172 related articles

Sorinai is a real-time AI meeting note tool that imports your own templates for auto-filling, captures system audio without bots, and supports live Q&A during meetings.

Noisegate is a differential privacy gateway for untrusted AI agents that injects calibrated noise into data flows, providing mathematically proven privacy guarantees when AI Agents process sensitive data.

Noisegate is a differential-privacy gateway for untrusted AI agents, injecting calibrated noise into data flows to provide mathematically guaranteed privacy protection for sensitive data processed by AI Agents.

Second Brain desktop brings unified persistent memory across AI tools for Mac and Windows, featuring intelligent recall, auto-built knowledge graphs, and self-hosted data via Cloudflare.

Freesolo Flash is a full-stack platform for enterprise small language model (SLM) training that commoditizes reinforcement learning, enabling teams to train specialized AI models at low cost.

SpecJudge is a fully local CLI tool that reads project spec documents to automatically recommend the best-fit AI model, avoiding costly overuse of frontier models. Supports Ollama, MIT licensed.

Google is rolling out Gemini Live conversational AI to older Google Home speakers, but subscription or plan requirements may apply. Here's what you need to know.

Google is rolling out Gemini Live conversational AI to older Google Home speakers, but subscription or plan restrictions may apply. Full breakdown of the upgrade details and impact.

A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.

Choose the right AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to help technical leaders avoid vendor lock-in.

Choose an AI Agent platform by evaluating model flexibility, observability, tool integration, security compliance, and total cost. A complete decision framework to avoid vendor lock-in.

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.

Analysis of why Gemini and other AI LLMs exhibit capability drift, including tool-calling mechanisms, context window limits, and safety policy triggers, plus practical strategies for PDF generation failures.

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.

Explore Gemini 3 Flash's core capability: extracting real textures from photos to generate design assets, helping designers and developers build custom creative tools.

An in-depth look at the three-layer funnel architecture for agent intent recognition: rules for fast interception, context for routine intents, and LLM as fallback. Exploring the engineering trade-offs of accuracy, latency, and cost.

A recursive technical proposition: Can we build a "meta-Skill" that auto-transforms any Skill into a Dify workflow? This article dissects the boundary between deterministic orchestration and autonomous Agent decisions.

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.

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.

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.