#LLM engineer
3611 related articles
·3 min
Why We Abandoned Our LLM Router: Lessons in Over-Engineering
An in-depth analysis of why teams are abandoning LLM routers, exploring hidden complexity costs, outdated cost assumptions, and how to avoid over-engineering in AI systems.
Read more →
·3 min
Agent Skill Routing: Engineering Trade-offs Between Retrieval and LLM, and the Two-Stage Layered Architecture
Deep dive into Agent skill routing: comparing pure model vs. pure retrieval approaches, with a detailed two-stage layered architecture balancing accuracy, latency, and cost.
Read more →
·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.
Read more →
·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Agent Topics
A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.
Read more →
·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Topics in the Agent Domain
A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.
Read more →
·2 min
3-Month Roadmap to Becoming an AI/LLM Engineer: A Systematic Learning Guide
A 3-month structured roadmap for developers transitioning into AI/LLM engineering: Python & API basics, LangChain/FastAPI stack, and RAG/Agent projects.
Read more →
·3 min
AI-Powered Python Reverse Engineering: A Full Retrospective on Using LLMs to Accelerate the Workflow
A real-world retrospective on AI-assisted Python reverse engineering: from JS obfuscation tracing and SM2/SM4 key extraction to generating decryption code with DeepSeek. An honest assessment of LLM value and legal risks.
Read more →
·4 min
Six Layers of Defense: Engineering Reliable Structured Output from LLMs
LLM JSON output unstable in your Agent? This guide covers 6 engineering layers: constrained decoding, validation retry, fake tool calls, Logit Masking, Schema contracts, and anti-pattern locking.
Read more →
Loving LLMs, Hating the Hype: How Engi…
·2 min
Loving LLMs, Hating the Hype: How Engineers Rationally Evaluate Large Language Models
Engineers love LLMs for real productivity gains but hate the hype around AGI narratives, glossed-over hallucinations, and valuation bubbles. Here's how to find the rational balance.
Read more →
·1 min
Agentic Coding in Practice: Test Feedback Loops, LLM Benchmarks, and an Engineering Adoption Guide
An in-depth look at agentic coding: how test-driven loops enable AI self-correction, the real limits of LLM benchmarks, and key engineering lessons on context management and human-AI collaboration.
Read more →
·2 min
4-Step Roadmap to Becoming an AI Agent Engineer: From Zero to a $50K LLM Role
A proven 4-step roadmap to becoming an AI Agent engineer: stable LLM calls, tool use (RAG + Function Calling), production engineering, and resume optimization.
Read more →
·3 min
4 Core Competencies Every High-Value LLM Application Engineer Must Have
Why can't companies find qualified AI engineers? Discover the 4 core competencies every high-value LLM application engineer needs: task decomposition, tool calling, observability, and production readiness.
Read more →
·3 min
Andrew Ng's Prompt Engineering Course: How Developers Call LLMs via API
A systematic overview of Andrew Ng's ChatGPT Prompt Engineering for Developers course: base vs. instruction-tuned models, API best practices, and two core prompting principles.
Read more →
·4 min
LLM Job Interviews: Multi-Agent and Harness Engineering Are Now Must-Know Topics
Deep analysis of LLM job interview essentials: Multi-Agent architecture, Harness engineering, Agent Loop, sandbox isolation, and memory management with career transition tips.
Read more →
Tutorials·1 min
Essential Skills for LLM Engineers: A Complete Guide to Application Development and Fine-Tuning
A systematic guide to LLM engineer core skills covering RAG, Agent app development and SFT, RLHF fine-tuning, with clear learning paths for different backgrounds.
Read more →
Tutorials·2 min
Career Prospects for LLM Development Engineers: Job Categories, Education Requirements, and Learning Paths
In-depth analysis of three LLM engineer career paths (Application, R&D, Algorithm), bachelor's degree entry, core algorithms, salary benchmarks, and a three-tier learning roadmap.
Read more →
Tutorials·2 min
OpenCode + LLM Automated Environment Patching: A Complete JS Reverse Engineering Workflow
Learn how to use OpenCode with DeepSeek LLM and System Prompts to automate JS reverse engineering environment patching for Taobao, Xiaohongshu, and more.
Read more →
Tutorials·2 min
AI LLMs Auto-Patching Browser Environments: A Practical Guide to 10x JS Reverse Engineering Efficiency
Learn how to use AI LLMs like DeepSeek with System Prompts to auto-patch JS browser environments for reverse engineering, covering major platforms with 10x efficiency gains.
Read more →
Tutorials·3 min
The Complete Guide to MLflow: An Open-Source AI Engineering Platform from Experiment Tracking to LLM Deployment
A deep dive into the MLflow open-source AI engineering platform, covering experiment tracking, LLM evaluation, model deployment, and monitoring to help teams efficiently manage the ML lifecycle.
Read more →
·2 min
Samsung Support Agent Accidentally Pastes ChatGPT Prompt, Exposing How AI Customer Service Really Works Behind the Scenes
A Samsung support agent accidentally pasted a ChatGPT prompt into a customer chat, revealing how enterprise AI customer service really operates behind the scenes.
Read more →