suspects it needs guidance, crystals are bound to particular actions and fire automatically based on pattern matching. Each crystal is a markdown file containing a concise, single-piece instruction delivered between defined markers, keeping the payload small and precise to avoid context-window budget issues. The approach addresses a documented gap in agent memory research: a failure mode where a correctly matched memory note is silently dropped by a token-budget packer before ever reaching the model. The authors frame this as a practical field report responding to a 2026 survey that identified bounded-memory management as an open problem in agent memory systems.

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ProgrammingHacker News ·

Scientists Achieve Breakthrough in Creating a Genuinely Blue Rose

Researchers have successfully developed a true blue rose, a feat long considered impossible in horticulture. The blue color was achieved through a specific combination of pigment and co-pigment compounds working together. Natural roses lack the genetic and biochemical pathways needed to produce blue hues, making this a significant scientific milestone. The discovery opens new possibilities for flower breeding and the study of plant pigmentation. Details of the research were reported by Science News.

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ProgrammingDEV Community ·

Students Build Camera-Based Fitness App That Reads Heart Rate Before Assigning Workouts

A four-person team called Kolkatar Rosogollas developed SoloFit, a React Native fitness app, during the 36-hour HackTropica 2K26 hackathon. The app uses a smartphone's front camera to detect subtle skin-colour changes caused by blood flow, extracting heart rate and breathing rate via the Presage SDK. These vitals are converted into a readiness score, which an LLM then uses to generate a personalised weekly workout plan. The team won the MLH Best Use of Presage SDK award for the project. Presage's own documentation notes its metrics are for general wellness purposes only and have not received FDA clearance for medical use.

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ProgrammingDEV Community ·

How a Jumia Product Dataset Was Cleaned and Turned Into an Excel Dashboard

A data analyst built an interactive Excel dashboard to examine product trends on Jumia, one of Africa's largest e-commerce platforms, using a scraped dataset of 115 products. The raw data required significant cleaning, including stripping currency symbols from price fields and extracting numeric ratings from descriptive text strings. Derived columns for price, discount, and rating categories were created using nested IF formulas to make the data analysis-ready. A key finding during cleaning was that roughly half the product listings lacked review counts or ratings, flagged as a data-quality gap affecting pricing and merchandising decisions. The project aimed to answer practical business questions around the relationship between discounts, ratings, prices, and customer engagement.

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ProgrammingDEV Community ·

GRPO Explained: A Lightweight RL Method for Fine-Tuning Large Language Models

Group Relative Policy Optimization (GRPO) is a reinforcement learning technique designed to fine-tune and align large language models more efficiently than traditional methods. Unlike PPO, which requires both a reward model and a critic model, GRPO eliminates the need for a separate critic by generating a group of responses and comparing them using a rule-based reward function. The method optimizes the model's policy by increasing the likelihood of better responses and reducing that of weaker ones, making it computationally lighter. GRPO differs from Supervised Fine-Tuning (SFT), which relies on curated prompt-response datasets and cross-entropy loss to train models. SFT is prone to issues like overfitting and catastrophic forgetting when training data is small, low-quality, or lacks diversity, making GRPO a compelling alternative in such scenarios.

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