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0:00 - Intro to Devin, a new AI tool released by Cognition Labs
0:41 - Overview of what Devin can do
1:00 - Comparison of Devin's capabilities to GPT-4
2:25 - Why GPT doesn't make full apps properly yet
2:56 - My experience building a similar tool called autocode Pro
3:13 - Implications and how I see the space evolving
5:00 - The main problem: agents getting sidetracked and stuck in "pockets"
6:18 - Devin's performance compared to previous agents
7:09 - The problem of "pocketing" and the need for manual intervention
7:38 - The importance of clear and concise prompts (high-quality writing)
9:37 - The role of deployment and scaling decisions
10:14 - The challenge of gaining users and distribution
11:09 - Evolution of software engineer roles
11:42 - Issues with hyper-specialization and identity attachment in software engineering
12:30 - The impact of AI and funding crunches on the software industry
13:20 - The importance of problem-solving over specific tools or languages
14:21 - Problem with the purist of front-end engineer
14:57 - Perspective on the software industry in India (exports, services, and consumer successes)
16:07 - Thinking like an engineer to solve problems
16:28 - Elon Musk's tweet and the my belief in truth-seeking
17:03 - Being flexible and adapting as AI automates jobs
17:29 - The potential impact of AI on the economy
18:21 - Conclusion: AI as liberation, not the enemy

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