1686 related articles
Expert OpinionsCan AI write code instantly—so is coding still worth learning? An Atlassian engineer breaks down the truth behind tech leaders' claims and AI coding limitations.
TutorialsLearn how to use DeepSeek to rewrite ASR local AI project startup scripts from countdown mode to intelligent output-based detection, with full steps and troubleshooting tips.
Deep DivesDeep analysis of NousResearch's Hermes Agent Self Evolution project: GIPA genetic Pareto prompt evolution algorithm, six-step optimization loop, and five guardrail mechanisms for real-world Agent self-evolution.
Industry InsightsDeep dive into five core design patterns for long-running AI Agents from Google Cloud Next 26: checkpoint recovery, delegated approval, hierarchical memory, ambient processing, and cluster orchestration.
Product ReviewsA non-coder indie developer shipped a product in 16 days using Gemini, Cline, MiniMax, and DeepSeek. Full retrospective on tool selection, model quality gaps, and practical lessons learned.
Tech FrontiersOpenAI's GPT-5.6 has entered internal testing, just three weeks after GPT-5.5. The key accelerator is the self-training loop introduced in GPT-5.3, enabling exponential iteration speed.
TutorialsAnthropic engineers share how to properly use Claude Code at AI Code Summit: build composable Skills systems instead of one-off prompts. Master four core rules for skills that get smarter over time.
Product ReviewsRoundup of 6 developer tools: CodeBurn for AI coding token cost tracking, Mirage virtual file system for Agents, Boring SSH tunnel manager, PeerTrace file tree renderer, DataTab font-based data visualization, and Flu TypeScript Agent framework.
Tech FrontiersAnthropic let AI Agent Luna autonomously run a physical store with $100K. It lost $13K in one month after trying to hire from Afghanistan, ordering 1,000 toilet seats, and giving random discounts.
Product ReviewsHands-on review of Manus AI Agent on the DeepSeek tech stack, analyzing task execution, Chinese reasoning capabilities, strengths, limitations, and the potential of domestic LLMs in Agent applications.
Tech FrontiersDeepSeek-V3.2 released with coding, math, and Agent capabilities matching Gemini 3.0 Pro, setting new open-source SOTA. Detailed analysis of performance gains, use cases, and deployment tips.
Expert OpinionsReplit CEO Amjad Massad on AI coding models hitting a ceiling, competition shifting to product engineering, SaaS being replaced by AI Agents, the death of the IDE, and multi-model orchestration.
TutorialsA complete workflow for collaborative UE5 development using DeepSeek multi-Agent matrix and UE5.8 official MCP, covering pure C++ architecture, agent roles, cache optimization, and automated code review.
Tech FrontiersHermes Agent 0.14.0 Foundation Update: local proxy unified auth, 180x browser automation speedup, native Windows support, AI video generation, free DeepSeek V4, and lossless Handoff context switching.
Tech FrontiersGPT-5.6 internal testing launches UltraFast mode, Codex goal-driven mode revolutionizes AI programming, MiniMax cuts costs 360x, Anthropic vs OpenAI valuation war, Cerebras IPO raises $5.55B, Figure robot validates 8-hour autonomous ops, Google Vio 3.1 leads AI video.
Product ReviewsHands-on review of an AI companion chat app featuring unrestricted dialogue, analyzing its roleplay, story interaction, and custom character creation while comparing it to Character.AI and SillyTavern.
TutorialsIn-depth analysis of Google's Gemma 4 open-source models: 31B, 26B MOE, and 14B/12B benchmarks, deployment guides for all platforms, and MS-Swift fine-tuning tutorial for building local Agent workflows.
Product ReviewsHands-on testing of Google Gemma 4 open-source models running offline on three phones, with Dense vs MOE architecture explained and a complete Ollama + Claude Code deployment tutorial.
TutorialsLearn how to use AI agents to auto-generate Excel test cases. Covers Coze platform setup, Dify private deployment with DeepSeek + Ollama, workflow design tips, and prompt engineering for testers.
Deep DivesA deep dive into the complete RAG pipeline — covering vector embeddings, document chunking, retrieval and reranking, plus three production optimization techniques for building accurate enterprise AI knowledge base applications.