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Over the last several months, XRP Ledger (XRPL) has fundamentally shifted in how amendments move from concept to mainnet. Historically, amendment development was largely focused on functional correctness, performance testing, traditional security audits, bug bounties and independent validator testing as the last line of defense to catch security vulnerabilities. As XRPL continues to grow in complexity and the value secured by the network increases, we recognized that the previous model was no...

Disclosure up front: I'm affiliated with diagram.now — I'm connected to the product. I'm posting this to get developer feedback on diagram import/export interoperability, not to pitch an install. Most teams I've worked with don't have one source of truth for their diagrams. They have: a few Mermaid blocks living in READMEs and Markdown docs, an old Visio ( .vsdx ) or Lucidchart file someone made two reorgs ago, a SQL schema that is secretly the "real" ERD, and a pile of...

Gas optimization is satisfying. You shave a few thousand gas off a function and feel clever. But some optimizations trade away safety in ways that are not obvious, and I have seen "optimized" contracts that introduced vulnerabilities. Here are the gas wins that are genuinely free, the ones that cost you safety, and how to tell the difference. Where gas actually goes Before optimizing, know what is expensive. Storage operations dominate. Writing a fresh storage slot ( SSTORE from...

AI agents are getting very good at writing final reports. The problem is not only that they make mistakes. The problem is that sometimes they make mistakes with excellent presentation. Proofline is a 5-skill Markdown pack that catches fake-ready output before it turns into a release, handoff, public post, or "yeah, looks done". What Proofline does It is not trying to be another giant agent. It works as a review route after the agent produces a result: Reference Gap R...

When a Spring Boot service needs to talk to another service without waiting on a synchronous HTTP call, message queues are the usual answer. Apache Kafka has become the default choice for this in most backend teams, but a lot of tutorials stop at a "hello world" producer and consumer that would never survive a real production load. Things like consumer retries, error handling, serialization of real objects, and graceful shutdown get skipped, and those are exactly the parts that page you at 2 a.m...

AI coding agents now edit repositories, run commands, and produce branches. That makes the spec before the work more important: it carries the context, boundaries, and success criteria the agent needs. What a good coding-agent spec includes Specs are becoming more important because AI coding agents are no longer only answering questions. They are reading repositories, editing files, running commands, producing branches, and asking humans to review the result. That changes what a ...

This is Part 13 of my series on the Microsoft Agent Framework. You can read the original post over on lukaswalter.dev . In the previous article , we looked at workflows. Workflows make sense when the process itself needs structure: state, checkpoints, events, human approvals, and resumable execution. This post is the bridge from Agent Framework into RAG. I plan on doing a full RAG deep dive sometime later. The practical question for now is smaller: How do I connect an Agent Frame...

Quick update to anyone interested in upcoming changes to the PAGI project (spiritual successor to Plack/PSGI). 1) Distribution split up: when we released PAGI, we initially released everything as one distribution. PAGI ( https://metacpan.org/pod/PAGI ) currently has a) the PAGI specification; b) the reference server and c) a bunch of ease of use tools, similar to the role that the Plack distribution played for PSGI. Putting everything into one place was just to make my life easier as in th...

You walk into the RFP briefing. Your competitor has 200 people, 97% AI coverage, and a 4-day delivery promise. You have 15 people and a proposal you haven't even finished writing. Do you bet on better tech, or on understanding people better — and playing dirtier when you have to? This story is your answer. Act I · The Crack When Finova's RFP landed, everyone in the industry knew how big this was. Cross-border payment system. Multi-currency settlement + compliance + r...

# EnvForge BETA v1.1 ⚡ Structured .env scaffolding for modern applications. Generate, validate, and protect environment variables for 14+ services – without ever opening a docs page. Github repo [ https://github.com/Jos3456/envforge ] NPM version (https://img.shields.io/npm/v/envforge-dev) MIT License (https://img.shields.io/badge/License-MIT-yellow.svg) ## Installation bash npm install envforge-dev **Requirements:** Node.js 18 or later. --- **## ...

Bash is the easiest language for AI to write and the easiest language to get devastating output from. A 20-line script that "just cleans up old files" can recursively delete a home directory because the model assumed a variable would always be set. A "simple log shipper" can write your secrets to a remote server because the model used set -x for debugging and forgot to remove it. I have run AI-generated bash that I should not have. Most engineers I know have too. After enough close calls, t...

Most SaaS ideas don’t fail because of bad ideas. They fail because the execution gets stuck in an endless setup loop. You start with energy, then slowly get buried in: auth systems, billing, dashboards, SEO, analytics, and infrastructure decisions. By the time the “real product” should begin, momentum is already gone. Here are 7 practical alternatives to building SaaS in a way that never gets finished. 1. Nexora (start with a working SaaS foundation) Instead of re...

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Unlike Linktree or Beacons which extract value from creators’ audiences, Payge.Me turns every follower into a revenue event.

The question is no longer whether you need to manage your AI perception. The question is whether you’ll do it reliably — or keep guessing.

Protect your pipeline from potential threats with these top-notch security practices.

AI prompts reveal more than requests. They reflect our biases, communication habits, need for control, and expectations of technology.

Complex Event Processing (CEP) is great at detecting patterns in real time, but detection alone doesn't create business value. Organizations also need context, enrichment, historical analysis, governance, and AI-driven insights to understand why events occur and what actions to take. This is where Complex Event Analytics (CEA) comes in. CEA extends beyond CEP by combining event capture, data refinement, large-scale storage, AI, and business applications into a unified architecture that transfor...

I rebuilt an old dissertation idea as a C#/.NET benchmark to test whether Hilbert curve ordering helps solve Shikaku puzzles. Pure Hilbert ordering beats row-major scanning, but MRV is far stronger as a primary heuristic. Blind Hilbert tie-breaking helps often but has nasty outliers. The best result came from using spatial locality cautiously. Apply MRV first, then use local proximity near the most recently placed rectangle only when MRV leaves a tie.

eSIM provisioning is the hidden flow that turns a QR code or activation code into a working mobile line. The phone’s LPA contacts the SM-DP+ server, authenticates through GSMA-backed certificates, downloads a protected profile package, installs it into the eUICC secure chip, and then uses that profile to authenticate to the mobile network.

AI is moving from output to action. Before we give systems more autonomy, we need controls around memory, permissions, audit trails, state tracking and human override. Governance is not something AI companies should add later. It has to be built in from the beginning.

The planning mistakes that ruin essays are identical to those that ruin software projects. Thesis statements are requirements documents. Here's why.

Can AI agents be regulated with old rules related to slavery?

The most dangerous AI-generated statement in a company is not always the obviously false one. It is often the sentence that sounds so complete, neutral, and professionally written that nobody feels the need to challenge it. AI does not merely generate information. It generates linguistic closure. It can transform uncertain assumptions into polished recommendations, contested interpretations into apparent facts, and human decisions into conclusions that seem to have emerged from the system itse...

Capturing continuous touchpad gestures in C++ on Windows 10 is complex due to poorly documented APIs, deprecated methods, and hardware inconsistencies.