Should I Learn Claude or
OpenAI First?

Start with whichever has better documentation for your use case. In 2026, both platforms are mature and well-documented. OpenAI has broader ecosystem integration and more tutorials available. Claude excels at longer context windows and nuanced instruction following. But here's the truth: spending 2 weeks with each platform teaches you more than 2 months with just one. The concepts transfer directly.

OpenAI currently appears in more job postings due to first-mover advantage. However, Anthropic (Claude) is growing rapidly in enterprise. The smartest move? List both on your resume. Most production systems in 2026 use multiple models anyway. Employers value developers who can evaluate and switch between providers based on requirements.

Both have similar learning curves for basics. OpenAI's API has more legacy patterns to navigate due to its longer history. Claude's API is cleaner but has fewer community resources. The real learning curve is understanding prompt engineering, token economics, and when to use AI vs traditional code - these skills transfer 100% between platforms.

Surprisingly easy if you learned the right way. The API calls are slightly different, but the core patterns are identical. Developers who learned principles first can switch in a day. Those who memorized one API's quirks struggle more. This is exactly why coaching focuses on transferable skills.

Not always, but it helps significantly. Many teams use OpenAI for some tasks and Claude for others. Knowing both signals that you understand the landscape and can make informed decisions. It also protects your career - if one platform has issues or changes pricing, you're not stuck.

Coaching gives you a personalized learning path based on your goals. Instead of guessing which platform matters for your target role, you get guidance from someone who's placed developers at companies using both. We focus on the 20% of knowledge that covers 80% of use cases, so you're productive fast on any platform.

Not necessarily. While some programming experience is helpful, many of my clients have successfully transitioned from web development, data science, or other technical backgrounds. We'll assess your current skills during our strategy call and create a personalized plan that meets you where you are.

Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.

You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.

Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.

Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.

Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.