#LLM memory extraction
211 related articles
·3 min
Deconstructing Agents: Task Decomposition, Context Compression, and the Case Against Heavy Frameworks
A deep engineering analysis of Agent internals: how LLMs decompose tasks via tool calling, why context compression and memory are essential, and why solo developers should avoid heavy frameworks.
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·3 min
Rusty HLP Viewer: A Cross-Platform Tool for Natively Opening Legacy HLP Help Files
Rusty HLP Viewer is the first open-source tool to natively open Windows HLP help files. Built in Rust, it runs on Windows, Linux, and macOS without format conversion.
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·5 min
Complete Breakdown of Core Competencies for AI Agent Engineers: From Demo to Production-Grade Systems
Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.
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·3 min
Self-Hosted Receipt Tracking Tools: Monitoring Grocery Expenses and Price Changes
Explore self-hosted receipt tracking tools for grocery expense management, covering OCR recognition, price tracking, food categorization, and budget management with open-source solutions like Firefly III.
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·3 min
DeepSeek-OCR Deployment and Fine-Tuning: A Complete Hands-On Guide
Master the full DeepSeek-OCR deployment and fine-tuning workflow: vLLM inference deployment, efficient Unsloth fine-tuning, dataset preprocessing, LoRA training, validation, and RAG vector database integration.
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·3 min
Laguna S 2.1: The Open-Source Coding Model That's 14x Smaller Yet Stronger
Poolside releases Laguna S 2.1, an open-source agentic coding model: 118B total params with only 8B active, scoring 40.4% on DeepSWE — ~4.5x DeepSeek V4 Pro Max. Supports 1M-token context, deployable on a single workstation.
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·8 min
A Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.
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·8 min
The Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.
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·4 min
Building an AI-Automated Topic Selection System: A Practical Guide to the Three-Dimension Method
Learn how Bilibili creator JK built an AI-automated topic selection system using Codex and Feishu — covering the three-dimension method: practice, trending topics, and benchmarking.
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·3 min
LoRA Fine-tuning or Prompt Engineering? Two Paths to Solving LLM Long-Conversation Memory
A developer fine-tunes a small model with LoRA to extract conversation state, tackling the LLM long-conversation memory problem. A deep dive into the technical approach, dataset design, and the real trade-offs between fine-tuning and prompt engineering.
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·7 min
Auditing Cryptographic Libraries with AI: What We Found in Cloudflare's CIRCL
An in-depth look at using AI LLMs to audit Cloudflare's open-source cryptographic library CIRCL, covering constant-time detection, side-channel vulnerabilities, and human-AI collaboration.
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·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
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·7 min
From Chat to Agent Platform: A Practical Guide to Engineering AI Applications
A deep dive into engineering AI applications: from a simple chat page to a multi-layer Agent platform, covering RAG knowledge bases, Workflow scheduling, multi-model management, and run tracing.
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·4 min
Zero-Code AI Voice Agents with Claude Code: 5 Real-World Business Scenarios Unpacked
Build a production AI voice agent with Claude Code + Telnyx single-stack — no code needed, live phone number in 5 minutes. Covers 5 business scenarios including appointment booking, lead qualification, and support triage.
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Cognee: The Open-Source Knowledge Grap…
·2 min
Cognee: The Open-Source Knowledge Graph Engine for Persistent AI Agent Memory
Cognee is an open-source AI memory platform using knowledge graphs to give AI agents persistent cross-session memory. Self-hosted, graph + vector hybrid retrieval. 28K+ GitHub stars.
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GitHub Daily · July 21: The Agent Skil…
·3 min
GitHub Daily · July 21: The Agent Skills Ecosystem Explodes, Intelligence Dashboard Tops the Charts
GitHub Trending July 21: The Agent Skills ecosystem explodes as pluggable skill packs top the charts, MCP becomes the de facto standard, and ai-agent-book surges 4,434 stars in a day.
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·3 min
The Complete Guide to AI-Native Architecture: RAG, Agents, and MCP
A comprehensive guide to AI-native application architecture: LLM inference, RAG retrieval (vector DB/knowledge graph/BM25), Agents, MCP tool calling, AI gateways, and observability — end-to-end.
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·3 min
AI Agent Production Guide: Four Orchestration Patterns That Actually Work
Most AI agents never make it past the demo stage. This guide covers four production-grade agent patterns—workflow orchestration, policy-constrained execution, anomaly handling, and load routing—to help teams build reliable agent systems.
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The Guardian Angels Framework: How LLM…
·3 min
The Guardian Angels Framework: How LLM Personalization Can Achieve Both Efficiency and Data Security
The Guardian Angels framework shows how LLM personalization can achieve both productivity and data security through local deployment, differential privacy, and tiered permissions.
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·4 min
Viktor: The AI Employee Living Inside Slack — How to Build a True Company-Wide AI Colleague
Viktor is a Slack-native AI employee with 3,000+ integrations and team-shared context. Learn how it evolved from browser agents to company-level AI, tackling memory, permissions, and proactivity.
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