Yes, @googledrive scans your files all of it. Their scan and detection AI is stupid and if misidentified, there is no way to get it back, to report it and explain (AI won't listen and understand the report).
Somehow a 100-line SQL query is considered unmaintainable, but splitting the same logic across five services and a message queue is considered architecture.
Saat dokter menanyakan obat yang dikonsumsi, jawabannya ternyata sederhana:
Ibuprofen.
Ia meminumnya sebelum lari untuk mencegah nyeri, lalu mengonsumsinya lagi setelah olahraga karena tubuh terasa pegal.
Di sinilah masalahnya mulai terlihat.
3. Dark skin around your neck/armpits.
This is called acanthosis nigricans.
It causes dark, thick, almost velvety patches — commonly around the neck, armpits, or groin.
It's strongly associated with insulin resistance.
Bir Kere Girince Saatlerce Çıkamayacağınız 50 Site
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İnternet, algoritmanın önünüze koyduğu o beş siteden ibaret değil.
Roles are collapsing.
If you're a "Software Engineer" today, you may be a "Product Engineer" soon - with many more responsibilities.
So:
- Learn design/UX/QA/PM skills.
- Focus more on the user, and less on the syntax.
Image via Gartner.
@dr__madmax I already made one! Omawrite is what I've been using to write all essays for the last few weeks. It's the new default in Quattro. Typora is gone. https://t.co/AEC5PSrBLz
Instead of watching 1 hour of Netflix tonight, watch this ex-Google Chief Scientist Jeff Dean’s lecture. It’s the clearest explanation I’ve seen of the full AI engineering stack - from building LLMs from scratch all the way to one human coordinating 100 agents.
The best part is that it’s useful whether you’ve never touched a model or you’ve been shipping agent systems every day for the past year.
Bookmark it & watch the whole lecture this weekend, because it might end up being the most valuable thing you learn all week.
In 2001, @JeffDean and Sanjay Ghemawat did the math and realized Google’s entire search index would fit in RAM — then shipped it in a few days, and search got fast.
In 2013, another napkin calculation showed that three minutes of daily speech recognition per user would require doubling Google’s server fleet. That one became the TPU.
At Startup School 2026, Google’s Chief Scientist talks with YC’s @sdianahu through the thought experiments behind both, why inference hardware is the next specialization, and where two or three people in a room can still win.
00:07 — Are AI Models Already Junior Engineers?
01:44 — AI Systems That Improve Themselves
02:40 — The Google Search Breakthrough That Changed Everything
04:38 — AI Agents Will Run for Weeks
05:58 — The Napkin Math That Led to TPUs
09:20 — How to Find Breakthrough Ideas
10:25 — The AI Engineer's New Mental Model
12:33 — Why AI Is Really an Energy Problem
16:11 — Context Engineering Is the Next Frontier
19:46 — The Skill That Made AI Better at Optimization
22:13 — Why Long-Running Agents Fail
25:21 — Where Startups Can Still Beat Google
31:19 — How to Become an AI-Native Founder
36:36 — Question Your Biggest Assumptions
42:08 — AI That Builds Better AI
50:02 — Build Something That Truly Matters
Meta's chief ai officer @alexandr_wang :
"Internally at Meta, we have seen cases where, if you develop the right agentic loop and have the right evaluation system and metric for the agents to optimize, a swarm of agents can accomplish more than a team of 100 engineers. They can do it very handily, actually, very easily."
Alexandr Wang was talking to CEO of Y Combinator @garrytan at Y Combinator Startup School 2026
----
full video link in comment
I'm a Principal engineer & I passed system design rounds of Amazon, Atlassian, Walmart, Saleforce, and Deliveroo.
Trust me, learning system is not hard. Start from these fundamental concepts:
1) Load Balancing: https://t.co/3jKCLiI6vl
2) CDN: https://t.co/dxzCmm9gAf
3) Caching: https://t.co/pRgn0FTPp2
4) Cache Invalidation: https://t.co/QrfRjJ57gd
5) Rate Limiting: https://t.co/LE5ECM2tGt
6) API Gateway: https://t.co/DgU8cBDUVr
7) CAP Theorem: https://t.co/a8WydnAIxd
8) Sharding: https://t.co/XQLU6eDriD
9) Replication: https://t.co/KuDkFH0fjx
10) Partitioning: https://t.co/3WXKeZLbLa
11) Queues: https://t.co/JchEoCcFmF
12) Microservices: https://t.co/aAQfM6AWMq
13) Microservices Vs Monoliths: https://t.co/bTaIIWkPU3
14) Fault Tolerance: https://t.co/qXNBoyOqYT
15) Database Scaling: https://t.co/D2lvPm1wkB
16) Service Discovery: https://t.co/z2DpwbJBVI
17) Consistency models: https://t.co/K2r3nMcCQu
18) Eventual Consistency: https://t.co/SWiz4ckIKR
19) Distributed Transactions: https://t.co/xqL7BTJxXn
20) Leader Election: https://t.co/ApNaYSnSFj
21) Horizontal vs Vertical Scaling: https://t.co/IFuEmzMfob
22) Back of the Envelope Estimation: https://t.co/7ntEmtVggQ
23) Idempotency, Data Latency & Finale: https://t.co/fNArLx4MrW
Let me know what you'd like me to cover, would love to help :)
Jeff Bezos explains the heavy-eater test behind Amazon Prime.
The finance model said the idea looked "horrifying."
Amazon would offer "unlimited shipping."
No minimum order threshold.
A customer could buy "a single $20 item" or "a single $10 item" and still get "free two-day shipping."
Then Bezos names the part most models miss:
"Shipping is expensive, and customers love free shipping."
"When we modeled this, it didn't look pretty."
"What happens when you offer a free, all-you-can-eat buffet? Who shows up to the buffet first? The heavy eaters."
I like this as an operator test.
A scary early cohort can mean the product is broken. It can also mean the people with the most acute pain found it first.
The question is whether the heavy users are abusing the system, or proving where the market has been under-served.
Prime worked because the expensive users were not a rounding error. They were the demand signal.
Jeff Bezos at The Economic Club of Washington, D.C.
@JeffBezos
My friend applied to 200 tech jobs in two years. No MIT. No Stanford.
Last month Anthropic offered him $750,000.
I asked him how he broke in from zero.
He sent me the exact video that got him in. Anthropic's 2 hour course on "How to become an AI engineer in 2026"
Their core team shows exactly how to architect & build AI agents from scratch.
I watched it last night.
Halfway through, I realized I could break into an AI lab in weeks, not years.
Bookmark this and read the article below.
• 00:00 - AI agents with graph engineering
• 06:41 - AI agent architecture
• 14:31 - building AI agent loops live
• 1:15:24 - AI agentic RAG
• 2:20:42 - Anthropic interview process
TDD is a human discipline. I don't expect agents to follow it. I DO expect agents to write unit tests as carefully and comprehensively as a human would, and I ensure that by running coverage, crap, and mutation tests.
The reason agents don't have to follow the tight human TDD loop is that they have better and bigger short term memories.