(Illustration: Hydrographic survey storage area. Each tube contains a registered hydrographicsurvey. Image source: Photo by NOAA on Unsplash.)

✳️ tl;dr

• The US government released America's AI Action Plan in July 2025, aiming to reshape America’s global AI dominance
• Three strategic pillars: Accelerate AI Innovation, Build AI Infrastructure, Lead International AI Diplomacy & Security
• Revoked previous administration’s AI Executive Order 14110, removing “red tape and overregulation”

• Emphasizes protecting free speech and American values, ensuring AI systems objectively pursue truth
• Encourages open-source and open-weight AI models development to promote innovation and commercial adoption
• Establishes streamlined permitting for data centers, semiconductor manufacturing, and energy infrastructure, realizing the “Build, Baby, Build” vision

• Revitalizes US semiconductor manufacturing through CHIPS Program Office
• Builds military-grade high-security data centers to resist nation-state attack threats
• Exports complete AI technology stack to partners

• Establishes regulatory sandboxes and AI excellence centers, enabling research institutions, startups, and enterprises to rapidly deploy and test AI tools
• Creates AI Workforce Research Center to continuously assess AI’s impact on labor markets and provide policy recommendations
• Invests in automated cloud laboratories covering engineering, materials science, chemistry, biology, and other scientific fields

• Includes full text: America's AI Action Plan (PDF to Markdown) ¹

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(Caption: Installing Kiro. Image source: Ernest’s MBP.)

✳️ tl;dr

• Feel like AI | Vibe coding is like opening a blind box?
• Kiro ¹ uses Specs to help you read the manual before unboxing
• One prompt → automatically expands into user stories, complete with EARS requirement standards

• Ernest attempts to deconstruct Kiro’s four-layer architecture (Intent Layer, Knowledge Layer, Execution Layer, Oversight Layer) ²
• Kiro AI = Kiro Agentic IDE

• Tasks list directly connects to unit/integration tests, reducing the awkwardness of forgetting to write tests
• Hooks let everyone unleash their imagination with event-driven automation - build your own automation
• Steering project guidance principles ensure consistency, making Kiro follow organizational culture and connect knowledge management
• Supports RWD and A11y - frontend is well taken care of too

• Free during preview period, supports Mac/Win/Linux (grab it while you can!)
• Kiro is based on Code OSS, compatible with VS Code
• VS Code users should be able to migrate seamlessly, though some extensions aren’t available in Kiro yet
• Kiro + WSL2 solution ²

• Extended use cases: Kiro + dev container for isolation
• Extended use cases: Kiro + Remote SSH + EC2 (CloudShell?) within VPC

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(Illustration: Brazil’s largest port, Port of Santos, provides container loading and unloading services. Image source: Photo by sergio souza on Unsplash。)

✳️ tl;dr

• Cloudflare Containers ¹ enters public beta, immediately available for paid users with full Workers integration.
• Region: Earth global deployment, containers start in seconds, developers don’t need to select regions.
• Through Worker→Container binding, dynamically generates isolated instances by ID, suitable for multi-tenant platforms.
• Three instance types: dev/basic/standard covering 256 MiB, 1 GiB, 4 GiB memory requirements.
• 10ms billing granularity with separate CPU, memory, and disk metering, plus free tier included.
• Built-in Metrics/Logs retained for 7 days, supports external LogSink, reducing observability integration costs.
• Upcoming: autoscale = true enables global auto-scaling and latency-aware routing.

• Cloudflare Containers runs on AWS-developed open-source Firecracker microVM ² with KVM isolation, reducing multi-tenant side-channel risks while maintaining startup speed and resource efficiency.
• Firecracker microVM: < 125ms cold start, < 5 MiB memory, balancing security and density.
• Ernest Chiang demonstrated ³ running 4,000 microVMs in 90 seconds on i3.metal at COSCUP 2020 Firecracker workshop.

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(Illustration: Ernest at Taiwan Product Conference 2025. Image source: Bob Chao.)

Witnessing Taiwan’s journey from nascent tech communities blossoming into full-fledged technical conferences, we’ve observed an organic proliferation of product-centric opportunities emerging alongside industrial metamorphosis and the ever-increasing complexity of cross-disciplinary integration. This ecosystem now encompasses the multifaceted spectrum of product operation, product marketing, product design, product management, and product development—a verdant and thriving landscape.

Yet beneath this seemingly lush canopy, one wonders: are we nurturing an organic greenhouse, or merely cultivating a wild tangle of weeds? As we navigate through this labyrinth of uncertainty, none among us possess the definitive answer. But perhaps not knowing is precisely what makes everything possible—it means we can still venture forth to explore, retreat home to experiment, and dare to iterate through our discoveries. On this sweltering weekend, we—a collective of souls orbiting the product ecosystem—gathered at the inaugural Taiwan Product Conference 2025, attempting to forge something meaningful together.

Conference reflections shall be compiled separately.

This piece unfolds in two movements: first, the release of presentation slides, followed by supplementary Q&A elucidations. I warmly invite you to utilize the feedback form found on the final slide to share perspectives from any angle, pose questions, or engage in dialogue. Looking forward to our next shared endeavor.

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(Illustration: Walk nearby Le Bouchon Ogasawara in Shibuya, Tokyo. Image source: Ernest)

✳️ tl;dr

With the launch of AWS Taipei Region (ap-east-2), it’s time to update that overgrown web latency testing tool.

• HTTP overhead is quite heavy, but when you don’t have CLI tools available or when dealing with remote clients, it can provide a simple evaluation.

• Arranged roughly according to city distances.
• Based on AWS Region naming rules, supplemented by my modest geographical knowledge.
• Following the principle of not over-categorizing to avoid too fine granularity. If your principles differ, feel welcome to fork from upstream and modify it to your liking.

• Ernest Toolkit: Latency Ping

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(Illustration: AWS Summit Hong Kong 2025 Dev Lounge. Image source: Dorothy.)

✳️ Background

I’m honored to have been selected after submitting my talk proposal—thank you to everyone who has quietly encouraged me along the way :) It’s also a privilege to be part of the 10th anniversary of AWS Summit Hong Kong. Thinking back to 2014, when Lenie, Locarno, and I invited Jeff Barr to Taiwan to deliver a keynote at COSCUP, to supporting the AWS Hero program, and now standing here in Hong Kong sharing with developers and technical managers at the AWS Summit Dev Lounge—it truly feels like a fortunate convergence of serendipity and iterative progress. My heart is full of gratitude.

This talk draws from over a year of experience working with traditional industries, streamlining processes, and modeling object states. It also reflects how our own product and technology integration (PTI) teams have adapted our workflows to collaborate with AI tools (with a fair share of pitfalls along the way). By combining Amazon Q CLI with an AI-augmented perspective on existing processes, we explore the mindset of inviting AI to be a new team member to join us. Like onboarding any new colleague, there will be a period of adjustment—but unless we invite this new teammate (or team?!) of AI to join us, that adaptation can never begin.

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(Illustration: Unbox Apple MacBook Pro M4 Pro and reMarkable Paper Pro. Taken at AWS re:Invent 2024, Las Vegas. Image source: Ernest)

Today I spent some time setting up a development environment for the nRF52 DK (PCA10040) board on my macOS Sequoia 15.1.1 machine running on an Apple Macbook Pro M4 Pro (Apple Silicon). This blog post documents the process and can serve as a reference for anyone working with Nordic Semiconductor’s nRF52 DK (development kit).

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tl;dr

• Evolution of AWS services from simple to complex systems
• Introduction of Amazon Aurora D SQL demonstrating strong consistency in globally distributed systems
• Time Synchronization as a new fundamental building block for distributed systems
• Six principles for managing complexity: evolvability, decomposition, organizational alignment, cell-based architecture, predictable design, automation
• Demonstration of complexity management through microservices and cell-based architecture

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tl;dr

• SageMaker evolution: New unified experience combining analytics, ML, and GenAI capabilities
• Bedrock enhancements: New model partnerships (Luma AI, Poolside), prompt optimization features, and advanced RAG capabilities
• Amazon Q improvements: ML model development assistance, business scenario analysis, and developer productivity tools
• Infrastructure optimization: Hyperpod task governance, flexible training plans, and compute resource management
• Security and responsible AI: Enhanced multimodal toxicity detection and automated reasoning checks

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tl;dr

• Announced major compute innovations: Graviton4, Trainium2/3, and P6 instances with NVIDIA Blackwell, delivering significant performance improvements for both general and AI workloads
• Revolutionized storage with S3 Table Buckets for Iceberg tables (3x better query performance) and S3 Metadata for instant data discovery and analytics
• Launched Aurora D SQL and enhanced DynamoDB Global Tables, enabling truly distributed databases with strong consistency and 4x faster performance than competitors
• Introduced Amazon Nova AI model family and enhanced Bedrock with automated reasoning checks and multi-agent collaboration, making GenAI practical for production
• Reimagined SageMaker as a unified platform for data, analytics, and AI with Zero-ETL capabilities, representing a fundamental shift in how enterprises handle data and AI workloads

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