ChatGPT and OpenAI API solutions: 👑 My Favourite Implementations - Adam Cogan

Custom GPTs help automate routine tasks, with examples including booking systems, scrum coaching, and code review assistance

Enterprise AI implementations should focus on clear documentation, transparency, and setting proper custom instructions to avoid noisy/unhelpful responses

Integration with APIs (like Azure Functions, Dynamics) enables powerful automated workflows while maintaining enterprise data security

Microsoft Copilot adoption is increasing, with 46% of code now being written through AI assistance according to Microsoft statistics

Vector databases and semantic kernel implementations help create more sophisticated enterprise chatbot solutions

Weekly AI review meetings help teams stay current with rapidly evolving capabilities and best practices

Non-developers can now create sophisticated automation using no-code AI tools, democratizing development

Custom instructions and proper prompt engineering are critical for getting reliable results from AI systems

AI implementations should be transparent - mark AI-generated content clearly and maintain human oversight

The trend is moving from pure language models toward AI assistants that can perform actions and integrate with multiple systems