AI-Generated Code Changes Software Work

"I'll share my current workflow. Identify the 2 biggest bottlenecks and suggest how AI could eliminate or reduce them."

MoE (Mixture of Experts):

An architecture where different parts of a model specialize in different tasks, and only a subset is activated for each request. This makes models more efficient and scalable without using full compute every time.

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Not a tech show, but a masterclass in power, decision-making, and incentives at the top. Useful for anyone building or navigating high-stakes environments where strategy is as much about people as it is about product.

Mercor is facing multiple class-action lawsuits after a reported hacking incident exposed sensitive data. As AI companies scale fast, security and trust are becoming just as critical as capability.

What it is:

An AI-powered WhatsApp automation layer that lets businesses run conversations, support, and actions directly inside WhatsApp using intelligent agents.

How you can use it:

Automate inbound queries, qualify leads, send updates, and even complete workflows like bookings or follow-ups, all within WhatsApp, without pushing users to external apps or dashboards.

Good for you if:

You want to engage customers where they already are and turn WhatsApp from a support channel into a high-conversion growth and operations engine.

Sundar Pichai sharing that AI generates around 75% of code at Google points to a shift in how software is actually built. Developers are no longer writing every line themselves. Instead, they are guiding, reviewing, and refining code produced by machines. The role is moving from creation to supervision, where speed increases but so does the need for oversight.

What Ringg thinks:

This changes what it means to be a good engineer. Writing code may matter less than understanding systems, spotting errors, and knowing how to direct AI effectively. It also compresses timelines. What once took days can now happen in hours. But that speed comes with trade-offs. If most code is generated, the bottleneck shifts to review, reliability, and accountability. The next phase of software development will not be defined by who writes the best code, but by who can manage and trust what gets generated.