4+ min ago (333+ words) A practical guide for hardware engineers, IoT developers, and anyone building battery-powered devices. When building an IoT node, wearable, handheld device, or robotics prototype, choosing the right lithium battery is more than "pick a voltage and capacity." A lithium battery datasheet is full of critical parameters, hidden limitations, and performance details that affect safety, runtime, thermal behavior, charging strategy, and long-term reliability. This guide gives you a developer-friendly checklist to decode any Li-ion/Li-polymer battery datasheet. Before anything else, identify: Why it matters: Form factors define energy density, thermal dissipation, bending tolerance (for wearables), and mechanical integration. Typical Li-ion nominal voltages are: But different datasheets may specify: Real-world capacity can differ by 1020% if your discharge current is higher than the datasheet's test current. This is one of the most abused datasheet parameters. A short-term burst (usually msseconds) for: For robotics…...

5+ min ago (553+ words) Docker is an open-source platform that makes it easy to build, ship, and run applications in isolated environments called containers. A Dockerfile is a plain text file that contains a set of instructions (like FROM, WORKDIR, COPY, RUN, EXPOSE, CMD) that Docker reads to build a Docker image. It's essentially a recipe for your application's environment. A Docker image is a lightweight, standalone, executable package that includes everything needed to run an application: code, runtime, system tools, libraries, and settings. Images are read-only. A Docker container is a runnable instance of a Docker image.5 You can create, start, stop, move, or delete containers using Docker commands. docker build -t my_image . The -t flag tags the image with a name, and . specifies the current directory as the build context. Run the Container: Once the image is built, you run a container from it....

12+ min ago (104+ words) " "API" " "ApidogAI" " Apidog" Apidog'API'API" PostmanSwagger EditorMock'API" " "AI" [AI] "AI" " " " " " AI" AI" [AI] API" " " AI " " " " " " " " " " " "AI" AI" " AI" [AI] Apidog'AI" "OpenAIClaude'AIAPI" "AI" " " " [AI] " " " " " "AI" " "AI" " " CI/CD" "AI" "AI'AI" " AI" " " " "AI" " " " https://docs.apidog.com/jp/apidog%E3%81%AEai%E6%A9%9F%E8%83%BD%E6%A6%82%E8%A6%81-1237382m0 https://docs.apidog.com/jp/%E3%83%86%E3%82%B9%E3%83%88%E3%82%B1%E3%83%BC%E3%82%B9%E3%81%AE%E8%87%AA%E5%8B%95%E7%94%9F%E6%88%90-1625320m0 API" " " AI " Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well...

13+ min ago (428+ words) I've been working with containerized applications for a while, and one thing that always confused me in the beginning was Docker image tagging. Nobody explained it properly. I just followed whatever the team did, pushed images, and hoped things worked. But over time.. especially when handling multi-tenant apps, shared registries, and too many deployments. I started to see how bad tagging decisions can break everything. So here's my experience and what I learned the hard way. The moment I realized "latest" is a trap When I first started using Docker, I thought: "Ah, just push it with latest. Simple." Until one day, a tenant's production environment suddenly rolled back to a previous version. Why? Because someone else on the team pushed a new image with the same latest tag. The registry replaced it silently. The cluster pulled it automatically. Chaos....

15+ min ago (276+ words) When a Django project starts small, model relationships are easy to understand. But as the project grows " new apps, foreign keys everywhere, business logic stacked across modules " suddenly: " Understanding how models relate becomes harder than reading the source code itself. This is where Entity-Relationship Diagrams (ERDs) become incredibly important. A good ERD helps every developer (new or old) understand: " How models depend on each other " Where foreign keys and many-to-many relations exist " Effects of cascading deletes " Where circular dependencies might cause migrations to fail Yet many teams never update ERDs after the first version, because manually drawing diagrams in Draw.io / Lucidchart / Figma becomes unmaintainable. " The solution? Generate ER diagrams automatically from Django models " as code or as images " directly from your project. Not only can this live documentation be added to the repo, it can also be generated automatically…...

19+ min ago (686+ words) A SIP calculator is one of the easiest tools for understanding how much your investments can grow over time. Whether you invest every month through SIP or put in money once through a lumpsum, the calculator shows how your money compounds, how much wealth you can build, and what your final maturity amount may look like. A lot of people assume SIP and mutual funds are the same thing, but SIP is simply a method of investing in mutual funds. You can either invest regularly (SIP) or put everything at once (lumpsum). In both cases, a SIP calculator or mutual fund calculator helps you estimate how your investments will perform in the future. A SIP calculator is a digital tool that tells you how much return you can expect when investing through SIP. You enter three simple inputs: Once you…...

20+ min ago (760+ words) We've been working with our friends from Anthropic for a while now, and it's finally time to share:Claude Opus 4.5 is launching today. Our team at Kilo Code has been spoiled testing a preview of the latest model from Anthropic. Today, Anthropic officially launches Opus 4.5, and we're making it available immediately in Kilo Code. The most significant change? Opus 4.5 introduces something genuinely new:effort settings. You can now tell the model how hard to think. High effort: Claude takes its time, uses more tokens, delivers maximum intelligence (this is Anthropic's default) Medium effort: The sweet spot for most tasks Low effort: Fast, efficient, and surprisingly capable for straightforward coding tasks Think of it like having three models in one. Need a quick function? Low effort. Architecting a complex system? Crank it to high. This aligns perfectly with Kilo Code's methodology…...

39+ min ago (520+ words) The "hello world" phase of generative ai development is officially over. We have moved past the era where simply calling an OpenAI API was enough to impress stakeholders. As we settle into 2025, the focus for software engineers has shifted entirely from experimentation to reliability, observability, and cost-efficient scaling. Building production-grade generative systems requires a rigorous engineering mindset. It is no longer just about prompt engineering; it is about architectural patterns that ensure determinism in a non-deterministic environment. The most significant trend we are seeing is the move away from monolithic LLM calls toward compound systems. In professional generative ai development, reliance on a single model's raw output is often a recipe for hallucination and latency. Instead, developers are now architecting "flows" or "chains." Agentic Workflows: Using frameworks like LangGraph or AutoGen to allow models to use tools'executing Python scripts, querying…...

48+ min ago (650+ words) Laravel Pint is a zero-configuration PHP code style fixer built specifically for Laravel projects. It automatically formats your PHP code to follow consistent styling standards without requiring manual setup or complex configuration files. Pint comes pre-installed with all new Laravel applications (version 9.21 and newer), so you can start using it immediately after creating a project. It works by scanning your PHP files and automatically fixing code style issues based on Laravel's opinionated coding standards. Laravel Pint is built on top of PHP-CS-Fixer, a popular PHP code formatting tool. The key difference is that Pint simplifies the setup process, while PHP-CS-Fixer requires complex configuration files written in PHP, Pint uses simple JSON configuration and works out-of-the-box with sensible defaults. When you run Pint, it scans all .php files in your project (except the vendor directory), identifies code style violations, and automatically…...

59+ min ago (583+ words) The Indian tech landscape is undergoing a massive shift in 2025. With new labor codes redefining salary structures and the rise of Generative AI, developers who understand their worth'and how to negotiate it'are positioned for massive growth. This is more than just a salary guide; it's a playbook for maximizing your compensation in a rapidly maturing market. The Cost to Company (CTC) is the most-cited figure in Indian offers, but it's the most misleading. It represents the total cost to your employer, not your monthly take-home pay. Ignoring this distinction can cost you thousands. The CTC is calculated by summing up Direct Benefits (your Gross Salary), Indirect Benefits (reimbursements, insurance premiums), and Statutory Contributions (Employer's PF and Gratuity). It is crucial to understand the components that affect your Net (In-Hand) salary: The New Labour Code Alert: Proposed new labor codes aim…...