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AI Engineer Programming

In the AI era, defining problems is often more important than solving them; here we explore AI's contradictions, boundaries, and possibilities.

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Latest from AI Engineer Programming

95 recent articles

AI Engineer Programming

Apr 8, 2026 · Artificial Intelligence

TF‑IDF vs BM25: Statistical Foundations of Text Retrieval for RAG

The article explains how TF‑IDF and BM25 compute term importance, compares their strengths and weaknesses, and shows how these sparse retrieval methods integrate with dense retrieval techniques such as DPR, SPLADE, and ColBERT in Retrieval‑Augmented Generation systems, concluding with a hybrid retrieval decision matrix.

BM25Hybrid RetrievalInformation Retrieval

0 likes · 14 min read

TF‑IDF vs BM25: Statistical Foundations of Text Retrieval for RAG

AI Engineer Programming

Apr 6, 2026 · Artificial Intelligence

Designing Agent Memory: Comparative Analysis of Claude, OpenAI Codex CLI, OpenClaw, and Claude Code

This article defines agent memory, outlines its three core components and memory classifications, then provides a detailed comparative analysis of the memory designs in Claude Agent SDK, OpenAI Codex CLI, OpenClaw, and Claude Code, highlighting trade‑offs, implementation details, and engineering implications.

Agent MemoryClaudeLLM

0 likes · 29 min read

Designing Agent Memory: Comparative Analysis of Claude, OpenAI Codex CLI, OpenClaw, and Claude Code

AI Engineer Programming

Apr 5, 2026 · Artificial Intelligence

How Kimi, Cursor, and Chroma Use Reinforcement Learning to Train Agent Models

The article analyzes three recent technical reports—Moonshot AI's Kimi K2.5, Cursor's Composer 2, and Chroma's Context‑1—detailing how each system trains agent models with reinforcement learning, parallel orchestration, self‑summarization, and self‑editing, and highlights shared methodological themes and performance gains.

Chroma Context-1Cursor ComposerKimi

0 likes · 19 min read

How Kimi, Cursor, and Chroma Use Reinforcement Learning to Train Agent Models

AI Engineer Programming

Apr 2, 2026 · Artificial Intelligence

How to Rigorously Test Your Own Trained LLM and Choose the Right Benchmarks

This guide outlines a systematic LLM evaluation framework, covering goal definition, core and code‑oriented benchmarks, agent and safety tests, data‑contamination mitigation, toolchain choices, result reporting, and the inherent structural limits of static benchmarks.

AgentLLMSafety

0 likes · 14 min read

How to Rigorously Test Your Own Trained LLM and Choose the Right Benchmarks

AI Engineer Programming

Apr 1, 2026 · Industry Insights

When AI’s Hype Bubble Deflates: From Marketing Showpiece to Real‑World Tool

The article analyzes how AI is shifting from excessive marketing hype to practical tooling, highlighting massive capital spending, low deployment maturity, a productivity paradox in software development, and the emerging risks and governance challenges of AI agents.

AIAI agentsGovernance

0 likes · 12 min read

When AI’s Hype Bubble Deflates: From Marketing Showpiece to Real‑World Tool

AI Engineer Programming

Mar 31, 2026 · Artificial Intelligence

How AI Agents Achieve Self‑Evolution Through Context Engineering

The article defines AI Agent self‑evolution as an autonomous loop of perception, learning, and optimization, outlines its three evolutionary levels, key characteristics, core development components, reviews leading frameworks such as EvoSkill and DGM‑Hyperagents, and discusses safety laws for controllable evolution.

AI agentAutonomous SystemsContext engineering

0 likes · 9 min read

How AI Agents Achieve Self‑Evolution Through Context Engineering

AI Engineer Programming

Mar 30, 2026 · Artificial Intelligence

Is GUI or CLI the Better Choice for Agent‑Native Interfaces?

The article analyzes how AI agents shift interaction paradigms from visual GUIs to structured, deterministic CLI protocols, citing tools like Claude Code, OpenClaw, and benchmark data that show CLI’s efficiency advantages while acknowledging the continued role of GUIs for human users.

AI agentsAgent NativeCLI

0 likes · 7 min read

Is GUI or CLI the Better Choice for Agent‑Native Interfaces?

AI Engineer Programming

Mar 30, 2026 · Artificial Intelligence

Agent, Multi‑Agent, Deep Agent: Start Simple, Add Complexity Only When Needed

The article clarifies the distinct meanings of Agent, Multi‑Agent, and Deep Agent, explains how control shifts from engineers to models, compares architectures across nine dimensions, and shows why a lightweight harness is essential for long‑running, parallel AI‑driven software development.

AgentDeep AgentHarness

0 likes · 22 min read

Agent, Multi‑Agent, Deep Agent: Start Simple, Add Complexity Only When Needed

AI Engineer Programming

Mar 29, 2026 · Information Security

Why AI Agents' API Keys Are a Massive Security Blind Spot

The article analyzes how AI agents often store raw API keys in environment variables, exposing them to prompt‑injection attacks, unchecked privileged actions, and amplified damage, and evaluates the OneCLI proxy‑based solution along with its limitations, technical challenges, and practical mitigation steps.

AI agentsAPI key securityOneCLI

0 likes · 11 min read

Why AI Agents' API Keys Are a Massive Security Blind Spot

AI Engineer Programming

Mar 28, 2026 · Artificial Intelligence

How to Start Training Your Own AI Model: A Complete Roadmap

This guide maps the end-to-end process for building a small AI model—from leveraging open-source base models and applying SFT with LoRA/QLoRA, through alignment techniques like DPO or ORPO, to low-cost distillation and final quantization for local deployment, while recommending free GPU resources and essential tooling.

AIDistillationLoRA

0 likes · 12 min read

How to Start Training Your Own AI Model: A Complete Roadmap