
AutoGen: Microsoft's conversational agent framework (MIT, 38k stars)
Enabling multi-agent conversations with code execution and human-in-the-loop — Microsoft's AutoGen framework for production-grade orchestration.
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Enabling multi-agent conversations with code execution and human-in-the-loop — Microsoft's AutoGen framework for production-grade orchestration.

How we built an automated social media graphics pipeline using Canva's API and AI features — generating 100+ branded assets per week.

How we built a document processing pipeline handling 10K+ pages daily using ChatGPT's API — with structured outputs, function calling, and streaming patterns.

How we migrated from GPT-4 to Claude for code analysis — leveraging 200K token context windows, prompt caching, and multi-shot prompting to cut costs by 60%.

How GitHub Copilot changed our code review process — a quantitative analysis of 500+ PRs measuring acceptance rates, code quality, and developer velocity.

Orchestrating role-based AI agents for complex workflows with local model support — the most popular multi-agent framework with 12.7M monthly downloads.

Running thousands of agents on a single core via the virtual actor model — transparent distribution across machines for scale-out orchestration.

Running DeepSeek V3 and R1 locally on Kubernetes — how we cut API costs by 90%, the hardware requirements, and the quantization trade-offs we made.

Benchmarking Gemini 2.5 Pro against GPT-4o for code generation, image understanding, and audio processing — a 3-month study with production workloads.