If I Wanted to Start a Career in AI in 2026, I'd Do This (Without Coding)

About this video

• Video Title: If I Wanted to Start a Career in AI in 2026, I'd Do This (Without Coding)
• Channel: Liam Ottley
• Speakers: Liam Ottley, Dave Eblahar
• Duration: 48:32

Overview

This video features a discussion between Liam Ottley and Dave Eblahar about navigating a career in AI, particularly in 2026. They explore whether coding skills are essential for success in AI, alternative non-coding pathways to monetize AI expertise, and the core skills needed for AI engineers. The conversation also touches on the future of AI agencies and freelancing, the impact of new tools like OpenAI's Agent Builder, and strategies for both technical and non-technical individuals to build successful careers in the rapidly evolving AI landscape.

Key takeaways

• Coding is not mandatory for AI success: While coding skills are valuable, there are multiple avenues to build a successful career in AI without them, including consulting, education, and utilizing no-code tools.
• Diverse AI career paths: Success in AI can be achieved through various roles such as AI engineers, freelancers, consultants, educators, and by leveraging no-code platforms like Make.com and Zapier.
• Importance of practical skills: For AI engineers, key skills include understanding language models, system design, building production-ready applications, RAG concepts, monitoring, evaluation, and deployment strategies.
• Rise of AI agencies and freelancing: The AI market is creating significant opportunities for agencies and freelancers, with strategies like building a personal brand and offering specialized services becoming crucial.
• Emerging tools and platforms: New tools like OpenAI's Agent Builder and MCP servers are changing the landscape, offering more accessible ways to build AI solutions and potentially reducing the need for extensive custom coding for certain applications.
• Education and self-learning: University degrees may become less critical for AI careers due to the rapid pace of technological change. Continuous self-learning through online resources and practical application is key.
• Strategic approach to AI business: For businesses and agencies, understanding client needs, starting with smaller, achievable AI solutions (like those enabled by MCP servers), and demonstrating value is more effective than tackling overly complex projects initially.