The content explores the critical decision for businesses by 2026: whether to use ready-made AI solutions like ChatGPT or invest in custom AI software. This strategic choice impacts long-term value and business processes as AI transitions from experimentation to task optimization.
O conteúdo explora a transição de ferramentas genéricas de IA para a construção de modelos personalizados de IA para coaches e consultores. Ele propõe um "Trigger-to-Insight Workflow" que automatiza a análise de eventos de clientes para gerar insights precisos, liberando os profissionais para focarem em desafios humanos complexos.
This content advocates for a paradigm shift from consuming generic AI tools to designing custom AI models tailored for specific actions and triggers. It highlights how this approach can create intelligent workflows, such as an AI system generating personalized reflection prompts for clients based on session transcripts and other data.
This article provides a practical checklist for deciding when to build a custom AI agent versus using built-in AI tools, based on the author's personal experience. It highlights criteria such as repetition, complexity, consistency, and context to help users make informed choices and avoid overcomplicating their work.
Nanochat offers a groundbreaking opportunity to build a custom ChatGPT-like language model for under $100. This open-source project emphasizes affordability, accessibility, hands-on learning, and customization in LLM development.
These AI development solutions are designed to help businesses adopt intelligent, adaptive systems, moving beyond basic automation. Custom solutions ensure higher accuracy, efficiency, and long-term scalability for business operations.