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OpenAI

GPT and beyond

OpenAI models power many of my AI implementations. I build production systems with GPT-4, fine-tuning, embeddings, and function calling.

3+years in production
40+projects shipped
expertproficiency

My take

Why I use OpenAI

OpenAI sets the pace on capability. GPT-4-class models, structured outputs, the Assistants API, and the Realtime API give me a complete toolkit. I pair them with Claude where reasoning depth and longer context matter.

Want the broader stack philosophy? Read about how Sri picks tools or browse engineering insights.

Honest assessment

Strengths & tradeoffs

No tool is perfect. Here's what shines and what to watch for.

Strengths

  • Frontier-class model performance
  • Structured Outputs (JSON-schema-enforced)
  • Realtime API for voice and streaming
  • Mature SDKs in every major language
  • Extensive fine-tuning options

Tradeoffs (honestly)

  • Cost adds up fast at scale without caching
  • Rate limits require enterprise tiers for serious traffic
  • Closed-source - less customization than open models
  • Output drift when models update

Fit assessment

When to reach for OpenAI

Pick the right tool for the job.

Best fits

Production chatbots and assistants

Content generation pipelines

Code review and codegen tooling

Embedding generation for RAG

Voice agents via Realtime API

Not ideal for

Workloads requiring fully on-prem deployment

Use cases sensitive to provider data policy

Tasks where open models suffice and cost matters

Common use cases

ChatbotsContent generationCode assistanceRAG systems

Resources

Learn more

Curated official docs, tutorials, and writing on OpenAI.

Need help with OpenAI?

Whether you're starting fresh or optimizing an existing implementation, I can help you get the most out of this technology. Read more in insights or get in touch.

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