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Qborfy AI

A knowledge base that logs daily experiences and learning journeys, sharing them with you to grow together.

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Recent Articles

Latest from Qborfy AI

92 recent articles
Qborfy AI
Qborfy AI
Aug 31, 2026 · Artificial Intelligence

Build an Enterprise‑Level AI Research Report Generator from Scratch with LangGraph

This article provides a step‑by‑step walkthrough for constructing a daily industry research‑report automation system using LangGraph, covering fan‑out parallel search, fan‑in aggregation, an evaluator‑optimizer feedback loop, human‑in‑the‑loop approval, checkpointing for resumability, and full observability with Langfuse, complete with runnable code.

AI automationHITLLangGraph
0 likes · 24 min read
Build an Enterprise‑Level AI Research Report Generator from Scratch with LangGraph
Qborfy AI
Qborfy AI
Aug 30, 2026 · Artificial Intelligence

Human-in-the-Loop and Time-Travel Debugging: Making AI Graphs Production-Ready

The article explains why autonomous agents need human supervision in critical steps, introduces three HITL scenarios, shows how LangGraph’s interrupt_before/after and update_state enable pause‑and‑review workflows, demonstrates time‑travel debugging and observability with Langfuse, and provides practical design principles and a production‑grade configuration.

AgentLangGraphLangfuse
0 likes · 20 min read
Human-in-the-Loop and Time-Travel Debugging: Making AI Graphs Production-Ready
Qborfy AI
Qborfy AI
Aug 29, 2026 · Artificial Intelligence

AI Session Memory Management: State Design, Reducers, and Checkpointing

This article examines common pitfalls in State design for LangGraph AI workflows, explains how Reducer functions resolve concurrent writes, compares short‑term, thread‑level, and long‑term memory architectures, and demonstrates practical Checkpointing and Time‑Travel techniques for robust session persistence.

AI AgentsLangGraphMemory Management
0 likes · 21 min read
AI Session Memory Management: State Design, Reducers, and Checkpointing
Qborfy AI
Qborfy AI
Aug 27, 2026 · Artificial Intelligence

Choosing Between LangGraph and AutoGen: A Deep Dive into Nodes, Edges, and State

This article explains the three core concepts of graph engineering—Node, Edge, and State—then dissects the design philosophies of LangGraph and AutoGen, comparing their architectures, strengths, limitations, and suitable use‑cases to help developers select the right framework without pitfalls.

AI AgentsAutoGenEdge
0 likes · 24 min read
Choosing Between LangGraph and AutoGen: A Deep Dive into Nodes, Edges, and State
Qborfy AI
Qborfy AI
Aug 26, 2026 · Artificial Intelligence

How Graph Engineering Tames Uncontrolled AI Agents and Solves Prompt Fatigue

The article explains that "prompt fatigue" stems from cramming multiple roles and tasks into a single LLM prompt, which causes attention competition and context pollution, and shows how Graph engineering restructures agents into specialized state nodes to isolate context, specialize roles, and enforce controllable workflows, backed by Anthropic’s 90% quality gain at a 15‑fold token cost.

AI Agent DesignAnthropicGraph Engineering
0 likes · 14 min read
How Graph Engineering Tames Uncontrolled AI Agents and Solves Prompt Fatigue
Qborfy AI
Qborfy AI
Aug 24, 2026 · Artificial Intelligence

How Small Businesses Can Deploy Ontology Without Building a Big Platform

SMEs can adopt lightweight ontologies to improve AI agents in three real-world scenarios—smart customer service, unified sales lead semantics, and inventory‑procurement reconciliation—by explicitly modeling product rules, regional hierarchies, and stock relationships, avoiding hallucinations and heavy platforms while enabling accurate, data‑driven answers.

AI AgentsCustomer ServiceKnowledge Graph
0 likes · 10 min read
How Small Businesses Can Deploy Ontology Without Building a Big Platform
Qborfy AI
Qborfy AI
Aug 20, 2026 · Artificial Intelligence

How UI Ontology and Neuro‑Symbolic AI Enable Agents to Operate a Computer

The article explains why a computer screen itself forms a spatial ontology, how Anthropic trained Claude to compute pixel coordinates and reason over UI elements, the four‑step action loop, benchmark results on OSWorld, prompt‑injection risks, and why combining symbolic and connectionist approaches—neuro‑symbolic AI—is essential for reliable computer‑using agents.

AI AgentsClaudeOSWorld benchmark
0 likes · 9 min read
How UI Ontology and Neuro‑Symbolic AI Enable Agents to Operate a Computer
Qborfy AI
Qborfy AI
Aug 18, 2026 · Artificial Intelligence

How to Build Secure AI Agents with Palantir’s OSDK and Ontology MCP

This article explains why Palantir requires ontology binding as the first step for AI agents, describes the OSDK and Ontology MCP toolchain that provide type‑safe access and a standard protocol for external agents, and walks through a minimal agent example with code, permissions, and a key pitfall.

AI AgentMCPOSDK
0 likes · 10 min read
How to Build Secure AI Agents with Palantir’s OSDK and Ontology MCP
Qborfy AI
Qborfy AI
Aug 13, 2026 · Artificial Intelligence

Microsoft Fabric Ontology Semantic Layer: Architecture, NL2Ontology & Palantir Contrast

The article analyzes how Microsoft Fabric builds an enterprise semantic layer using ontology—defining entity types, properties, relationships, and data binding—and explains NL2Ontology's natural‑language‑to‑query translation while contrasting this approach with Palantir's decision‑centric model.

AI AgentKnowledge GraphMicrosoft Fabric
0 likes · 10 min read
Microsoft Fabric Ontology Semantic Layer: Architecture, NL2Ontology & Palantir Contrast