AI Engineering 2025 PLAN - Max out AI COMPUTE for o1 Preview, Realtime API, and AI Assistants

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AI Summary

Summary of the Video Transcript

Vision for the Future of Engineering (2025)

• Utilize generative AI, AI agents, and AI assistants to enhance data gathering, synthesis, and building processes.
• Four key AI advancements in 2024:
  • Sonic 3.5
  • Structured outputs
  • 01 reasoning models
  • Real-time API

Demonstration of ADA - Personal AI Assistant for Engineering

• ADA can:
  • Load SQL tables into memory.
  • Create markdown documents with table definitions.
  • Execute SQL queries and save results as CSV files.
  • Generate Python code for data visualization (bar charts).
  • Manage files (creation and deletion).

Importance of AI Tooling

• AI tools enable a new level of software engineering.
• Prompt design, AI agents, and AI assistants are key components.
• AI assistants act as an orchestration layer, managing multiple AI agents.
• Future goal: Agentic software that operates autonomously.

The Role of an Engineer

• Engineers ingest data and synthesize it into outputs like code, information, research, media, and products.
• AI tooling can assist in both the ingestion and synthesis processes.

AI Tooling Breakdown

• Prompts: Fundamental unit of knowledge work.
• AI Agents: Combine prompts, logic, and data to solve specific problems.
• AI Assistants: Orchestration layer to control multiple AI agents.
• Agentic Software: Autonomous software that prompts the user for next actions.

Engineering in 2025

• Engineers should leverage generative AI to perform tasks faster, better, or cheaper.
• Productivity gains from using AI tooling can be significant.
• Tasks should be pushed up the generative AI composition chain based on frequency and importance.
• Focus on automating ingestion and synthesizing tasks with AI tooling.

Plans for the Channel

• Explore meta prompting concepts.
• Release an AI coding course.
• Continue developing next-generation AI tooling capabilities.

Concrete Example: Code Generation

• Code generation is a key use case for AI tooling in software engineering.
• It is important to match ingestion tasks with the highest level of AI tooling possible.

Conclusion

• The presenter’s plan for 2025 involves optimizing ingestion and synthesizing tasks with generative AI tooling.
• Upcoming content includes meta prompting, an AI coding course, and advancements in AI tooling.

(Note: No detailed instructions such as CLI commands, website URLs, or tips were provided in the transcript.)