Ryan Peterman(@ryanlpeterman):Should people still learn to code if coding is largely solved? Thariq Shihipar (Engineer on Anthropic’s Claude Code team): "I think being technical is really important. Knowing how do computers work? How do languages work? What are the hard things like? All of these things are actually really important to learn. Like we talked about earlier. Oh, the only way you can tell you've solved the Riemann Hypothesis or the Jacobian Conjecture is like, if you're a great mathematician. Right? And in the same way, the only way you can tell if you're, like, built great software is like, if you're a great software engineer. When Boris says coding is solved, it just means we don't get stuck in the same ways that we used to before. Like, very few people in the entire world could write software, and they were very rare. And even if you got them all together, there were so many other reasons why it wouldn't work. Right? And now that coding is solved, you can use coding to do all these other things that we've not done before." For the full conversation, you can search Thariq Shihipar on my YouTube, Spotify or Apple Podcasts (link in bio)

2026.09.08 15:01

Should people still learn to code if coding is largely solved? Thariq Shihipar (Engineer on Anthropic’s Claude Code team): "I think being technical is really important. Knowing how do computers work? How do languages work? What are the hard things like? All of these things are actually really important to learn. Like we talked about earlier. Oh, the only way you can tell you've solved the Riemann Hypothesis or the Jacobian Conjecture is like, if you're a great mathematician. Right? And in the same way, the only way you can tell if you're, like, built great software is like, if you're a great software engineer. When Boris says coding is solved, it just means we don't get stuck in the same ways that we used to before. Like, very few people in the entire world could write software, and they were very rare. And even if you got them all together, there were so many other reasons why it wouldn't work. Right? And now that coding is solved, you can use coding to do all these other things that we've not done before." For the full conversation, you can search Thariq Shihipar on my YouTube, Spotify or Apple Podcasts (link in bio)

Ryan Peterman@ryanlpeterman

2026.09.07 13:05

Thariq Shihipar (@trq212) is an engineer on Anthropic’s Claude Code team I asked him how Anthropic makes the most out of the models for engineering and how the industry will change soon. In this episode: • Internal best practices in leveraging the models • What percent of Anthropic's work is fully autonomous • How Anthropic maintains higher volumes of code • What has worked in preventing AI-written breakages Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:29 Onboarding at Anthropic 02:53 Internal capabilities vs external perception 06:16 Model vs Harness 08:55 What percent of Anthropics changes are fully autonomous 14:51 Computer use 17:42 How to make the most out of your compute 20:45 Loop engineering 22:47 Where the industry will go soon 26:02 Which model do Anthropic engineers use 27:38 Is learning a particular model worth it 30:56 Prompting tips for todays models 35:04 How to get the models to do tasteful work 39:00 How much of writing is done by AI at Anthropic 45:36 Code ownership and maintenance at Anthropic 52:04 How Anthropic prevents breakages 55:24 Visibility and sharing your work 58:42 Luck surface area example 01:00:57 Should people still learn to code 01:07:42 Advice for his younger self 01:09:58 Outro