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Pymnts

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Thredd: Inside the Payments Overhaul Powering Faster, Smarter Transactions

Banks and FinTechs, aided by issuer-processor Thredd, are using agentic AI to enhance transaction orchestration for improved efficiency and customer experience in the financial sector.
Thredd is restructuring its platform to support agentic AI's capabilities, focusing on real-time APIs, serverless compute, tokenization, and federated data access to ensure secure and efficient transactions.
Thredd allows AI models to be rigorously tested in simulation environments before deployment, ensuring trust and consistency in agent behavior.
By leveraging agentic AI, Thredd aims to provide faster and more accurate decision-making in processing transactions, reducing false positives and enhancing client experience.
Thredd is implementing AI agents with specific roles to optimize real-time decisions and combat fraud effectively in the financial ecosystem.
The company is enhancing fraud detection using explainable AI and aims to reshape B2B finance with autonomous agents for dynamic fund issuance and global transaction optimization.
Agentic AI deployment is expected to reduce transaction latency, improve authorization approvals, and increase repayment conversion rates in the financial industry.
Thredd's future goals include agent-to-agent interoperability and creating a network where AI agents collaborate seamlessly for scalability in the evolving ecosystem.
Piloting agent identity registries is crucial for enforcing auditability and advancing the potential of AI in financial services.
In conclusion, AI-driven processes facilitated by Thredd's infrastructure overhaul show promising advances in financial decisioning and transaction efficiency.

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Dev

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Lexus LFR Spied Testing: GR GT3's Street-Legal Evolution Nears Debut

The Lexus LFR, a street-legal evolution of Toyota's GR GT3 concept, has been spied testing in California by journalist Jonny Lieberman.
Key observations include the LFR's purposeful design and potential variants focusing on street refinement or track performance.
Lexus benchmarked the LFR against a previous-gen Mercedes-AMG GT, showcasing its aim to rival European GT cars.
The prototype displayed a stiff suspension for track-focused handling, promising a raw driving experience similar to the GR GT3's racing roots.
The powertrain, likely a twin-turbo V8 hybrid system exceeding 800 hp, remains unconfirmed for the LFR.
A reveal for the LFR is anticipated in late 2025 or 2026 after years of active road testing.
The name 'LFR' (Lexus Front-Engine Racer) aligns with Lexus' performance nomenclature, following the LFA.
The LFR marks Lexus' reentry into the supercar market, combining F1 aspirations with Toyota's racing heritage and Lexus luxury.
Targeting models like the AMG GT and Porsche 911 Turbo, the LFR aims to blend endurance racing roots with luxurious elements.
With active road testing underway and prototypes challenging benchmarks, the GR GT3's street version is becoming a reality.

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Dev

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Apple's Screen Revolution: Shrinking Dynamic Island in 2025 Paves Way for All-Screen 20th Anniversary iPhone in 2026

Apple is progressing towards an all-screen iPhone face through a multi-year roadmap leading to a significant redesign for the 20th-anniversary iPhone in 2026.
In 2025, the iPhone models are expected to feature a smaller Dynamic Island, aiming to minimize the display cutout.
The 2026 redesign is anticipated to include curved glass edges, extremely thin bezels, and a move towards a display with no visible cutout, bringing Apple closer to the goal of an all-screen iPhone.
Reports conflict regarding the implementation timeline of under-screen Face ID technology, with some suggesting its integration before the under-screen front camera by 2027.
The gradual evolution of iPhone displays from the notch to a potentially hole-punch free design by 2027 highlights Apple's systematic approach to innovation.

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Medium

157

To make money by taking a loan and getting high return in real estate, here’s a smart, step-by-step…

Using a bank loan to invest in high-growth real estate can lead to profits through property value appreciation or rental income.
Key Steps:
1. Choose a high-growth property in developing areas like Ajmer Road or Mahindra SEZ, with rates ranging from ₹18,900 to ₹30,000 per sq. yd.
2. Take a home or plot loan covering 70-80% of the property cost, with an easy EMI payment plan.
3. Hold onto the property for 2-3 years to benefit from areas like Jaipur's outer ring road or Mahindra SEZ, expecting a growth in property value.
4. Sell the property at a higher price after 2-3 years or generate passive income by renting it out.
Example Calculation:
Buying a 100 sq. yd plot at ₹19,000/sq. yd for ₹19 lakhs, with a potential profit of ₹11 lakhs when selling at ₹30,000/sq. yd.
Key Tips: Choose JDA approved & RERA registered properties, invest in upcoming infrastructural locations, start with small investments like 50-100 sq. yd plots or 1BHK flats.
Loan Amount (80%): ₹15,20,000
Your Investment (20%): ₹3,80,000
EMI (5 yrs approx.): ₹11,000/month
Price After 2 Years: ₹30,000/sq. yd
Selling Price (Expected): ₹30,00,000
Profit: ₹11,00,000+

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Medium

289

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These 6 steps helped me master coding easily

Start with learning Html, Css, and Javascript as foundational web development languages.
Having a mentor is important for faster learning and to save time, especially for beginners.
Follow a structured learning path to avoid getting stuck. Roadmap.sh and platforms like freeCodeCamp, Codecademy, Udemy can help.
Use fun resources for learning programming to avoid boredom and make learning more engaging.
Implement what you learn by creating small projects like todo lists, quiz apps, or calculators.
Having a programming buddy or being part of online communities like FreecodeCamp, The Odin Project, Codepen can enhance learning and motivation.

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Nordicapis

223

10 Tools for Securing MCP Servers

Model Context Protocol (MCP) links AI-driven tools with organizational resources, necessitating secure MCP servers. Here are ten tools for securing MCP servers:
1. Salt Security MCP Server provides context-aware analysis and threat detection.
2. MCPSafetyScanner offers role-based testing and audit logging.
3. CyberMCP integrates with IDEs and offers natural language querying.
4. Invariant Labs MCP-Scan detects MCP-specific threats like tool poisoning.
5. Kong AI Gateway enables natural language API queries and behavior profiling.
6. MasterMCP provides Python toolkit for MCP security threat emulation.
7. MCP Security Scan is a lightweight, open-source scanner.
8. MCP for Security offers a suite of MCP-compatible functions for cybersecurity professionals.
9. Docker MCP Toolkit provides Docker-native integration and OAuth support.
10. Slowmist MCP Security Checklist offers risk-based assessment tools.

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Dev

140

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How To Build AI Chatbot Using React + Node.js

A webinar is being offered on how to build an AI chatbot using React and Node.js.
Participants will learn to create a fully functional full-stack AI chatbot step-by-step.
The chatbot will be able to answer questions based on a user's uploaded resume.
Key learnings include building a chatbot using React + Gemini AI, deploying the application live, and adding Rate Limiting.
Participants will also discover how to ensure the chat app stays operational even with a free plan.

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Lostmoa

231

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Using enumerated() with SwiftUI List and ForEach to show item numbers

Enumerated() in SwiftUI can be used with List and ForEach to show item numbers.
It returns a sequence of (offset, element) pairs, where offset is a counter from zero.
In Swift 6.2 and iOS 26, EnumeratedSequence now conforms to RandomAccessCollection.
Previously, an additional step was required to wrap the sequence in an array.
The offset in EnumeratedSequence should not be used as an index to access elements from the original collection.
Using offset or index as the id in ForEach is not recommended in dynamic collections.
For dynamic collections, a stable and unique identifier like Identifiable should be used.
A struct can be used with Identifiable to maintain stable identity in dynamic collections.
By decoupling numbering from identity, correct behavior is ensured as the data changes.
SwiftUI Fundamentals book is recommended for a deep dive into SwiftUI core principles and APIs.
For more resources on Swift and SwiftUI, other books and book bundles are available.

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13 Likes

Medium

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This Easy Tool "Hacks" ChatGPT, Gemini & Grok To Send You Millions Of Clicks.

A tool claims to 'hack' into ChatGPT, Google Gemini, and Elon Musk's Grok to generate millions of clicks without advertising costs.
The tool is an intelligent automation system that leverages AI bots, trending prompts, and content hooks for massive attention.
Users can select an offer, utilize AI scripts to create engaging content, and publish on pre-made traffic platforms to drive traffic.
The system does not require showing face, a website, ad investment, works in any niche, and is beginner-friendly.
The tool promises to provide free traffic using AI bots, which is considered an untapped traffic source.
Users are encouraged to get the 'Free Traffic Tsunami' offer to benefit from the tool.
The world is yet to realize the potential of AI for free traffic, and users are urged to seize the opportunity now.

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Medium

384

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Design patterns: Roses with thorns

Design patterns, though beneficial, may have downsides and trade-offs.
Information on when design patterns should not be used is often lacking in available resources.
The author aims to discuss both the advantages and disadvantages of design patterns to encourage deeper analysis and conscious decision-making.
The complexity of advanced systems can involve navigating through layers of abstraction when implementing design patterns.
Each layer of abstraction introduced by a design pattern should be thoroughly understood and analyzed.
Implementing highly flexible solutions based on design patterns can require additional time and effort, which is only worthwhile if future needs can be predicted accurately.
Design patterns offer approaches to solving common problems, but they are not one-size-fits-all solutions.
It is not necessary to implement a design pattern every time a problem aligns with the pattern's definition.
Balancing productivity, performance, and flexibility in software architecture is a complex endeavor with trade-offs.
There is no definitive answer on how to balance these factors, relying on experience and thoughtful decision-making.
The author acknowledges the complexity of design patterns and emphasizes the need for careful consideration in their application.

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23 Likes

Dev

248

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🌟 Build Stunning UIs Instantly with AakarUI – A Native Web Component Library

AakarUI is a native Web Components library built with pure JavaScript, focusing on simplicity, performance, and developer experience.
Components include buttons, input fields, alerts, cards, navigation bars, tabs, accordions, chat boxes, calendars, tables, and more.
No class names or setup required, users can directly use the tags for instant UI components.
AakarUI offers 30+ ready-to-use components with elegant default styles and extensibility across different frameworks.
Each component can be globally accessed with just one line of installation using the CDN link provided.
Developers can build their own design systems on top of AakarUI or contribute by adding new components following the guidelines.
The library's simplicity makes it suitable for quick projects like dashboards, landing pages, or Chrome extensions.
For live demo and documentation, users can visit the provided URL along with the GitHub repository for the project structure and contributions.
AakarUI's usage examples cover buttons, input fields, file uploads, calendars, and chat boxes.
Developers can leverage Shadow DOM for using AakarUI components in different frameworks or create custom components with HTML and JS.
The library aims to provide a fast, simple, native, and aesthetically pleasing UI experience.
Developers can connect with the project creator on GitHub or the official website for feedback, ideas, or contributions.
AakarUI targets those who seek hassle-free UI implementations without the need for extensive framework knowledge.
The library is introduced with the goal of simplifying UI development and offering a range of pre-built components for various UI needs.
With a focus on ease of use and rapid UI setup, AakarUI strives to cater to developers looking for efficient UI solutions.
AakarUI stands out for its lightweight nature, lack of dependencies, and the convenience of direct tag usage for creating UI elements.

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Dev

281

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I Created a Simple Tool to Instantly Preview HTML Generated by ChatGPT

ChatGPT has become a powerful tool for generating HTML and other code snippets, but working with the HTML output can be tedious.
Creating and previewing HTML typically involves manual steps like saving files and opening them in browsers, which can become cumbersome over time.
To address this issue, a simple web tool has been developed to allow instant rendering of HTML code without the need to save files.
Users can paste the HTML code generated by ChatGPT into the tool, click 'Render,' and view the output directly in the browser.
The tool employs document.write() which helps maintain consistent line numbers for debugging purposes if syntax errors occur.
Eliminating the manual process of creating and saving HTML files can enhance workflow efficiency and ease of use.
The developer encourages users to download the tool from GitHub to streamline their coding experience.

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Self-Learning-Java

140

Need to Stop a Running BigQuery Job? Use bq cancel

To stop a running BigQuery job before completion, use the 'bq cancel' command followed by the job ID.
For example, 'bq cancel job_id' will immediately halt the job's execution.
You can find the job ID from various sources like GCP console, logging systems, or bq query outputs.
Using 'bq ls -j' allows listing recent jobs with their details, including job ID.
The 'bq cancel' command helps save costs by stopping long-running or unoptimized queries.
It also allows for quickly interrupting accidental or test jobs.

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Medium

327

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Agentic Architectures Deserve Their Own OSI Model

The OSI model, originally for network protocols, influenced how engineers structure complexity with its seven-layer abstraction.
As autonomous agents become more advanced, a new layering model is needed to focus on goals, memory, actions, and reasoning.
The new model maps the OSI layers to LLM-powered agentic systems instead of TCP/IP.
At the top of the new model is the Application Layer where agents have goals like generating reports or booking meetings.
Prompt assembly, structured tool calls, and knowledge encoding take place in the Presentation Layer of the new model.
Memory and partial reasoning activities are managed in the Session Layer of the reimagined model.

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Self-Learning-Java

148

Getting Started with LangChain4j and Ollama: A Step-by-Step Guide

LangChain4j is a Java-centric tool for building LLM-powered applications, akin to LangChain in Python.
Ollama is a local LLM runtime to run models like LLaMA2 or Mistral on your machine via HTTP.
The guide covers setting up a Java project with LangChain4j, integrating it with Ollama, and utilizing LLMs.
Prerequisites include setting up Ollama and pulling the llama3.2 model.
Step-by-step instructions involve creating a Maven project, updating pom.xml, and defining a HelloWorld class.
The HelloWorld application sends a prompt to LLaMA3.2 and prints the response in the console.
OllamaLanguageModel builder specifies the Ollama model integration details in Java code.
Important details like baseUrl and modelName are set for interacting with the Ollama model.
A prompt is defined to inquire about Interesting Facts about LLMs in a concise manner.
The process generates a Response object including generated content, token usage, finish reason, and metadata.

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