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Alibaba Cloud Developer

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Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 16, 2026 · Industry Insights

Rethinking AI Coding: Multi‑Agent Collaboration as the New Development Paradigm

The article analyzes the shift from single‑agent AI coding workflows to a multi‑agent collaboration model, proposing a spec‑driven orchestration framework, observable claims, and a review‑centric UI called Mexus to enable efficient parallel development, conflict resolution, and human oversight.

AI codingMulti-Agent CollaborationObservability
0 likes · 15 min read
Rethinking AI Coding: Multi‑Agent Collaboration as the New Development Paradigm
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 15, 2026 · Artificial Intelligence

Uncovering OpenClaw’s Memory Weaknesses and How RDSClaw’s Plugin Gains a 14% Accuracy Boost

This article dissects OpenClaw’s multi‑layer markdown‑based memory pipeline, highlights the instability caused by LLM‑driven write decisions and token‑threshold flushes, and then presents the RDSClaw memory plugin that adds deterministic extraction, real‑time CRUD integration, and vector‑based de‑duplication, resulting in a 13.9% overall accuracy improvement on the LoCoMo10 benchmark.

0 likes · 22 min read
Uncovering OpenClaw’s Memory Weaknesses and How RDSClaw’s Plugin Gains a 14% Accuracy Boost
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 14, 2026 · Operations

Why Browser Automation Fails and How OpenCLI’s API‑First Approach Solves It

The article explains why traditional UI‑based browser automation is unstable, proposes extracting and reproducing underlying API requests instead, and introduces OpenCLI’s workflow—including rapid setup, a five‑tier authentication strategy, adapter generation, AI‑driven CLI synthesis, and current limitations—to achieve more efficient and reliable automation.

API extractionBrowser automationCLI generation
0 likes · 10 min read
Why Browser Automation Fails and How OpenCLI’s API‑First Approach Solves It
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 7, 2026 · Artificial Intelligence

Rethinking Agent Memory: From Raw Ledgers to Non‑Parametric Systems

This article analyses the nature of memory for LLM‑based agents, arguing that memory is a closed‑loop system composed of a raw ledger, derived views, and a policy layer, and explores how non‑parametric designs, system‑2 architectures, temporal structuring, and skill‑based execution can bridge the gap between parametric and non‑parametric memory while highlighting key bottlenecks and practical design guidelines.

LLMmemory systemsnon‑parametric memory
0 likes · 50 min read
Rethinking Agent Memory: From Raw Ledgers to Non‑Parametric Systems
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 3, 2026 · Artificial Intelligence

Why AI Agents Stumble at Code and How a Harness Can Make Them Reliable

The article explains why large‑language‑model agents often lose context and violate architectural rules when generating code, and proposes a Harness framework that treats the repository as an operating system, adds layered linting, pre‑validation, automated verification, and cross‑model review to keep agents on track.

LLMcode generationlinting
0 likes · 21 min read
Why AI Agents Stumble at Code and How a Harness Can Make Them Reliable
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 3, 2026 · Artificial Intelligence

Why OpenClaw Gets Smarter Over Time: Inside Its Self‑Evolving Markdown Engine

The article explains how OpenClaw’s “use‑more‑you‑use‑more” effect stems from a self‑evolving markdown file system that records agent identity, user profile, skills, memory, and lessons, enabling continuous learning, precise retrieval, and personalized AI behavior without changing the underlying model.

OpenClawmarkdown knowledge basememory indexing
0 likes · 15 min read
Why OpenClaw Gets Smarter Over Time: Inside Its Self‑Evolving Markdown Engine
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 2, 2026 · Artificial Intelligence

How ADB MySQL Turns Agent Logs into Actionable Insights – A Step‑by‑Step Guide

This article analyzes why over 40% of Agentic AI projects fail due to inadequate observability, outlines three common pain points—trace blindness, uncontrolled token costs, and untraceable failures—and demonstrates a practical ADB MySQL solution that reconstructs logs, classifies failures with AI functions, quantifies token waste, and generates prompt‑optimization suggestions, all with a few SQL statements.

ADB MySQLAI AgentsAgent Observability
0 likes · 10 min read
How ADB MySQL Turns Agent Logs into Actionable Insights – A Step‑by‑Step Guide
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 30, 2026 · Artificial Intelligence

Harness Engineering: Turning AI Agents into Reliable Digital Teams

This article analyzes the emerging paradigm of Harness Engineering, explaining how prompt, context, and feedback-loop innovations enable AI agents to act as controllable, scalable digital workers, and illustrates the concept with four real‑world case studies and open‑source projects that push the limits of AI‑driven software development.

Context EngineeringGroup IntelligenceHarness Engineering
0 likes · 19 min read
Harness Engineering: Turning AI Agents into Reliable Digital Teams