2026-01-26 Tech Briefing | SKILLS tackles AI programming token issues with modular rules and lightweight scripts.

Monday

Welcome to this edition, featuring 13 articles.

📚 Contents/📝 TL;DR

📚 Contents

📝 TL;DR

Primary

# Understand SKILLS: Modular Rules + Lightweight Scripts

SKILLS tackles AI programming token issues with modular rules and lightweight scripts.

# Understand SKILLS: Modular Rules + Lightweight Scripts

SKILLS tackles AI programming token issues with modular rules and lightweight scripts.

Is React Source Code Worth Reading in 2026? ❓❓❓

Analysis and recommendations on the value of reading React source code in 2026.

Is React Source Code Worth Reading in 2026? ❓❓❓

Analysis and recommendations on the value of reading React source code in 2026.

Former Megvii CEO Yin Qi Takes Over as Chairman of Jiayue Xingchen

Former Megvii CEO Yin Qi becomes Chairman of Jiayue Xingchen, responsible for strategy and technology.

Former Megvii CEO Yin Qi Takes Over as Chairman of Jiayue Xingchen

Former Megvii CEO Yin Qi becomes Chairman of Jiayue Xingchen, responsible for strategy and technology.

Essential

How Fuzhuang Reduced Ad Outbound System Timeout Rate to 0.01% Under Billion-Level Requests

Fuzhuang RTA system optimization, reduced timeout rate from 30% to 0.01% at million-level QPS.

How Fuzhuang Reduced Ad Outbound System Timeout Rate to 0.01% Under Billion-Level Requests

Fuzhuang RTA system optimization, reduced timeout rate from 30% to 0.01% at million-level QPS.

Meituan's EvoCUA Refreshes Open-Source SOTA, Achieving a Self-Improving Computer-Using Agent

Meituan's EvoCUA refreshes the open-source SOTA in OSWorld, realizing a self-evolving computer-operating agent.

Meituan's EvoCUA Refreshes Open-Source SOTA, Achieving a Self-Improving Computer-Using Agent

Meituan's EvoCUA refreshes the open-source SOTA in OSWorld, realizing a self-evolving computer-operating agent.

Former OpenAI Senior Member Jerry Tworek Leaves, Criticizes Industry Entertaining Trends and Homogenization

Jerry Tworek, a former OpenAI senior member, leaves and criticizes industry entertainment and homogenization, attributing Google's catch-up to OpenAI's mistakes.

Former OpenAI Senior Member Jerry Tworek Leaves, Criticizes Industry Entertaining Trends and Homogenization

Jerry Tworek, a former OpenAI senior member, leaves and criticizes industry entertainment and homogenization, attributing Google's catch-up to OpenAI's mistakes.

AI Agent Is a Long-Running 'Risk System'; Only Preventing Prompt Injection Is No Longer Sufficient

AI Agent security must guard against instruction detection and historical poisoning, not just Prompt Injection.

AI Agent Is a Long-Running 'Risk System'; Only Preventing Prompt Injection Is No Longer Sufficient

AI Agent security must guard against instruction detection and historical poisoning, not just Prompt Injection.

General

E222｜The Decline of Tight Pants, Who Defines the Fashion Trend?

Podcast explores the decline of tight pants and the rise of loose styles, analyzing changes in fashion trends.

E222｜The Decline of Tight Pants, Who Defines the Fashion Trend?

Podcast explores the decline of tight pants and the rise of loose styles, analyzing changes in fashion trends.

Data Engineering Weekly #254

Data engineering weekly report, focusing on AI, LLM, and data architecture trends and conferences.

Data Engineering Weekly #254

Data engineering weekly report, focusing on AI, LLM, and data architecture trends and conferences.

Zi Yi's 2025 Annual Review

Annual 2025 personal review, covering AI programming, Agent development, frontend frameworks, financial management, and sports.

Zi Yi's 2025 Annual Review

Annual 2025 personal review, covering AI programming, Agent development, frontend frameworks, financial management, and sports.

Differences and Use Cases of deep, v-deep, and >>> in Vue

In Vue, scoped styles penetration, ::v-deep and >>> have been deprecated, and :deep() is the recommended approach.

Differences and Use Cases of deep, v-deep, and >>> in Vue

In Vue, scoped styles penetration, ::v-deep and >>> have been deprecated, and :deep() is the recommended approach.

Global Perspective on January 25, 2026

International news compilation covering politics, economy, culture, and nature.

Global Perspective on January 25, 2026

International news compilation covering politics, economy, culture, and nature.

Phobos: Mars' Fate Moon

Phobos, a Martian moon, will eventually disintegrate into a ring of debris due to tidal forces.

Phobos: Mars' Fate Moon

Phobos, a Martian moon, will eventually disintegrate into a ring of debris due to tidal forces.

Primary

# Understand SKILLS: Modular Rules + Lightweight Scripts

Juejin Frontend Hottest•Published on January 22

Insight•AI Agent Programming•Score: 8/10

SKILLSAI AgentModular RulesLLMPrompt Engineering

Source

◆

Is React Source Code Worth Reading in 2026? ❓❓❓

Juejin Frontend Hottest•Published on January 21

Insight•Frontend Framework•Score: 7/10

Reactsource code readingfrontend frameworkFiber architectureinterview

Source

◆

Former Megvii CEO Yin Qi Takes Over as Chairman of Jiayue Xingchen

InfoQ - AI & LLM•Published on January 26

News•AI Industry Dynamics•Score: 7/10

Yin QiJiayue XingchenMegviiAI CompanyFoundational Large ModelEmbodied IntelligenceAI + Terminal

Source

Essential

How Fuzhuang Reduced Ad Outbound System Timeout Rate to 0.01% Under Billion-Level Requests

InfoQ - AI & LLM•Published on January 26

Insight•Performance Optimization•Score: 9/10

RTAHigh ConcurrencyPerformance OptimizationUnit DeploymentJDK21AI Coding

🔬

Tech Insights

1. Application architecture decoupling, RTA independent splitting, JVM upgrade to JDK21 Virtual Threads and SpringBoot 3.x, reducing application restart time by over 80% and improving deployment efficiency. 2. Through traffic collection and replay systems, testing cycles were shortened from 3 days to 1 day, effectively addressing the challenges of testing in closed and heterogeneous media channel environments. 3. Unit deployment fully resolved cross-regional network latency, reducing the direct connection timeout rate of Xiaohongshu to 0.01%; Tengine long connection optimization at the gateway layer reduced TIME-WAIT connection count by 99% and CPU usage by 10%. 4. The log system lowered CPU usage by 9 points and reduced log file size by 60% through protocol optimization, batch aggregation, asynchronous disk flushing, and layered sampling. 5. AI Coding practices were introduced, with Pipeline mode and adapter layer design, reducing the new media channel integration cycle from 5 days to 2 days.

Source

◆

Meituan's EvoCUA Refreshes Open-Source SOTA, Achieving a Self-Improving Computer-Using Agent

Meituan Tech•Published on January 26

Insight•Agents and Intelligent Bodies•Score: 9/10

EvoCUAComputer Use AgentSOTAExperience-Driven Evolution LearningOSWorldReinforcement Learning

🔬

Tech Insights

1. EvoCUA builds a verifiable data synthesis engine through the 'generate and verify' paradigm, solving the low quality of traditional imitation learning data synthesis and the disconnection between semantic and execution, expanding training data to tens of thousands of levels. 2. A 100,000-level sandbox concurrency infrastructure is established, using a hybrid virtualization architecture of Docker containers nested within QEMU-KVM, achieving minute-level launch of tens of thousands of sandbox instances and ensuring environment isolation with millisecond-level response. 3. A progressive evolution paradigm is introduced, training in three phases: cold start, rejection sampling fine-tuning (RFT), and reinforcement learning (RL), particularly using efficient DPO algorithms to drill the optimization granularity down to 'key decision points', significantly enhancing model robustness. 4. EvoCUA-32B achieved a 56.7% success rate in the OSWorld open-source benchmark, surpassing OpenCUA-72B and the closed-source UI-TARS-2, and still maintaining significant advantages in small-parameter models (EvoCUA-8B outperforms OpenCUA-72B).

⚠️

Notable

1. Meituan's claim of '100,000-level sandbox concurrency' sounds impressive, but the operational costs are inevitably extremely high, making it nearly impossible for non-large companies to replicate its full infrastructure set. 2. The 'test Agent' and 'validator' introduced in the 'generate and verify' process have not fully discussed their hallucination and misjudgment risks, which could introduce new data biases. 3. The article frequently mentions 'approaching the closed-source model Claude-4.5-Sonnet', but the actual success rate still lags, and closed-source models typically iterate faster, making SOTA sustainability questionable. Additionally, the capability gap between open-source models and top-tier closed-source models remains significant in handling complex, low-resource language tasks.

Source

◆

Former OpenAI Senior Member Jerry Tworek Leaves, Criticizes Industry Entertaining Trends and Homogenization

InfoQ - AI & LLM•Published on January 26

Insight•AI Industry Insights•Score: 9/10

OpenAIJerry TworekAI IndustryAGIReasoning ModelGoogle Catch-upAnthropicResearch Direction

🔬

Tech Insights

1. Jerry Tworek argues that OpenAI's focus on user growth and GPU costs has led to reduced risk appetite, making it difficult to conduct breakthrough fundamental research, and organizational rigidity also limits cross-team collaboration. 2. He criticizes the AI industry for severe homogenization competition, as the five major players are all using similar formulas to make minor differentiated products, hindering true innovation and diversity exploration. 3. Emphasizes the combination of 'reasoning models' with large-scale reinforcement learning as the most important capability leap after GPT-4, enabling the model to learn things it couldn't from pre-training, and is optimistic about the world model direction. 4. Points out two underestimated research areas: architectural innovation (beyond Transformer) and continual learning (continual learning), believing the latter is one of the key elements for achieving AGI. 5. Highly praises Anthropic's focus and execution, especially its achievements in code models and coding Agents, believing its products are substantially enhancing enterprise productivity.

Source

◆

AI Agent Is a Long-Running 'Risk System'; Only Preventing Prompt Injection Is No Longer Sufficient

InfoQ - AI & LLM•Published on January 26

Insight•AI Security•Score: 8/10

AI Agent SecurityInstruction DetectionHistorical PoisoningHoneypot ActionsLLM SecurityContext Management

🔬

Tech Insights

1. AI Agent's security risks primarily stem from external API or database return results, not just user input, making traditional Prompt Injection defenses insufficient. 2. 'Instruction Detection' (Instruction Detection) is proposed, using LLM-based referee models to identify text intent, behavior patterns, and instruction structure features for review before data reaches the main model. 3. 'History-Aware Validation' (History-Aware Validation) is introduced to prevent 'historical poisoning'—malicious instruction fragments accumulating over multiple interactions to form a complete attack. This is achieved by submitting all historical API responses and the latest data to the instruction detector together. 4. 'Honeypot Actions' (Honeypot Actions) are designed as security traps to capture abnormal Agent behaviors and promptly detect attempts at meta-level probing, data extraction, or system prompt leaks.

Source

General

E222｜The Decline of Tight Pants, Who Defines the Fashion Trend?

SV101 Podcast•Published on January 26

News•Consumer Trend Research•Score: 5/10

Fashion TrendsConsumer PsychologyE-commerce PlatformsTrend ForecastingProduct Homogenization

Source

◆

Data Engineering Weekly #254

Data Eng Weekly•Published on January 26

News•Data Engineering•Score: 5/10

Data EngineeringLLMAI AgentData MeshSemantic LayerKafka DLQReal-time Budget

Source

◆

Zi Yi's 2025 Annual Review

Juejin Frontend Hottest•Published on January 25

Insight•Personal Growth / Frontend Development•Score: 5/10

Annual ReviewAI ProgrammingAgent DevelopmentOpenManusLangchainReActFrontend FrameworkInvestment Management

🔬

Tech Insights

1. Transitioning from Vibe Coding to intelligent IDE-assisted programming, and looking forward to SDD (Software Defined Development) development paradigm, emphasizing the construction of complex domain knowledge systems to achieve precise AI code generation. 2. Deep dive into the OpenManus open-source project, understanding the Agent design logic based on Function Calling and ReAct architecture, including Multi-Agent mode and task planning. 3. Comprehensive study and practice of the Langchain framework, designing an efficiency-enhancing Agent for frontend development, and exploring RAG retrieval and memory compression in practical applications. 4. Through a series of self-posed questions and answers, the article conducted in-depth thinking and summarization on core technical concepts such as ReAct and Fiber trees.

Source

◆

Differences and Use Cases of deep, v-deep, and >>> in Vue

Juejin Frontend Hottest•Published on January 22

Insight•Frontend Development•Score: 5/10

Vuescoped stylesstyle penetrationCSS preprocessors:deep()::v-deep>>>

🔬

Tech Insights

1. Scoped styles achieve isolation by adding unique attributes to component elements and CSS selectors, preventing global pollution. 2. >>> is the early Vue2 syntax for style penetration, which is not compatible with CSS preprocessors and has been deprecated in Vue3. 3. ::v-deep is a transition compatibility solution for Vue2 to Vue3, supporting preprocessors but has been replaced by :deep() in Vue3. 4. :deep() is the standard recommended syntax in Vue3, with clear syntax and compliance with CSS standards, supporting all preprocessors and achieving penetration through compile-time transformation. 5. When modifying the styles of third-party UI components, it is essential to use :deep() and pair it with parent selectors to avoid global pollution and precisely control the scope of styles.

Source

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Global Perspective on January 25, 2026

Global Vision•Published on January 25

News•International News Digest•Score: 1/10

International RelationsGeopolitical ConflictsEconomic IndicatorsCultural EventsNatural Disasters

📝

Summary

1. Retrospective Exhibition of Le Corbusier in Switzerland 2. First trilateral meeting between the US, Russia, and Ukraine, next round scheduled for February 1st 3. Danish Prime Minister visits Greenland 4. China-Europe freight train holiday special, 6,037 trains operated from Xi'an in 2025 5. Japan faces its strongest cold snap of winter 6. Nobel Museum receives a donation of *The Old Man and the Sea* 7. Jiangsu Zoo celebrates the Laba Festival 8. Japanese House of Representatives dissolved, new election on February 8th 9. Putin meets US Presidential Envoy 10. 3rd Beijing Commercial Spaceflight Exhibition 11. Vienna Philharmonic Orchestra Ball 12. 2026 Cairo International Book Fair 13. India's Shiva Temple Festival, India's GDP exceeds Japan's in 2025 14. Leo constellation gravitational lens galaxy cluster 15. Trump launches a Peace Committee

Source

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Phobos: Mars' Fate Moon

NASA APOD•Published on January 25

News•Space Science•Score: 1/10

PhobosMars MoonGravitational TidesPlanetary ScienceDebris Ring