AI is Going to Make Programming Obsolete π
Key Takeaways at a Glance
00:00
Programming as we know it is going to die.00:53
Coding is a valuable skill.02:10
Coding is difficult and humans are not naturally good at it.05:07
GitHub co-pilot has revolutionized coding.07:48
AI coders are faster and cheaper than human programmers.11:19
AI coding still has limitations.12:35
Data and synthetic data will improve AI coding.13:10
Solutions to current limitations include codebase mapping and compression.13:54
AI is transforming the future of coding.21:27
Natural language will replace traditional programming languages.23:47
Learning to code is still valuable.
1. Programming as we know it is going to die.
π₯85
00:00
The speaker believes that programming is going to become obsolete.
- The speaker has done research and come to this conclusion.
- They will explain their reasoning and provide evidence.
2. Coding is a valuable skill.
π₯78
00:53
The speaker acknowledges that coding is a valuable skill that they have personally benefited from.
- Coding allows individuals to bring their ideas to life and build things independently.
- It provides the freedom to create and iterate quickly.
3. Coding is difficult and humans are not naturally good at it.
π₯82
02:10
The speaker highlights the challenges of coding and the limitations of human coding abilities.
- Coding requires thinking through complex problems and writing instructions in a foreign language.
- Bugs are hard to spot and humans struggle to keep track of every edge case.
4. GitHub co-pilot has revolutionized coding.
π₯89
05:07
The speaker emphasizes the impact of GitHub co-pilot, an AI assistant for coding.
- GitHub co-pilot can generate code and fill in gaps, reducing trial and error.
- It has made coding less tedious and improved productivity.
5. AI coders are faster and cheaper than human programmers.
π₯87
07:48
The speaker compares the cost and efficiency of human programmers to AI coders.
- AI coders can write code faster and at a lower cost than human programmers.
- AI scales horizontally and can access knowledge and syntax more effectively.
6. AI coding still has limitations.
π₯76
11:19
The speaker acknowledges the current limitations of AI coding.
- Context window limitations and data availability are challenges for AI coding.
- AI models may not be up-to-date with the latest APIs and solutions.
7. Data and synthetic data will improve AI coding.
π₯83
12:35
The speaker discusses the potential for data and synthetic data to enhance AI coding.
- As more code is written with AI tools, it can be used to train models and improve coding capabilities.
- The snowball effect of more productive coding and continuous model improvement.
8. Solutions to current limitations include codebase mapping and compression.
π₯79
13:10
The speaker mentions codebase mapping and compression as potential solutions to current limitations.
- Codebase mapping can compress large code bases into shorthand that AI models can understand.
- This allows AI models to comprehend entire code bases and iterate on existing projects.
9. AI is transforming the future of coding.
π₯95
13:54
AI will automate coding tasks, making programming skills less necessary in the near future.
- Large language models will understand and generate code based on human requirements.
- Non-technical individuals will be able to write software using AI tools.
10. Natural language will replace traditional programming languages.
π₯92
21:27
In the long term, humans will communicate with large language models using natural language, eliminating the need for traditional programming languages.
- Humans will speak in natural language, and large language models will program devices accordingly.
- Programming will become a matter of expressing desired outcomes rather than writing code.
11. Learning to code is still valuable.
π₯88
23:47
While AI will automate many coding tasks, learning to code is still valuable for problem-solving, logical thinking, and reasoning.
- Coding teaches how to break down problems and use logic to solve them.
- Computer science skills are still valuable, but working with AI will become increasingly important.