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• Large Language Models in 2026: GPT-5 vs Claude vs Llama and the Future of AI ModelsJan 06, 2026. LLMs in 2026: Specialization, multimodality, open-source competition, & practical safety. Explore technical advances, product shifts, & future trends.
• The Usefulness of Tabular Editor and How to Launch It from Power BI DesktopJan 05, 2026. In this article, I talked about how to unlock Power BI's full potential with Tabular Editor! Learn how to launch it from Power BI Desktop for faster DAX editing, bulk changes, and model optimization. Elevate your Power BI skills!
• DAX Query View in Power BI Desktop: Why It Matters and How It Elevates Your Data ModelingJan 05, 2026. In this article, I talked about unlocking Power BI's potential with DAX Query View! Explore, debug, and optimize DAX queries directly in Desktop. Elevate data modeling and build reliable reports. I also covered how to evaluate and create a new DAX measures from the DAX query view
• Why There Is No "Tokenization-Only Model" in Modern NLPJan 06, 2026. Uncover why tokenization in NLP isn't a neural model like embeddings. Explore its deterministic nature, algorithm-based approach, and tight coupling with LLMs.
• The Autonomous Enterprise: Operating Model, Roles, and a Practical Maturity RoadmapJan 03, 2026. Mastering the autonomous enterprise: Learn a practical operating model, define key roles, and implement a maturity roadmap for safely scaling AI automation.
• Blueprint for Intelligence: What Business Agent Architecture Is and How to Build ItJan 01, 2026. Learn what business agent architecture is and how to build it with key components, governance, security, and operating metrics to deliver reliable ROI from AI agents in the enterprise.
• Sector Watch: What Agentic AI Is and How It Will Disrupt Industries FirstDec 31, 2025. Discover what agentic AI is and how it will initially disrupt industries, with a business-ready framework to prioritize sectors, quantify value, manage risk, and facilitate adoption.
• Implementing MCP for Enhanced Prompting and RAG-Based ApplicationsDec 30, 2025. Enhance AI with MCP! Learn how Model Context Protocol revolutionizes prompt engineering and RAG, enabling context-aware, personalized, and efficient AI interactions.
• World Modeling in AI: What It Is and How It Works End-to-EndDec 30, 2025. Learn what world modeling in AI is and how it works end-to-end, including core architectures, training loops, planning, evaluation, and practical deployment patterns.
• Agentic AI vs. Generative AI in 2025: What They Are and How to ChooseDec 28, 2025. Learn what Agentic AI vs. Generative AI means in the 2025 business reality and how to choose the right approach with practical frameworks, governance steps, and ROI-focused rollout guidance.
• C# LINQ: .ToList() vs .ToListAsync() - Threading Model Analysis and Performance OptimizationDec 29, 2025. Unlock C# LINQ performance! Discover the crucial differences between .ToList() and .ToListAsync() for optimal threading, scalability, and I/O efficiency. Boost your app's responsiveness!
• Agentic AI vs. RPA: What ends dumb automation and how businesses scaleDec 29, 2025. Learn what Agentic AI and RPA mean for businesses, how each drives ROI, and how leaders modernize automation with governance, cost control, and measurable outcomes.
• How to Optimize Performance in Power BI Reports and DashboardsDec 26, 2025. Learn how to optimize Power BI performance using proven data modeling, DAX optimization, query tuning, and report design best practices. A practical guide for faster dashboards at scale.
• Designing the Right Data Structure in PowerApps: Why Your List Schema MattersDec 26, 2025. Optimize PowerApps data structures! Learn best practices for list design: naming, column types, validation, performance, security, and future-proofing. #PowerApps
• C# 14: From Helper Classes to First-Class APIsDec 24, 2025. C# 14 extension members introduce extension properties, operators, and static members. Learn how they transform helper classes into first-class APIs and enable modern, expressive, and binary-safe .NET domain modeling.
• How to Create a Generative Page in Power AppsDec 22, 2025. Generative Pages in Power Apps represent a major evolution in low-code development, enabling makers to build modern, responsive, and fully functional pages using natural language. This article explains what Generative Pages are, their key features, benefits, limitations, and how they transform model-driven app development. It also includes a detailed step-by-step guide on creating Generative Pages using AI, connecting Dataverse data, refining layouts, and publishing results. Perfect for beginners as well as Power Platform professionals exploring AI-powered app creation.
• Claude Opus 4.5 on Azure: A Friendly Deep-Dive into Anthropic’s Most Powerful ModelDec 23, 2025. Explore Claude Opus 4.5 on Azure: Anthropic's top AI model for coding, agents, and enterprise tasks. Discover its capabilities, use cases, and pricing details.
• Kimi K2 Thinking on Azure: A Simple Guide to Moonshot AI’s Deep Reasoning ModelDec 23, 2025. Explore Kimi K2 Thinking, Moonshot AI's powerful deep reasoning model, now on Azure. Discover its capabilities, architecture, API compatibility, and pricing.
• Accelerating AI Innovation Using the Microsoft AI ToolkitDec 23, 2025. Streamline AI development with the Microsoft AI Toolkit! Build, evaluate, and deploy AI agents and models efficiently using its comprehensive features. Cloud-ready & scalable!
• Partial Constructors in C# 14 (.NET 10) - A Game-Changing FeatureDec 22, 2025. C# 14 introduces Partial Constructors, a game-changer for .NET 10! Split constructor logic across files, enhance source generator support, and improve maintainability. Build modular, scalable applications with ease.
• Why MCP Matters in Modern AI SystemsDec 20, 2025. Discover MCP (Model Context Protocol), a universal standard for connecting AI models to backend systems. Learn how .NET developers can leverage MCP for scalable AI.
• Getting Started with Foundry Local: Run AI Models on Your Own DeviceDec 17, 2025. Running AI models on your own laptop or PC is now easy with Foundry Local, a small tool you install and use from the command line. It lets you download, run, and manage modern AI models locally so you can experiment, build apps, or work offline.?
• Getting Started with AI Toolkit in VS Code: A Simple Guide for EveryoneDec 16, 2025. The AI Toolkit for Visual Studio Code is a free extension that lets you download, test, fine-tune, and use AI models directly from VS Code, either on your own machine or in the cloud. It gives you a simple, step-by-step experience so you can go from “no model” to “AI inside my app” without leaving your editor.
• Creating Objects Without a Model in C#Dec 16, 2025. Creating Objects Without a Model in C#
• What are AI hallucinationsDec 15, 2025. AI hallucinations occur when language models generate confident but incorrect or fabricated information. Learn what causes AI hallucinations, why they happen in large language models, real world risks, and how developers and architects can reduce them in production systems.
• How LLMs Generate ResponsesDec 15, 2025. Learn how large language models generate responses step by step. Understand tokenization, embeddings, attention, and next-token prediction to see why LLMs sound confident, how they work internally, and why hallucinations occur.
• Different Types of AI HallucinationsDec 15, 2025. Learn the different types of AI hallucinations in large language models, including factual, reasoning, contextual, and conversational hallucinations, and understand why they matter for developers and architects building production AI systems.
• Differences Between asyncio, Multiprocessing, and Threading in PythonDec 16, 2025. Learn the key differences between asyncio, threading, and multiprocessing in Python. This beginner-friendly guide explains how each concurrency model works, when to use them, and includes simple code examples for real-world use cases.
• Record, Record Struct, and Structural Equality in C#Dec 14, 2025. Learn how structural equality works in modern C# using records and record structs, and why it is essential for building correct value objects in Domain-Driven Design. This guide explains when to use records, record structs, and classes for clean, scalable domain models.
• Entity Framework Core – Code First ApproachDec 14, 2025. This article provides a complete and descriptive explanation of the Entity Framework Core Code First approach. It explains how databases are created and managed using C# classes, how DbContext and entities work together, how migrations handle schema changes, and how relationships, configuration, and change tracking are managed in Code First development. Written in simple language, this guide is ideal for beginners and professional .NET developers building modern, scalable applications using Entity Framework Core and SQL Server.
• How to Connect SharePoint Using ASP.Net Core Azure Function (Isolated worker model) ?Dec 14, 2025. this article is about to connect with SharePoint using ASP.Net azure function. and fetch data from SharePoint list.
• Entity Framework Core – Database First ApproachDec 14, 2025. This article provides a complete and descriptive explanation of the Entity Framework Core Database First approach. It explains how EF Core generates entity classes and DbContext from an existing database, how scaffolding works, how relationships, views, and stored procedures are handled, and how to safely manage schema changes using re-scaffolding and partial classes. Written in simple language, this guide is ideal for beginners and professional .NET developers working with legacy or enterprise databases using Entity Framework Core.
• The Evolution of Web Security: Best Practices for 2025 and BeyondDec 12, 2025. Explore the evolution of web security and best practices for 2025 and beyond. Covers modern threats, secure development, API and frontend protection, and cloud security. Designed for senior developers building resilient and future-ready web applications.
• LLMs And GSCP-15: Turning Raw Models Into Governed Reasoning SystemsDec 11, 2025. Why LLMs Need A Governing Mind Around Them Large language models are astonishingly capable pattern machines. With the right prompt, they can write code, draft contracts, design interfaces, and summarize complex logs. But under all the capability sits a very simple objective: predict the next token. That objective explains almost all of their bad behavior. They hallucinate because the next token that fits the pattern is not always the truth. They drift off spec because there is no native concept of a contract that must be honored. They break policies because their goal is fluency, not compliance.
• Evaluating Generative AI Models and Agents in Azure AI FoundryDec 12, 2025. An autonomous insurance claims processing agent in Azure AI Foundry can read FNOL (First Notice of Loss) documents, predict settlement outcomes, and automate claims workflows by leveraging AI-powered data extraction, validation, and orchestration capabilities. Such an agent automates the intake and processing of claims, including extraction of data from forms, emails, and supporting documents, cross-referencing claims with policy terms, and routing for approval or escalation, thereby reducing cycle times significantly.
• What LangSmith Fetch Is and How It Automates Dataset Retrieval for EvaluationsDec 11, 2025. Learn what LangSmith Fetch does, how it streamlines dataset ingestion for LLM evaluation, and how to use it in LangChain workflows. Includes architecture diagrams, step-by-step setup, code examples, and best-practice recommendations.
• 🔮 Micro-LLMs vs Large LLMs: The Future of Lightweight AI ModelsDec 10, 2025. Micro-LLMs are compact, fast, on-device AI models designed for privacy, low cost, and real-time performance. This summary explains their benefits, differences from large LLMs, and why they drive the future of everyday AI.
• AI Agents vs Traditional AI Models: How Digital Workers Will Replace AppsDec 08, 2025. For more than a decade, developers have built applications around a fixed paradigm: front-end clients, well-defined APIs, backend services, databases, and static business workflows. Machine learning models were optional add-ons that improved specific parts of the system, such as recommendation engines, fraud detection, or text classification. These models were specialised, narrow, and completely dependent on deterministic software logic.
• Difference Between Public, Private, and Hybrid Cloud?Dec 08, 2025. Learn the key differences between Public, Private, and Hybrid Cloud models in simple words. Understand how each cloud deployment model works, their benefits, use cases, and which one is best for businesses in different regions.
• Entity Framework Core – A Complete and Deep ExplanationDec 06, 2025. This article provides a complete, descriptive, and beginner-to-advanced explanation of Entity Framework Core (EF Core). It covers how EF Core works internally, its core components, change tracking, relationship handling, migrations, DbContext, DbSet, performance features, advanced capabilities, concurrency handling, shadow properties, value conversions, global filters, interceptors, and when EF Core is suitable for real-world .NET applications. Written in a simple, clear style, this guide helps developers understand EF Core deeply without focusing on LINQ or specific approaches.
• Beyond Single Models: Why The Future Belongs To Private, Tailored, Small AI Models and TeamsDec 06, 2025. Discover why private, tailored, small AI models are the future. Gain control, cut costs, and boost performance with specialized AI teams. Ditch the monolithic model!
• LangSmith Cost Tracking: Full Guide to Logging, Monitoring, and Optimizing LLM CostsDec 06, 2025. A comprehensive walkthrough of LangSmith’s cost-tracking system, including setup, callbacks, token accounting, dashboards, best practices, and optimization strategies.
• Integrating Machine Learning Models into ASP.NET Core ApplicationsDec 04, 2025. Integrate AI into ASP.NET Core! This guide covers ML.NET, ONNX, Python microservices, and cloud models for scalable, enterprise-grade intelligent apps.
• Protecting AI Models Against Malicious InputsDec 04, 2025. Secure AI models from attacks! Learn to identify threats, mitigate risks, and implement robust security measures for AI in production. Protect your AI today!
• Large Language Models: What They Really Change In Work And SoftwareDec 05, 2025. LLMs are transforming work & software, shifting from research toys to invisible infrastructure. Learn how they work, their impact, and future implications.
• Integrating Machine Learning Models into ASP.NET Core ApplicationsDec 03, 2025. Learn how to integrate machine learning models into ASP.NET Core apps using ML.NET, ONNX, and external APIs. Build intelligent, production-ready applications!
• Deploying AI Models to Azure App Services with ASP.NET CoreDec 03, 2025. Deploy AI models to Azure App Services using ASP.NET Core. Learn best practices for scalable, secure, and production-ready AI applications. Includes model integration and storage.
• Protecting AI Models Against Malicious InputsDec 03, 2025. Learn to defend AI models from malicious inputs! Discover key strategies for validation, adversarial training, monitoring, and secure AI architecture.
• Major Challenges LLMs Face When Working With Healthcare DataDec 03, 2025. Healthcare data is complex, sensitive, and heavily regulated. Discover the major challenges large language models face with PHI privacy, accuracy, hallucinations, multimodal data, specialty knowledge, and clinical deployment, and why the future belongs to safer, specialty specific healthcare models.
• Docker Model Runner Adds vLLM for Fast AI InferenceDec 01, 2025. Docker Model Runner now supports vLLM, enabling faster AI inference! Prototype locally with llama.cpp, then scale to production with vLLM using the same workflow.
• Three Years of ChatGPT: How a Simple Interface Redefined Digital LifeDec 01, 2025. Explore ChatGPT's 3-year evolution: from viral demo to essential tool. Discover its impact on work, education, creativity, and communication. A simple interface redefined digital life.
• Model Validation in ASP.NET Core Using Data AnnotationsDec 02, 2025. Master ASP.NET Core model validation using Data Annotations! This guide covers everything from basic attributes to custom rules, ensuring secure and reliable web apps.
• NanoChat Deep Dive: How Lightweight AI Chats Work Using Transformer ModelsNov 30, 2025. Explore how NanoChat delivers fast, low-resource conversational AI by using optimized Transformer pipelines. Learn architecture, workflows, use cases, limitations, and best practices.
• Efficient Soft-Delete Models Without Query Degradation in SQL Server | A Practical Guide for High-Volume OLTP SystemsDec 01, 2025. Optimize SQL Server soft-delete models for high-volume OLTP systems. Learn strategies to avoid query degradation using filtered indexes, views, and archiving for peak performance.
• SQL vs NoSQL: Strategy and System Design Considerations for Modern Data PlatformsDec 01, 2025. Explore SQL vs. NoSQL for modern data platforms. Understand key differences in data modeling, scalability, and use cases to optimize your system design.
• How Large Language Models (LLMs) WorkNov 30, 2025. Learn how Large Language Models (LLMs) work in simple, natural language. Understand tokenization, embeddings, transformers, attention, training, inference, hallucinations, applications, prompt engineering, and the future of AI.
• MCP vs RAG: The Ultimate Battle for AI DominanceNov 28, 2025. Unleash AI's potential! Explore MCP vs RAG: a head-to-head comparison of these powerful technologies for knowledge retrieval and task automation. Brains vs. Brawn!
• When Your Learning Architecture Is Not Smart Enough, Your Model Gets WorseNov 26, 2025. Stop model degradation! This article reveals how naive learning architectures (RLA/SLA) damage models. Learn to build smarter systems for reliable improvement.
• Generative AI: When Your Learning Architecture Is Not Smart Enough, Your Model Gets WorseNov 27, 2025. Generative AI models degrade with naive learning architectures. Learn how to build smarter Reinforced Learning (RLA) and Self Learning (SLA) systems for model improvement.
• LLMs: Generative AI: When Your Learning Architecture Is Not Smart Enough, Your Model Gets WorseNov 27, 2025. LLMs degrade when learning architectures (RLA/SLA) are naive. John Gödel's blueprint offers a structured, selective, and experiment-driven approach to fix it.
• Designing Transactional Microservices with Saga and Orchestration ModelsNov 25, 2025. Master transactional microservices with Saga! Learn Choreography vs. Orchestration, .NET/.Angular implementation, compensation, failure handling, and testing strategies.
• Workload Analyzer — Predict SQL Query Performance Using ML ModelsNov 24, 2025. Predict SQL query performance with ML! Prevent slow queries, reduce database incidents, and guide efficient SQL development. Integrate into CI/CD pipelines.
• Qwen3-Omni: The AI That Actually Speaks Your Language (Literally!)Nov 25, 2025. Alibaba's Qwen3-Omni is a groundbreaking AI that understands text, images, audio, and video, responding with natural speech in real-time. A true multimodal marvel!
• Workload Analyzer: Predict SQL Query Performance Using ML ModelsNov 25, 2025. Proactively optimize SQL performance with a self-learning Workload Analyzer! Predict query cost, suggest indexing, and prevent regressions using ML models.
• Building a Unified Logging Correlation Model (TraceID Propagation)Nov 24, 2025. Implement TraceID propagation across Angular, .NET, and microservices for end-to-end request tracing. Improve debugging, observability, and system reliability.
• Building Reliable Web Applications with Model Validation in ASP.NET CoreNov 24, 2025. Master ASP.NET Core model validation! Learn to build robust web apps with Required, Range, and custom rules. Prevent data corruption and ensure reliability.
• Designing a Consistency Model for Hybrid SQL + Event StoreNov 24, 2025. Achieve data consistency in hybrid SQL + Event Store architectures! Learn Transactional Outbox, Event Sourcing, CDC, and idempotent projections for reliable systems.
• 6 Types of Filters in ASP.NET Core – Complete Guide (With Examples & Use Cases)Nov 23, 2025. This article provides a complete and detailed explanation of the 6 types of Filters in ASP.NET Core, including Authorization, Resource, Action, Endpoint, Exception, and Result Filters. Each filter type is described in a clear and practical way with syntax examples, real project scenarios, and line-by-line breakdowns to help learners understand how filters work in the MVC and Web API pipeline. This guide is ideal for developers, students, and professionals preparing for .NET interviews or working on enterprise-level ASP.NET Core applications.
• Building a Unified Logging Correlation Model (TraceID Propagation) | .NET + AngularNov 21, 2025. Master distributed tracing in .NET & Angular! Learn to correlate logs, traces & metrics with Trace IDs for efficient debugging & observability. #OpenTelemetry
• Designing a Consistency Model for Hybrid SQL + Event Store | .NET Core + AngularNov 21, 2025. Master hybrid SQL & Event Store consistency! Learn Transactional Outbox, Event Sourcing, CDC patterns, plus Angular UI tips for eventual consistency. .NET Core examples.
• Designing a Consistency Model for Hybrid SQL + Event StoreNov 21, 2025. Achieve data consistency in hybrid systems! This article details a robust consistency model for SQL and Event Stores, ensuring traceability and auditability.
• Architecting a BYOK (Bring Your Own Key) Encryption ModelNov 21, 2025. Implement Bring Your Own Key (BYOK) encryption for ultimate data control. Secure .NET, SQL Server, and Angular architecture for enterprise applications. Achieve compliance and data sovereignty.
• Designing an Attribute-Value-Store (AVS) Engine inside SQL for Dynamic FieldsNov 20, 2025. Build a robust Attribute-Value-Store (AVS) engine within SQL for dynamic fields. Covers data models, indexing, validation, audit, and scaling for modern apps.
• Hybrid Query Engine: SQL + JSONB + XML within the Same Data ModelNov 20, 2025. Unify SQL, JSONB, and XML in a single data model with a Hybrid Query Engine! Query across formats with consistent performance and governance. Ideal for modern apps.
• Power BI Modeling MCP Server in VS CodeNov 18, 2025. Power BI Modeling MCP Server in VS Code empowers AI agents to access and modify semantic models, enabling automation, collaboration, and enhanced productivity.
• Microsoft Launches the New Teams SDKNov 19, 2025. Microsoft's new Teams AI Library empowers developers to build intelligent agents faster and more efficiently. Streamlined tools and advanced orchestration unlock collaborative AI.
• Building a Code Generator for Angular (Models, Services, Components) Using GPT APINov 18, 2025. Automate Angular code generation (models, services, components) using OpenAI's GPT API. Streamline development, reduce errors, and boost productivity. .NET backend & Angular UI.
• The Mathematics Behind Artificial Intelligence and Large Language ModelsNov 16, 2025. Explore the essential mathematical foundations of AI and LLMs, from linear algebra to information theory, that drive learning, reasoning, and model performance.
• The Mathematics Behind Artificial Intelligence and Large Language ModelsNov 16, 2025. Explore the mathematical foundations of AI and LLMs, from linear algebra to information theory. Understand how math drives learning, reasoning, and model design.
• The Mathematics Behind Artificial Intelligence and Large Language ModelsNov 16, 2025. Explore the essential mathematics underpinning AI and LLMs, from linear algebra to information theory. Discover how math drives learning, reasoning, and efficiency.
• Sentiment Analysis with GPT-5 and Python: A Complete 2025 GuideNov 14, 2025. Learn how to build accurate sentiment analysis systems using GPT-5 and Python. Includes architecture, code, prompt patterns, use cases, diagrams, limitations, FAQs, and optimization tips.
• Qwen3-Next: The AI Model That's Actually Affordable to RunNov 15, 2025. Qwen3-Next redefines AI accessibility. This model delivers top-tier performance with 10x faster inference and a fraction of the training cost. A game-changer!
• Artificial Intelligence: The Silent Bottleneck - Why Model Scaling Alone Cannot Deliver Reliable AINov 14, 2025. AI's future isn't just bigger models. It's robust systems: data quality, governance, orchestration. Unlock reliable AI by focusing on the ecosystem, not just scale.
• Automating Code Reviews Using AI Models (GitHub Copilot for Teams)Nov 14, 2025. Automate code reviews with GitHub Copilot for Teams! Improve code quality, speed up pull requests, and reduce bugs in Angular and .NET projects using AI-powered analysis.
• LLMs: We Should Stop Calling Them “Large Language Models”Nov 11, 2025. LLMs have evolved beyond simple language generation. This article argues for new terminology reflecting their cognitive, agentic, and multimodal capabilities.
• Gen AI: We Should Stop Calling Them “Large Language Models”Nov 11, 2025. LLMs are evolving beyond text generation. This article argues for new terminology reflecting their cognitive abilities, reasoning, and autonomous execution.
• Artificial Intelligence: We Should Stop Calling Them “Large Language Models”Nov 11, 2025. LLMs are evolving beyond text generation! This article argues for new terminology reflecting cognitive abilities, agency, and autonomous execution in modern AI systems.
• ☁️ Understanding Cloud Computing: Models, Concepts, and Consumption-Based ArchitectureNov 11, 2025. Just and introduction for beginners. Unlock the power of cloud computing! Explore models (IaaS, PaaS, SaaS), deployment strategies, pricing, and the shared responsibility model. Scale globally!
• Smart UI Personalization Using Machine Learning Models: Building Adaptive User Interfaces with .NET and AngularNov 11, 2025. Build adaptive UIs with .NET, Angular, and ML! Learn to personalize user experiences using machine learning models for enhanced engagement and retention.
• Intelligent Error Classification in Application Logs Using AI ModelsNov 11, 2025. Leverage AI for intelligent error classification in application logs using ASP.NET Core, ML.NET, OpenAI, and Angular. Automate categorization and predict issues.
• Build and Run Local AI Models Using Ollama and LangChainNov 11, 2025. Learn how to build a private, high-performance local AI assistant using Ollama and LangChain. This guide covers installation, setup, prompt orchestration, and integration with local data.
• Tokencrush, LangGraph, and the Real Economics of LLM EfficiencyNov 09, 2025. Explore Tokencrush for LangGraph and how tools like LLMCostOptimizer.com redefine enterprise LLM efficiency through deep cost analytics, optimization, and ROI-driven AI strategy.
• AI for Python Developers: OpenAI API Setup and Best Practices in 15 MinutesNov 06, 2025. Learn how to integrate the OpenAI API in Python within 15 minutes. Includes setup, environment configuration, example scripts, and production-ready best practices.
• AI Assurance You Can Operate: From Model Risk to Verifiable OutcomesNov 03, 2025. AI assurance: Transform AI from risky to reliable. Learn to manage model risk, ensure fairness, and achieve verifiable outcomes with our practical blueprint.
• MaxKB Open-Source Platform | Enterprise AI Agents & RAG PipelineNov 04, 2025. Explore MaxKB—an open-source platform by 1Panel-dev for enterprise-grade AI agents featuring RAG pipelines, agentic workflows, model-agnostic support, multi-modal input/output, and seamless integration.
• Automating Bank Statement Analysis with LLMs & RAG TechniquesNov 04, 2025. Explore how this project automates bank statement processing, uses OCR + layout models + embedding + vector DB + LLM + RAG to convert PDF statements into structured data and enable natural-language querying and financial insights.
• From Prompt Engineering to Proof: How Prompt and Context Engineering Work as OneOct 31, 2025. Unlock verified AI outcomes! Learn how prompt & context engineering unite to deliver concise, verifiable results with citations and safe tool integrations.
• Causal AI You Can Ship: From Correlation to DecisionsOct 31, 2025. Move beyond predictions! This article details a practical approach to Causal AI, emphasizing clear questions, logging, guardrails, and audits. Learn how to optimize for incremental impact and drive better decisions.
• Prompt Engineering: Prompt Observability - Traces, Metrics, and Incident ResponseOct 30, 2025. Unlock LLM reliability with prompt observability! Capture traces, metrics, & automate incident response. Debug, audit, & improve language model systems effectively.
• Artificial Intelligence: Is GPT-Image-1 a Diffusion Model? No—It’s AutoregressiveOct 31, 2025. GPT-Image-1 is autoregressive, not diffusion-based, excelling at text rendering and layout. Combine AR with diffusion for optimal image generation workflows.