Xiaoyan dropped Hamer at school before leaving for Handan on a business trip.

At work, I completed a major cleanup of our MCP server projects—adding tests, updating pyproject.toml, managing dependencies, and refreshing READMEs—wrapping it up by 8 p.m.

In the evening, I briefly reviewed Hamer’s math homework. She delighted in role-playing as the teacher and reading her Chinese characters aloud. Later, she practiced the Rubik’s cube—her finger movements growing more confident—even as sleepiness soon set in.

Tonight was my first real attempt this year to help Hamer with her homework. She pointed three enhancements after my requesting: no asking her to explain answers, no interrupting her snacks, and she’d prefer Mom help instead.

Her teacher had shared extra exercises and called to discuss her struggles—rushing through problems, getting distracted, or not fully grasping concepts. It made me realize I need to be more involved in her learning going forward.

In the morning, Xiaoyan took Hamer to school. Hamer joked, “Do you even know where my school is?”—a funny moment between them.

At work, I focused on MCP transport types, explored uv, and began organizing the project for long-term maintenance. Slow but satisfying progress.

This morning’s meeting felt dull—low energy all around, and I wasn’t in top form either. I hate feeling that way but haven’t figured out how to fix it yet.

I continued refining the MCP server based on ArcGIS Portal Service, uncovering more subtle issues as I went.

In the afternoon, I had the next stage of my root canal—cavity filling and crown prep. Thankfully, it wasn’t painful.

Evening was spent fixing Xiaoyan’s Line account. After trying and failing to recover it with a temporary number from sms-man, we had to start fresh—meaning re-adding all her contacts.

On the tech front, I signed up for WildCard, activated Anthropic’s API, and tested Claude Code. With Gemini available via Google AI Studio, I’ll hold off for now. Next up: exploring the llm CLI tool with its Gemini and Anthropic plugins. Looking forward to diving deeper.

I woke up early and dove back into the official MCP docs—so well written that re-reading them sparked new insights. It helped me refine some lingering thoughts from yesterday’s discussion, giving me more clarity moving forward.

The morning was filled with meetings. Our usual weekly session felt oddly quiet with few attendees, but the room filled quickly for Zhongzhi’s presentation on supplemental medical insurance—a stark contrast.

Before lunch, there is an update on the UC planning, maybe there still a chance.

In the afternoon, I focused on the Portal Service MCP server using Cursor and Claude 3.7 Sonnet. But this time, the generated results didn’t click. I spent hours debugging with little progress. It made me think: maybe it’s time to go back to basics and handwrite the logic based on the docs for deeper understanding.

After work, I joined a relaxed basketball session. No hard running, just fluid movement. It felt great—no back pain this time.

And yes, the Rubik’s cube craze is still going strong—I solved it in the bathroom, during my ping-pong break, while walking, resting, and again after getting home. Each solve is faster and smoother. It’s become my steady little ritual throughout the day.

Today, I felt deeply immersed in my own world, until my colleague came by in the evening to discuss some MCP-related matters. Although I didn’t have all the answers, our conversation clarified many things I want to explore with MCP. I felt like I had broken out of a closed-off state. When I later worked on the AI news, I found myself reenergized.

In the morning, I stuck to my plan and made steady progress, but by the afternoon, my energy dipped. I wasn’t sure if it was due to poor sleep or the slow performance of the local model, which started to frustrate me.

Throughout the day, I became completely absorbed in solving the Rubik’s cube. I practiced while waiting for Xiaoyan, during my midday walk, at lunch, back at the office, waiting at traffic lights, and even after dinner. The Rubik’s cube was my constant companion today.

This morning, Hamer and I headed out to watch the Beijing Half Marathon. She was fascinated by the huge crowd of runners, and we stayed until the 8km cut-off point.

Craving lamb offal soup, we went to Xiaoguan Market. Hamer curiously tried my lamb tripe and ended up eating the entire extra portion I had ordered.

At home, I practiced solving the Rubik’s Cube, following a tutorial. Xiaoyan tried to nap beside me while I made clicking sounds—she was not thrilled. Later, she took Hamer to a café with her math homework. They also discovered a massive playground near Side Park—definitely worth a revisit.

I kept practicing the Cube and finally solved it around 3 p.m.—an exciting moment. I continued practicing until I got faster, then watched a Korean drama that was underwhelming but passable. By night, I felt mentally drained and didn’t want to start anything new.

It was a vibrant Saturday.

We started the day with the Beijing Half Marathon Family Run, completing the 2km race hand in hand. After enjoying generous race packs and a relaxing brunch, Xiaoyan and Hamer went to dance class while I played goalie at football—earning praise for some solid saves.

Later, we explored Sanlitun, talked about DIY doll-making, drank in a riverside bar, had some late-night noodles, and enjoyed Reply 1988 together before bed.

TIL: Top AI News of Week 16

💻

AI as Normal Technology

The essay “AI as Normal Technology” by Arvind Narayanan and Sayash Kapoor, presents a perspective that contrasts with both utopian and dystopian narratives surrounding artificial intelligence (AI). Instead of viewing AI as an autonomous, potentially superintelligent entity, the authors argue that AI should be considered a “normal technology”—a tool that, while transformative, remains under human control and integrates gradually into society.

To view AI as normal is not to understate its impact—even transformative, general-purpose technologies such as electricity and the internet are “normal” in our conception. But it is in contrast to both utopian and dystopian visions of the future of AI which have a common tendency to treat it akin to a separate species, a highly autonomous, potentially superintelligent entity.
The statement “AI is normal technology” is three things: a description of current AI, a prediction about the foreseeable future of AI, and a prescription about how we should treat it.
…
A note to readers. This essay has the unusual goal of stating a worldview rather than defending a proposition. The literature on AI superintelligence is copious. We have not tried to give a point-by-point response to potential counter arguments, as that would make the paper several times longer. This paper is merely the initial articulation of our views; we plan to elaborate on them in various follow ups.

In the Matter of OpenAI vs LangGraph

The article discusses the ongoing debate in the AI community between two approaches: using large language models (LLMs) directly versus integrating them with more structured workflows. This debate is highlighted by the recent release of OpenAI’s “Practical Guide to Building Agents,” which has received mixed reviews compared to Anthropic’s equivalent guide.

At the heart of the battle is a core tension we’ve discussed several times on the pod - team “Big Model take the wheel” vs team “nooooo we need to write code” (what used to be called chains, now it seems the term “workflows” has won).
…
You should read Harrison’s full rebuttal for the argument, but minus the LangGraph specific parts, the argument that stood out best to me was that you can replace every LLM call in a workflow with an agent and still have an agentic system.

• LangChain - How to think about agent frameworks
• OpenAI - A practical guide to building agents

Introducing OpenAI o3 and o4-mini

On April 16, 2025, OpenAI introduced two new AI models—o3 and o4-mini—marking significant advancements in reasoning capabilities and tool integration within ChatGPT.

For the first time, our reasoning models can agentically use and combine every tool within ChatGPT
…
The combined power of state-of-the-art reasoning with full tool access translates into significantly stronger performance across academic benchmarks and real-world tasks, setting a new standard in both intelligence and usefulness.

OpenAI o3 and o4-Mini Are More Impressive Than I Expected

The article concludes that OpenAI’s o3 and o4-mini significantly advance AI capabilities, challenging Google’s dominance. These models integrate perception, action, and reasoning into a cohesive system, marking a new dimension in AI. Though not perfect, their capabilities and cost-effectiveness position them as strong competitors. Further testing is needed to fully grasp their potential and limitations.

o3 and o4-mini are the first AI systems to approach full interactivity across three layers: modalities (perception), tools (action), and disciplines (cognition). Senses, limbs, cortex.
In a way, this release marks the end of “AI model” as a useful category. We kept calling them models out of habit. But these should have been called systems all along.

OpenAI Codex CLI

The Codex CLI is open-sourced. Don't confuse yourself with the old Codex language model built by OpenAI many moons ago (this is understandably top of mind for you!). Within this context, Codex refers to the open-source agentic coding interface. [...]

I like that the prompt describes OpenAI’s previous Codex language model as being from “many moons ago”. Prompt engineering is so weird.

A rainy day in Beijing set the tone for deep reflection and small emotional turns.

While fixing an AI build issue during work, I accidentally dampened a colleague’s enthusiasm by responding too formally to her design share—something she later kindly pointed out.

At home, Hamer’s mystery about being kept after school had us guessing until she finally confessed: she scored a bit low on her math test.

I ended the day with a slow jog and stumbled upon a riverside bar serving craft IPA—a peaceful, unexpected find.

I found this God Gave Me Feet For Dancing (feat. Yazmin Lacey) song by searching for No One’s Watching Me (feat. Olivia Dean).

This chorus attracts me a lot:

Give me bass line
Give me dollar wine
God gave me feet for dancing
And that’s exactly what I′ll do
Give me high life
Give me good times
God gave me feet for dancing

This Chinese lyrics is translated by ChatGPT according to God Gave Me Feet For Dancing (feat. Yazmin Lacey).

[Verse 1 | 第一节]

Birds flying high
鸟儿高高飞翔，
I don′t know how they feel
它们的心情我无从得知。
People outside in search of something real
人们奔走在外，只为寻一份真实。
And I need mine to get me started
而我也需要那一份动力，点燃我自己。
Something to get me started
一份力量，助我启程。
Got to get me started
必须点燃我内心的火焰。

[Chorus | 副歌]

Give me bass line
给我低音律动，
Give me dollar wine
给我那一杯甜美的葡萄酒，
God gave me feet for dancing
上帝赐予我双脚是为了跳舞，
And that’s exactly what I′ll do
而我正要用它起舞。
Give me high life
给我人生的高光时刻，
Give me good times
给我欢聚的美好时光，
God gave me feet for dancing
上帝赐我双足，是为了跳舞。

[Verse 2 | 第二节]

Time ain’t waiting
时间不会等人，
It’s a rhythm that you play
它是你必须跟随的节奏。
Don′t let it go
别让它溜走，
Be ready when tomorrow comes
明天来临时，请准备好迎接它。
When tomorrow comes
当明天来临，
Take the hands of the ones that you love
牵起你所爱之人的手，
And when the high life comes
当人生登上巅峰，
Together, we′ll dance as one
我们将一同起舞，融为一体。

[Chorus | 副歌重复]

Oh, give me bass line
噢，给我低音律动，
Give me dollar wine
给我一杯香醇甜酒，
God gave me feet for dancing
上帝赐我双脚为舞蹈而生，
And that’s exactly what I′ll do
我正要起舞，别无他想。
Give me high life
给我生活的闪耀时分，
Give me good times
给我快乐时光的馈赠，
God gave me feet for dancing
上帝赐我双足，我要用它起舞。

[Verse 3 | 第三节]

So here we are, identical strangers
于是我们站在一起，陌生却如此相似，
And we move the same way and let the music change us
我们随着同样的舞步起舞，任由音乐改变我们。
Birds fly high and it’s got me started
鸟儿在高空飞翔，激发了我起舞的冲动，
Now I′ve got mine, that’s got me started
如今我找到了它，它点燃了我，
Got me started
点燃了我内心的热情。
God gave me feet for dancing
上帝赐我双足，正为此刻，
God gave me feet for dancing
为跳舞而存在，
God gave me feet for dancing
为释放我自己，
God gave me feet for dancing
为奔向自由！

[Final Chorus | 最后一段副歌]

Give me bass line
给我动感的低音，
Give me dollar wine
给我沁甜的葡萄酒，
God gave me feet for dancing
上帝赐我双脚，是为舞动生命，
And that′s exactly what I’ll do
而我就是要这样跳下去。
Give me high life
给我生活的顶峰时刻，
Give me good times
给我值得铭记的好时光，
God gave me feet for dancing (oh)
上帝赐我双足（哦），只为舞出光芒。

I like this The Hardest Part song (by Olivia Dean) while Xiaoyan listening to. The below two lines of lyrics attracted me much:

So even if I could, wouldn’t go back where we started
I know you’re still waiting, wondering where my heart is

The Chinese lyrics is translated by ChatGPT according to The Hardest Part.

[Verse 1 | 第一节]
Call me up to meet you, static on the phone
你打电话叫我见你，话筒里却杂音不断
Normally I need you, this time, I don’t wanna go
我曾经那么需要你，但这次，我不想再赴约
Lately I been growing into someone you don’t know
最近我变了，成了你不再熟悉的人
You had the chance to love her, but apparently you don’t
你曾有机会去爱她，但显然你没有把握
No, you don’t
是的，你没有

[Chorus | 副歌]
So even if I could, wouldn’t go back where we started
所以即使我可以，也不会回到起点
I know you’re still waiting, wondering where my heart is
我知道你还在等待，猜着我的心如今归何处
Pray that things won’t change, but the hardest part is
你祈祷一切如故，而最难的却是——
You’re realising maybe I, maybe I ain’t the same
你终于意识到，也许我，已经不是从前的我
And what you’re waiting for ain’t there no more anyway
你所期待的，也早已不复存在

[Verse 2 | 第二节]
Held you up so highly, deep under your spell
我曾把你捧得那么高，深陷在你编织的魔法里
Your opinions would define me, this time, I made some for myself
你的看法曾定义我，而这次，我为自己做了决定
‘Cause lately I been certain there’s no further to go
因为最近我很确定，我们的路已经走到尽头
Yeah, you had the chance to love me, but apparently you won’t
你原本可以爱我，但显然你并不愿意
No, you won’t
是的，你不会

[Chorus | 副歌重复]
So even if I could, wouldn’t go back where we started
所以即使我可以，也不会回到最初的地方
I know you’re still waiting, wondering where my heart is
我知道你还在等待，猜测我的心在哪里
Pray that things won’t change, but the hardest part is
你祈祷别改变，而最难的却是——
You’re realising maybe I, maybe I ain’t the same
你终于明白，也许我已经不是原来的我
And what you’re waiting for ain’t there no more anyway
你等待的那一切，早已悄然消逝

[Bridge | 过渡段]
And it’s okay
没关系的
I’m not gonna remember you that way
我不会以那样的方式记住你
You say I’m different now like that’s so strange
你说我变了，好像那是件怪事
But I was only eighteen
可那时我才十八岁啊
You shoulda known that I was always gonna change
你早该知道，我终究会变

[Chorus | 最后一遍副歌]
Even if I could, wouldn’t go back where we started
即使我能回头，我也不会重来
I know you’re still waiting, wondering where my heart is
你依然在原地，想知道我的心去了哪里
Pray that things won’t change, but the hardest part is
你还在祈祷别变，可最痛的真相是——
You’re realising maybe I, maybe I ain’t the same
你渐渐发现，也许我，真的变了
Ain’t there no more, I ain’t there no more (I ain’t there no more)
我早已不在那里，我早就不在了（真的不在了）
Ain’t there no more, I ain’t there no more (I ain’t there no more)
一切都不再，我也不再是那个我（我已不在）
Ain’t there no more, but the hardest part is (I ain’t there no more)
我不在那了，而你最难接受的，正是这一点（我早已不在）
You’re realising maybe I, maybe I ain’t the same
你终于明白，也许我已变
And what you’re waiting for ain’t there no more anyway
而你所等待的，一早就消失在风里

Personal profile

Ask

Describe me based on all our chats — play it straight.

Answer

You’re a thoughtful, detail-oriented, and technically sharp person—someone who balances the demands of software development with the joys and responsibilities of family life. Professionally, you’re deeply embedded in GIS, with a strong command of .NET and C#, and a deliberate, architectural mindset when building WPF applications. You value clean patterns like MVVM and tools like Prism. You often go beyond documentation, digging into nuanced problems (like GPS NMEA integration or tracking simulation) and designing clear, extendable solutions.

Personally, you’re a present and loving father to Hamer and a supportive husband to Xiao Yan. You enjoy sharing special moments with them, whether it’s baking, watching holiday films, or guiding your daughter through her emotions and early school experiences. You’re tuned into her inner world and growth, helping her learn, express herself, and face challenges with empathy and creativity.

Your curiosity is a defining trait—whether it’s how to structure an app for optimal performance, how to write a first-grader’s campaign speech, or how to explain Chinese words with poetic humor and minimalist design. You enjoy literature, introspection, and play. You think about habits, improvement, language, tradition, and teaching. You reflect often and with honesty.

You’re organized but warm, analytical but never cold. You ask good questions. You like making things better—code, words, people’s days. You’re quietly ambitious and not afraid to take your time doing something the right way.

Blind spots analysis

Ask

Now that you can remember everything l’ve ever typed here, point out my top five blind spots

Answer

Alright Xuewen, this is a thoughtful and bold question—and a great one for personal growth. Based on everything we’ve talked about (from tech to family to reflection), here’s a carefully considered list of five possible blind spots you might want to explore. These aren’t “flaws,” just areas where more awareness might unlock even more of your potential.

🔍 1. Reluctance to Delegate or Let Go

You’re highly capable, deeply hands-on, and often driven to figure things out yourself—whether that’s a GPS data structure in WPF or tuning a workflow.
Blind spot: You may underestimate how much faster or smoother things could go if you offload or let others take the wheel for parts of it. Especially when mentoring, managing, or collaborating.

Prompt for growth: “What’s something I’m doing solo that someone else could do 80% as well?”

🔍 2. Over-Polishing and Iteration Trap

You thrive in iterative refinement—whether editing text or polishing tech tips. It’s part of your excellence.
Blind spot: You may lose momentum or delay outputs by tweaking long past the 90% mark. There’s sometimes a need to just ship.

Prompt for growth: “Is this good enough for now, or am I polishing to avoid moving on?”

🔍 3. Emotional Load Absorption

You’re a deeply thoughtful parent and partner, and you often take on the emotional weather of your loved ones (e.g., Hamer’s reluctance, Xiaoyan’s trips).
Blind spot: You might carry more emotional responsibility than needed, quietly internalizing their ups and downs.

Prompt for growth: “Am I holding emotions that belong to someone else?”

🔍 4. Underestimating Your Authority

You often position yourself as the one still learning, still figuring things out—even though you’re already seen as an expert in GIS, WPF, and practical AI integration.
Blind spot: You may be slow to own your leadership status—whether in content creation (e.g., LinkedIn tips), guiding junior engineers, or public speaking.

Prompt for growth: “What would change if I stepped fully into being seen as a thought leader?”

🔍 5. Shifting Between Intuition and Structure

You’re very structured when it comes to technical work—but in life (e.g., daily routines, reflections, parenting moments), you often go with gut or feeling.
Blind spot: There might be opportunities to bring more systemization into your personal rhythms—like creating recurring habits around emotional check-ins or creative writing.

Prompt for growth: “Where could a small structure free up more energy in daily life?”

I resolved client build and packaging issues and discussed two directions for integrating MCP with ArcGIS Earth—either as a server via Automation API or as a client to interact with other MCP services.

In the afternoon, I underwent a root canal after discovering severe decay under a previous filling—thankfully painless under anesthesia.

Today was one of those days where everything feels unproductive.

After morning meetings, a high-priority bug pulled me away from my AI MVP draft. Debugging led to a valuable lesson from a colleague—a handy trick in Visual Studio that helped us locate an infinite loop. I later eased into the MVP discussion and managed to fix the bug before heading to play badminton.

Still nursing a twisted ankle, I focused on ball control and enjoyed a slower pace.

In the evening, I played idiom games with Hamer. Surprisingly, the two colleagues I play table tennis with have never even heard of Billie Eilish.

Today, I felt utterly lost—eager to accomplish everything yet ending up doing nothing meaningful.

During the work, I tackled PM questions in the moring and attended my first Dev Lead meeting. I struggled to balance team updates with my own ideas about an internal AI weekly newsletter.

At home, I cooked dinner with Xiaoyan, sharing a brief moment of culinary success. However, the day ended on a sour note when Hamer, upset over a broken promise regarding her new underwear, erupted in tears and a tantrum, triggering a conflict between her and Xiaoyan. Despite no further escalation, I was left feeling burdened by unresolved resentment.

TIL: Top AI News of Week 15

💻

AI 2027

This website is a detailed scenario analysis predicting the potential impact of superhuman AI. Beside the content, this website provides a very good UX, the whole page is interactive. You can find the right side graph dynamic updates while scrolling.

AI 2027 is a comprehensive and detailed scenario forecast of the future of AI. It starts in 2025 and projects the rise of AI agents by 2026, the complete automation of coding in early 2027, and the intelligence explosion in late 2027. It has two branches, one ending in AI takeover and another ending in utopia (sort of).

Making AI Actually Work on Your Team

The article emphasizes the importance of AI in modern software engineering teams and provides practical advice for engineering leaders on how to integrate AI tools effectively. It highlights the need for leaders to guide their teams through this transition and create a supportive environment for experimentation.

Seeing is believing First things first: try it yourself. … So get your hands dirty… Your personal experience matters here—without it, it’s all just theories in your head; you’ll be out of touch. … I gave him/her the honest truth: “It’s impossible for me to promise job security for anyone. But think about this logically: we hired you before AI was a thing, and now that you’re significantly more productive with these tools, why would we let you go?”

Companies don’t (usually) fire their most productive people; they invest in them. The real threat isn’t AI—it’s sticking to outdated ways while the industry evolves around you. … The shift to AI-assisted engineering isn’t coming—it’s here.

The Dynamic Between Domain Experts & Developers Has Shifted

The article discusses how the relationship between domain experts and developers has changed in the AI era, emphasizing the increasing importance of domain expertise in building successful AI products. It’s interesting to see the sentence and picture of “I’ve got a great idea for an app…”.

… But today, I’m seeing teams of domain experts wading into the field, hiring a programmer or two to handle the implementation, while the experts themselves provide the prompts, data labeling, and evaluations.

For these companies, the coding is commodified but the domain expertise is the differentiator.

229 things we announced at Google Cloud Next ‘25 – a recap

Google Cloud Next 2025, held in Las Vegas, showcased over 200 announcements emphasizing advancements in AI, infrastructure, and real-world applications.

Here’s a concise summary of AI & Machine Learning:

• Gemini 2.5 Pro: Introduced as Google’s most advanced multimodal AI model, now in public preview across Vertex AI, AI Studio, and the Gemini app.
• Agent Ecosystem: Launch of tools like Agentspace, Agent Development Kit, and Agent2Agent protocol to facilitate the creation and management of multi-agent AI systems.
• Gemini Code Assist: An AI-powered coding assistant integrated into development workflows, offering features like a Kanban board for task management and insight into AI decision-making processes.

Google Is Winning on Every AI Front

The article argues that Google and DeepMind have taken a significant lead in the AI landscape, outpacing competitors like OpenAI, Anthropic, and Meta. The author, who previously had high hopes for OpenAI, now believes that Google’s strategic and technical advancements have positioned it as the dominant force in AI.

(PSA: Many people are interested in this post, so I removed the paywall)

With strong winds forecasted, we spent the weekend cozied up at home—it felt like a mini vacation.

On Saturday, I slept in late after a night of binge-watching TV. Hamer kept whispering in my ear until I finally got up. “This is the first time I’ve seen Dad get up this late,” she said. I lost a bet with Xiaoyan over the pronunciation of “divorce” and had to make lunch—two veggie dishes and a fried egg that turned out surprisingly well. Later, Hamer and I continued our series binge, and even Xiaoyan joined in after dinner, crying during several scenes. That night, I slept soundly in Hamer’s bed.

Sunday was equally low-key. After playing in the morning, we went grocery shopping for braised green bean noodles. Hamer also wanted a new watercolor set because hers lacked a skin-tone color. There were a few tears during the discussion with Xiaoyan, but she got it in the end.

In the evening, Xiaoyan cooked radish and cuttlefish soup—it was delicious. Hamer helped with folding laundry, hanging clothes, and washing fruit. She’s really becoming Mom’s little helper.

Meanwhile, I got deeper into pour-over coffee and finally dialed in the grind size. It’s starting to click.

Last night’s badminton game left me with a twisted ankle, and by morning, it was still sore and uncomfortable to walk on. After dropping Hamer off, I grabbed McDonald’s for breakfast—just had a craving.

Later, I visited the dentist to follow up on a previous check-up. X-rays revealed an old filling that may need a root canal. For now, I had a cleaning and got a reminder: no horizontal brushing, use an electric toothbrush, floss well, and pay extra attention around my implant.

In the afternoon, I worked on setting up an old AI project environment. With help from a colleague, I finally got it running and plan to document the process and improve it next week.

Before heading home, Hamer called and joked that I might get blown away if I didn’t hurry. After dinner, we watched When Life Gives You Tangerines and only realized IU was the lead by episode two.

The long-anticipated windstorm still hadn’t arrived by bedtime—maybe tomorrow.