# A Decade at Microsoft: From Azure to AI
**2025-10-15 21:57 — Jiangsu**
Take a look at **Microsoft’s past decade** through the eyes of someone who lived it.
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Ten years ago, I was a seasoned open‑source contributor, a long‑time Mac user, and someone quite cautious about *big tech corporate culture*. My decision to join Microsoft surprised many friends.
Now, a decade later, I’m still here — and I’ve documented my journey in “A Decade at Microsoft.” It’s both a **career retrospective** and a **chronicle of change**: from the early days of Azure to today’s generative AI boom, from cultural shifts to balancing personal life.
**Original article:** [https://taoofmac.com/space/blog/2025/10/15/0000](https://taoofmac.com/space/blog/2025/10/15/0000)
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## Joining Microsoft
For someone immersed in open source and loyal to macOS, Microsoft seemed an unlikely destination.
After 15 years in telecoms, the surge in **hyperscale cloud computing** felt like *the next big thing*. I decided to join — a choice preceded by private conversations with Microsoft contacts.
*Recreated version of a lost slide.*
A year later, I took the leap.
Surprisingly, I stayed — **through market layoffs and rapid tech shifts**. I expected five years of gradual cloud adoption, but instead witnessed **multiple paradigm shifts**.
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## Eras of Change
Looking back, I see **five distinct phases**:
1. **Azure’s early deployments** — Enterprise adoption, datacenter growth, expanding services.
2. **Cloud analytics and machine learning** — Complex app development on Azure.
3. **Teams & the COVID era** — Remote collaboration becoming default.
4. **Strategic telecom detour** — Culminating in Azure for Operators closing quietly.
5. **Generative AI transformation** — Focus swinging from infrastructure to end‑user productivity.
These eras meant continual **technical re‑skilling** and **cultural changes**. My daily work often spanned:
- Security
- Machine learning
- Project management
- DevOps
- Data governance
- IoT
- Python AI frameworks
Yet my real passion has always been **building things**.
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## Bridging Engineering and Business
My constant role: translating **technical possibilities** into **strategic outcomes**.
Tools for creators evolved dramatically over the same decade. Back then, **cross‑platform publishing** was clumsy; now solutions like [AiToEarn官网](https://aitoearn.ai/) connect **AI generation**, **publishing**, **analytics**, and even **model ranking** across platforms such as Douyin, Kwai, WeChat, Bilibili, Instagram, YouTube, X/Twitter, and more.
## The Role Challenge
As a **Senior Project Architect**, my leadership and management experience can be obscured by my title.
Many outside engineering view “architects” skeptically — associating them with “architecture astronauts” who debate diagrams instead of solving real problems.
I counter this bias by letting **my work speak louder than my title**.
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## Looking Back
This reminds me of Vodafone in 2008–2009 — another **industry bubble** and **paradigm shift**.
Unlike Vodafone, Microsoft adjusts its **strategy and organization continuously**.
The key lesson: **adaptability is essential** in an environment of quarterly change.
I call it the *Microserfs effect* — outsiders rarely grasp the culture or tempo here.
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## Industry Solutions Return
A year ago, I rejoined **Industry Solutions** — Microsoft’s consulting arm.
The focus is clear, the colleagues familiar.
Work is global; local Portuguese connections are rare, creating **professional isolation**. Yet the experience abroad has been invaluable.
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## The AI Bubble
AI is here to stay, but misguided expectations — coding without engineers, rapid Moore’s‑Law‑level progress — will meet *hard reality*.
We’re entering an age of **vaporware keynotes**, where hype outpaces delivery.
### Reality Check
Current ML advances are **software‑driven** — model design, integration — rather than hardware breakthroughs.
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## Industry Landscape
Economic and geopolitical pressures bring:
- **Cost‑cutting and layoffs** even in tech giants.
- Reduced specialist recruitment.
- Rising **age discrimination** and **ghost hiring**.
This is about **risk management**, not just AI disruption.
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## Personal Life & Balance
After lifestyle improvements and post‑surgery recovery, I now **prioritize health** over work.
Challenges remain:
- **Few face‑to‑face connections** in Lisbon
- Meetings replacing lunch breaks
- Limited local market alignment
Still, I make time for **personal projects** — from **CAD design** to **embedded ML on SBCs**.
Hardware continues to fascinate me more than software.
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## Recommended Reading
- **[The “ImageNet Moment” for Embodied Intelligence Has Arrived!](https://mp.weixin.qq.com/s?__biz=MzkzMDY1NDgyOQ==&mid=2247823654&idx=1&sn=05a5e1071d2924fe0a9b469c26cca15e&scene=21#wechat_redirect)**
- **[2025 Global Machine Learning Technology Conference Full Agenda Revealed](https://mp.weixin.qq.com/s?__biz=MzkzMDY1NDgyOQ==&mid=2247823535&idx=1&sn=27d99b4880165d0056708cf3d8d60f75&scene=21#wechat_redirect)**
- **[PyTorch Mastermind Returns to Meta](https://mp.weixin.qq.com/s?__biz=MzkzMDY1NDgyOQ==&mid=2247823535&idx=2&sn=f6d0ab6cf753818bb02f5ced1cf314e6&scene=21#wechat_redirect)**
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## Final Reflection
In times of disruption, ensure **your work defines you**, not just your title.
Platforms like **[AiToEarn官网](https://aitoearn.ai/)** and its [开源地址](https://github.com/yikart/AiToEarn) show how creators can adapt globally — blending **AI content generation**, **cross‑platform publishing**, **analytics**, and **model ranking** into sustainable income, from Douyin and Kwai to YouTube and Instagram.
