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Welcome back!

This week, we’ll solve the most asked Linked List problem. Every big tech company has asked this problem. Can you solve it without looking at the solution?

Today we will cover:

• Reverse Linked List

• Eventual vs Strong Consistency

Read time: under 4 minutes

CODING CHALLENGE

Reverse Linked List

Given the head of a singly linked list, reverse the list, and return the reversed list.

Example 1:

Input: head = [1,2,3,4,5]
Output: [5,4,3,2,1]

Example 2:

Input: head = [1,2]
Output: [2,1]

Solve the problem here before reading the solution.

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SOLUTION

To reverse a linked list, we can use three pointers: one for the previous node, one for the current node, and one for the next node.

We'll iterate through the list, changing the direction of each pointer.

For each node, we store its next node, update its next pointer to point to the previous node, and move our pointers one step forward.

The time complexity of this solution is O(n), where n is the number of nodes in the linked list.

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SYSTEM DESIGN

Eventual vs Strong Consistency

When building distributed systems, one of the biggest challenges is keeping data consistent across multiple servers. You have two main options: Strong Consistency and Eventual Consistency. Let's understand when to use each approach.

Strong Consistency ensures that all servers have the exact same data at all times. When you write data to one server, the system waits until all other servers have updated before confirming the write.

While Strong Consistency gives accurate data, it comes with a cost. The system has to wait for all servers to respond, which makes writes slower. If some servers are down or slow to respond, the whole system slows down. This approach works well for systems that need absolute accuracy, like banking transactions.

Eventual Consistency takes a different approach. It allows servers to have different versions of data temporarily, but ensures they all match up eventually. When you write data to one server, the system confirms the write immediately and updates other servers in the background. This makes writes much faster since you don't have to wait for all servers to sync.

The trade-off is that different users might see different versions of data for a short time. For example, when you post on social media, some of your followers might see your post immediately while others see it a few seconds later. This is fine for many applications where perfect accuracy isn't critical.

Here's a comparison of both approaches:

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NEWS

This Week in the Tech World

SpaceX Acquires xAI: Elon Musk merged SpaceX with his AI startup xAI, valuing the combined entity at $1.25 trillion. The deal aims to build data centers in space ahead of a mega IPO.

Waymo Raises $16B: Alphabet's robotaxi unit raised $16 billion at a $126 billion valuation. The funding will fuel expansion to 20+ cities in 2026, including Tokyo and London.

Anthropic Tool Sparks $285B Selloff: Anthropic's new Claude Cowork AI agents triggered a massive selloff in software stocks. Salesforce, ServiceNow, and Intuit all dropped over 7% as AI disruption fears grew.

Intel Pushes Into GPUs: Intel CEO Lip-Bu Tan announced the company will build data center GPUs to compete with Nvidia. Intel has hired a chief GPU architect from Qualcomm.

AMD Stock Crashes 17%: AMD shares plunged 17% despite beating Q4 earnings. Investors were disappointed by softer-than-expected Q1 guidance amid the AI spending boom.

Alphabet Beats, Plans $180B Capex: Google parent Alphabet reported $113.8B in Q4 revenue, up 18% YoY. The company plans up to $185B in AI infrastructure spending for 2026.

Pinterest Fires Layoff Trackers: Pinterest CEO Bill Ready fired engineers who built an internal tool to track layoffs, calling them "obstructionist." The company is cutting 15% of staff.

Google Chrome Gets AI Agents: Google launched "auto browse" in Chrome, letting Gemini AI perform multi-step tasks like booking travel on users' behalf. The feature targets AI Pro subscribers.

Microsoft Tanks 10% on AI Spend: Microsoft stock dropped 10% after reporting $37.5B in quarterly AI capex, its biggest single-day fall since 2020. Azure growth slowed despite record spending.

BONUS

Just for laughs 😏

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