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  • 🍔🧠 OpenAI's Stack for Streaming to Billions of Customers

🍔🧠 OpenAI's Stack for Streaming to Billions of Customers

PLUS: Designing a Rate Limiter 🚦, Agent Programming Deep Dive 🤯, Developer Salary Report 💵

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📚 Software Engineering Articles

🗞️ Tech and AI Trends

👨🏻‍💻 Coding Tip

  • Use inotifywait for automated builds and real-time file monitoring

Time-to-digest: 5 minutes

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OpenAI revealed its real-time data streaming infrastructure that powers ChatGPT and other AI systems at Current 2025. The platform processes massive volumes of data through Kafka and Flink to enable instant responses, continuous learning, and global-scale operations.

The challenge: Building infrastructure that can handle enormous data volumes with sub-second latency while coordinating model training, inference, and feedback loops across a global system.

Implementation highlights:

  • Multi-region architecture: Deployed Kafka clusters across regions with failover capabilities

  • PyFlink extensions: Custom adaptations for ML training and experimentation workflows

  • Kafka Forwarder: Simplified consumption layer converting pull to push-based model

  • Zero-downtime migrations: Strategies for seamless cluster updates and region failovers

  • Scale optimization: Handling massive throughput with custom performance tuning

Results and learnings:

  • Enterprise-ready: Production infrastructure supporting ChatGPT's global user base

  • Developer friendly: Simplified streaming interfaces reduce complexity for ML teams

  • Future-proof: Architecture designed to scale with growing AI model and usage demands

The key takeaway is that even cutting-edge AI needs robust data infrastructure. OpenAI shows that stream processing isn't just plumbing - it's the nervous system that makes real-time AI possible.

ARTICLE (show-me-the-money)
Remote Software Engineer Salary Report

ARTICLE (ai-cheap-cheap)
LLMs are cheap

ARTICLE (agent-smith-mode)
How I Program with Agents

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Brief: Meta nears a $14B investment in Scale AI, hiring its founder Alexandr Wang to lead a new AI lab as Zuckerberg ramps up efforts to catch rivals like OpenAI.

Brief: Researchers are using focused ultrasound stimulation (FUS) to treat inflammation, diabetes, and obesity by hacking nerve signals—potentially replacing pills with wearable, noninvasive devices.

Brief: XRobotics' compact pizza-making robots are producing 25,000 pizzas monthly, saving restaurants 70-80% of staff time, after raising a $2.5M seed round to scale production.

Brief: Frustrated by Meta’s AI lag, Zuckerberg makes his biggest bet yet—a $14B stake in Scale AI—while hiring its founder Alexandr Wang to revamp the company’s AI strategy amid fierce competition.

Brief: AMD debuts its MI400 AI chips designed for hyperscale data centers, with OpenAI’s Sam Altman endorsing them as a cost-efficient rival to Nvidia’s GPUs, promising rack-scale integration and lower power consumption.

This week’s coding challenge:

This week’s tip:

Use Linux's inotifywait command for real-time file system monitoring and automated development workflows. The command provides granular control over file system events and can trigger custom actions through shell scripting.

Wen?

  • Local development: Automate build processes without heavyweight watch modes or polling.

  • Custom deployment pipelines: Trigger immediate deployments when specific files change.

  • Log monitoring: Create real-time log aggregation systems by watching log directories.

Become the kind of leader that people would follow voluntarily, even if you had no title or position.
Brian Tracy

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