#LLM application engineer
2611 related articles
Tutorials·2 min
pnpm Monorepo Full-Stack AI Engineering in Practice: Building a Multimodal Conversation System
Learn how to build a full-stack multimodal AI conversation system using pnpm Monorepo architecture, covering local model integration, image understanding, and streaming chat.
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Tutorials·3 min
Building AI Agents with Node.js: Replacing Prompt Engineering with Function Calls
Learn how to refactor a Node.js AI Agent using Function Calls instead of prompt engineering. Covers tool definition via JSON Schema, the Agent Loop, and key implementation details from analyzing Claude Code.
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Tutorials·3 min
Context Engineering in Practice with CodeBuddy IDE: Two Rule Files to Generate Apps with a Single Sentence
Learn how to apply Context Engineering in CodeBuddy IDE using two custom rule files — a Requirements-to-TODO-LIST engine and a Project Execution engine — to generate complete apps with a single sentence.
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Industry Insights·3 min
Should Custom Software Teams Go All-In on LLMs? ChatGPT Itself Gave the Answer
Should custom software teams go all-in on LLMs? Through a deep conversation with ChatGPT, we analyze scenario selection, Token costs, and industry fit to provide a rational decision framework for ToB developers.
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Tutorials·3 min
35 Lines of Prompts Let Codex Auto-Optimize Your Workflow — Reposted by OpenAI's President
An OpenAI employee used just 35 lines of prompts to have Codex analyze 30 days of work history, identify repetitive tasks, and generate reusable automated Skills. Combined with screen reading and long-term memory, Codex is becoming a proactive workflow optimization agent.
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Tech Frontiers·2 min
Claude Opus 4.8 Thinking Effort Calibration Explained: A Critical Optimization Direction for AI Reasoning Models
Anthropic releases Claude Opus 4.8 with optimized thinking effort calibration. This article explains what it is, why it matters for AI reasoning models, and its impact on industry competition.
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Tutorials·3 min
A Complete Guide to Using AI Agents for Product Launch Videos, Growth Marketing, and Business Plans
How to use AI Agents for product launch videos, multi-platform growth marketing, and business plan writing — a complete workflow for indie developers building one-person companies.
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Product Reviews·2 min
Claude Opus 4.8 Real-World Testing: What $50 in Tokens Actually Gets You
In-depth testing of Claude Opus 4.8 across game dev, UI reproduction, 3D scenes, and tool building—$50 in Tokens reveals its true capabilities and limits.
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Tech Frontiers·2 min
OpenAI Voice Hackathon: 4 Real-Time Voice AI Projects Built in Just 6 Hours
OpenAI hosted Voice Hack Night where teams built 4 real-time voice agent projects in 6 hours. Deep analysis of technical challenges, use cases, and developer ecosystem trends in real-time voice AI.
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Tutorials·3 min
Build a Claude Code Agentic OS in 3 Steps — Stop Using AI Like a Slot Machine
Learn how to transform Claude Code from a random prompting tool into a systematic Agentic OS through three layers: architecture, Obsidian memory, and an observability dashboard.
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Product Reviews·3 min
Zion No-Code Platform Hands-On: Building a Production-Ready E-commerce Mini Program from Scratch Without Writing a Single Line of Code
Hands-on review of Zion no-code platform: building a production-ready e-commerce mini program from scratch with visual design, built-in database, workflow orchestration, AI Agent integration, and one-click multi-platform publishing.
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Tutorials·2 min
Tutorial: Deploying a PD-Disaggregated SGLang Multi-Node Inference Cluster on AMD GPUs
Learn how to deploy a PD-disaggregated SGLang inference cluster on AMD GPUs using a single config file, boosting LLM throughput and latency performance.
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Tech Frontiers·2 min
Step 3.7 Flash: Deep Dive into the 198B Sparse MoE Multimodal Model
Deep dive into StepFun AI's Step 3.7 Flash, a 198B sparse MoE vision-language model with 256K context and 3-level reasoning, excelling in multimodal understanding, AI coding, and Agent tool orchestration.
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Tech Frontiers·2 min
LFM2.5-8B-A1B: A MoE Model with 1.5B Active Parameters Delivering 4x Its Weight Class Performance
Liquid AI releases LFM2.5-8B-A1B, a MoE model with 8B total params but only 1.5B active, matching 6B-class models in tool calling. Supports 128K context, local deployment, multilingual, with SGLang Day-0 support.
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Industry Insights·2 min
SGLang Enters Finance: How AI Inference Infrastructure Is Reshaping Wall Street
SGLang co-hosts a finance AI inference event with Crusoe AI and Cloudflare, exploring LLM inference deployment in trading, risk management, and compliance — signaling Wall Street's shift to production-grade AI infrastructure.
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Tutorials·3 min
BMad-Method: Building an AI Agile Development Team with a Multi-Agent Framework
Deep dive into BMad-Method, an open-source multi-agent framework simulating a full agile team—from business analysis to QA—supporting Claude Code, Cursor, and more.
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Tutorials·3 min
Claude Code Source Code Study Guide: Efficiently Mastering Core AI Agent Development Architecture
Learn AI Agent development from Claude Code's 510K lines of source code, covering Agent Loop, context compression, multi-Agent orchestration, and two efficient study methods.
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Tutorials·3 min
Spring AI Agent Utils: A Java Agent Toolkit Reverse-Engineered from Claude Code's Core Features
Deep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
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Research·3 min
MixupMP: How Data Augmentation Fixes the Uncertainty Quantification Flaws of Deep Ensembles
Deep dive into AISTATS 2024 paper MixupMP: revealing Deep Ensembles' fundamental UQ flaws and fixing them via Mixup augmentation and Martingale Posterior framework for better calibration and OOD detection.
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Tutorials·3 min
AI Programming Spec Sheets: 30 Lines of Configuration Saves Five Rounds of Rework
Replace vague prompts with spec sheets—30 lines of config gets AI coding right the first time. Covers the six-element framework, three-tier boundaries, and three iron rules to eliminate rework.
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