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Videos CoEIs6Xm8m8

Open Source Is Dead. Long Live Open Source. — Saoud Rizwan, Cline

index_state ready data_status ok

AI Engineer· published 2026-08-07· 0:17:30· en-US· indexed 2026-08-10 19:34

Open on YouTube

Scene timeline

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What was stored

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Provenance

Each pipeline stage, its state and the model that produced it
stage state model started took
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stt done 2026-08-08 23:38 18s
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Frames, and what the machine read

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    10. TRACK 8• JULY 2, 20260.95
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    1. ZIZIG0.95
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    3. World'sFair1.00
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    5. ← Back to Home0.99
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    7. The Zig community is decentralized. Anyone is free to start and maintain their own community, which is not subject to these rules.0.99
    8. This document contains the rules that govern these spaces only:0.99
    9. • The ziglang organization on Codeberg0.98
    10. • #zig IRC channel on Libera.chat0.98
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    13. maintain a positive environment, especially when disagreements occur.1.00
    14. Strict No LLM / No AI Policy0.97
    15. No LLM-generated content, whether it be code or prose.0.99
    16. No paraphrasing LLM-generated content.1.00
    17. No LLMs for editing, including fixing spelling or grammatical errors.0.99
    18. No LLMs for translation. English is encouraged, but not required. You are welcome to post in your native language and rely on others to0.99
    19. have their own translation tools of choice to interpret your words.1.00
    20. No LLMs for brainstorming and then sharing the results of that brainstorming, even if you create the prose. If you use a chatbot to give1.00
    21. you advice on a comment on the issue tracker, that comment is unwelcome.1.00
    22. No LLMs for finding bugs.1.00
    23. No talking about use of chatbot/LLM services.1.00
    24. Profession by Isaac Asimov0.98
    25. TRACK 8· JULY 2, 20260.96
    26. World'sFair1.00
    27. Agentic Engineering1.00
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    3. Daniel Stenberg · 3rd+0.97
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    5. curl CEO. Code Emitting Organism0.99
    6. 1yr· Edited ·0.91
    7. That's it. I've had it. I'm putting my foot down on this craziness.0.99
    8. 1. Every reporter submitting security reports on #Hackerone for #curl now needs1.00
    9. to answer this question:1.00
    10. "Did you use an Al to find the problem or generate this submission?"1.00
    11. (and if they do select it, they can expect a stream of proof of actual intelligence0.99
    12. follow-up questions)1.00
    13. 2. We now ban every reporter INSTANTLY who submits reports we deem Al slop.0.99
    14. A thresnold nas been reached. we are errectively being DDoSed. Ir we couid, we0.94
    15. would charge them for this waste of our time.0.99
    16. We still have not seen a single valid security report done with Al help.0.98
    17. 6,7181.00
    18. 2546401.00
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    22. TRACK 8• JULY 2, 20260.96
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    7. à Pull requests 730.95
    8. Agents0.96
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    19. Hey all, update on the tidraw policy with regard to contributions.0.97
    20. For the good of the project, we're going to begi0.99
    21. automatically closing pull requests from external contributors0.99
    22. We will of course1.00
    23. continue to welcome issues, bug reports, and discussions. This is a temporary policy until GitHub provides better tools for managing0.99
    24. contributions.1.00
    25. Getting ahead of it1.00
    26. Like many other open-source projects on GitHub, we've recently seen a significant increase in contributions generated entirely by Al0.99
    27. tools. While some of these pull requests are formally correct, most suffer from incomplete or misleading context, misunderstanding of0.99
    28. the codebase, and little to no follow-up engagement from their authors.1.00
    29. An open pull request represents a commitment from maintainers: that the contribution will be reviewed carefully and considered0.99
    30. seriously for inclusion. For that commitment to remain meaningful, we need to be more selective. For now, that means closing first and1.00
    31. selectively re-opening pull requests that are actually under consideration, with the expectation that most unsolicited submisslions will0.99
    32. not be reviewed.1.00
    33. Weird year coming0.99
    34. I first made the tldraw repository public in 2021, and I've been proud to invite public contribution to its code and have been happy to0.98
    35. have many improving pull requests over the years. I'm sorry to shut that down, however I sincerely believe this decision is in the best0.99
    36. interests of the project, our code, and our community. With luck, GitHub will soon roll out management features that let us open things0.99
    37. back up.0.97
    38. This is going to be a weird year for programmers and open source especially. For now, whether you've contributed before, are interested0.99
    39. in contributing in the future, or just are a friend of the project: thank you and please hang on while we all figure this stuff out.0.99
    40. 881.00
    41. TRACK 8· JULY 2, 20260.94
    42. World's Fair0.99
    43. Agentic Engineering1.00
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    1. AlEngineer0.98
    2. World'sFair1.00
    3. Code1.00
    4. Issues1.00
    5. Pull requests0.99
    6. Agents1.00
    7. Discussions1.00
    8. Actions1.00
    9. Projects1.00
    10. Wiki1.00
    11. Security1.00
    12. Insights1.00
    13. Settings1.00
    14. 0.79
    15. General1.00
    16. Get started with Discussions1.00
    17. Engage your community by having discussions right in your repository,1.00
    18. Set up discussions0.99
    19. where your community already lives0.99
    20. Projects1.00
    21. Pull requests1.00
    22. Pull requests allow others to suggest changes to your repository.1.00
    23. Pull request permissions0.99
    24. Creation allowed by: Collaborators only1.00
    25. If restricted, pull requests will still be readable by everyone who can see this repository.0.98
    26. TRACK 8· JULY 2, 20260.94
    27. World's Fair0.99
    28. Agentic Engineering1.00
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    1. AlEngineer0.97
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    3. Trivy scanner1.00
    4. LiteLLM's1.00
    5. Trivy exfiltrates1.00
    6. (GitHub Actions marketplace)1.00
    7. CI/CD pipeline runs0.99
    8. Cl/CD environment0.98
    9. compromised1.00
    10. compromised Trivy1.00
    11. secrets1.00
    12. 81.00
    13. END USER INSTALLS0.99
    14. PyPI token publishes0.98
    15. Attacker obtains1.00
    16. Steals SSH keys1.00
    17. malicious 1.82.7 & 1.82.80.98
    18. PyPI publish token0.98
    19. API keys· crypto keys0.95
    20. GitHub PAT defaces the1.00
    21. + GitHub PAT1.00
    22. installs a backdoor0.98
    23. maintainer profile & repos0.99
    24. remote command execution1.00
    25. cline.bot1.00
    26. TRACK 8• JULY 2, 20260.96
    27. World's Fair0.99
    28. Agentic Engineering1.00
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    1. Gadget Revieu.0.87
    2. AlEngineer0.98
    3. World's Fair0.96
    4. Month Due To No Usage Limit On Licenses0.99
    5. Company Blew $5OOM On Claude Al In One0.96
    6. For Employees1.00
    7. May 29, 2026 - 2 min read0.96
    8. Nikshep Myle0.99
    9. 61.00
    10. PRESENTED BY1.00
    11. ANTH.P... ☆0.97
    12. A mysterious enterprise just torched $500 million in a single0.99
    13. Microsoft1.00
    14. month on Anthropic's Claude Al platform, according to Axios0.99
    15. reporting.0.99
    16. The culprit? No usage limits on employee licenses,1.00
    17. turning what should have been controlled experimentation into a1.00
    18. financial bloodbath that makes your surprise Netflix subscription1.00
    19. charges look quaint.1.00
    20. You've probably experienced the sting of unexpected cloud bills1.00
    21. before—maybe a few hundred dollars when that side project1.00
    22. accidentally left servers running. Scale that feeling up by several0.99
    23. million times. This anonymous enterprise learned the hard way1.00
    24. that token-based Al pricing without guardrails transforms helpful1.00
    25. productivity tools into budget-devouring monsters faster than a0.99
    26. TikTok algorithm learns your guilty pleasures.1.00
    27. TRACK 8· JULY 2,20260.95
    28. World's Fair0.99
    29. Agentic Engineering1.00
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    1. EDITORS' PICK | INNOVATION > CLOUD0.96
    2. AlEngineer0.99
    3. Uber Burns Its 2O26 AI Budget In Four Months On0.98
    4. World'sFair1.00
    5. Claude Code1.00
    6. By Janakiram MSV, Senior Contributor. I cover emerging technologies with ...0.98
    7. Published May 17, 2026, 11:18pm EDT, Updated May 27, 2026, 12:17pm EDT0.98
    8. 0.69
    9. PRESENTED BY0.99
    10. PIXABAY1.00
    11. Taxi1.00
    12. Uber exhausted its entire 2026 artificial intelligence budget by April, four months into0.99
    13. Microsoft1.00
    14. the calendar year, after Anthropic's Claude Code spread across roughly 5,ooo engineers1.00
    15. faster than the company's finance models had anticipated.0.99
    16. Chief Technology Officer Praveen Neppalli Naga confirmed the overrun to The0.99
    17. Information, saying the company was back to the drawing board on its assumptions.0.99
    18. Uber's total research and development spend reached $3.4 billion in 2025, up 9% year1.00
    19. over year, which makes the budget collapse less about scale and more about a pricing0.99
    20. model that enterprise finance teams have not learned how to manage.0.99
    21. The disclosure landed alongside a structural shift from Anthropic itself. On May 13, the0.99
    22. company announced that paying Claude subscribers would soon face a separate monthly1.00
    23. credit meter for agent tools and third-party harnesses, billed at full application1.00
    24. programming interface rates starting June 15. Read together, the two events describe a0.99
    25. single problem. Token-based consumption pricing does not behave like the software line0.99
    26. items chief financial officers know how to model, and the gap between what engineers0.99
    27. consume and what finance teams expect is no longer hypothetical.0.99
    28. TRACK 8· JULY 2, 20260.94
    29. World'sFair0.97
    30. Agentic Engineering1.00
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    1. AlEngineer0.97
    2. World'sFair1.00
    3. VERIFICATION & QUALITY GATES1.00
    4. tests·type-check·build·code review·Cl1.00
    5. TOOLS1.00
    6. MCP·terminal ·file edits·browser0.98
    7. 0.99
    8. CONTEXT1.00
    9. rules·skills·memory·docs1.00
    10. Model1.00
    11. TRACK 8• JULY 2, 20260.95
    12. World's Fair0.96
    13. Agentic Engineering1.00
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    1. AlEngineer0.98
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    3. Fixing the same bug. Half the cost.0.99
    4. GLM-5.21.00
    5. $0.411.00
    6. builds clean1.00
    7. Opus 4.81.00
    8. $0.811.00
    9. × breaks the build0.95
    10. TRACK 8• JULY 2, 20260.95
    11. World's Fair0.97
    12. Agentic Engineering1.00
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    shot 23·duplicate of #22

Transcript

130 cues· 2,729 words· 15,352 chars

  1. 0:12 Hi, I am Saud, founder of Klein.
  2. 0:19 I started Klein as an open source project a few years ago.
  3. 0:24 Some of you might know it as the first ever coding agent back before the Cloud Mac subscription and the Codex subscriptions when people had to pay for each and every API request.
  4. 0:35 which got extremely expensive.
  5. 0:38 This was before prompt caching became a thing.
  6. 0:40 And so there were people that paid hundreds of dollars a day using Klein.
  7. 0:47 But for a lot of people, it was their first AGI moment.
  8. 0:50 It was the first time they saw LLMs be able to do their jobs end to end.
  9. 0:55 And they got hooked.
  10. 0:57 And I don't think Client would have been as successful as it is if it wasn't open source because it allowed these developers to inspector code and trust it and connect to any API so they could be comfortable with spending so much money on it and know that they weren't getting screwed over.
  11. 1:18 And we were the first to add things like custom rules and plan mode.
  12. 1:22 And a lot of that came from talking to and learning from this really incredible open source community we had around the project.
  13. 1:28 And so, you know, having spent most of my life building open source, it's really heartbreaking to see just like the broader open source community wither and die over the last two years because of how AI has fundamentally changed everything about software development.
  14. 1:46 GitHub is effectively an archive of slop PRs and issues and security reports, where the sense of community before has turned into this deep skepticism and distrust of each other's responsible use of these tools.
  15. 2:03 Because AI coding can be extremely dangerous to a project, and everyone's kind of had to learn that on the fly, but especially open source projects that rely on trusting third parties.
  16. 2:15 I wanted to share some examples of how open source has been dealing with AI.
  17. 2:22 This is the code of conduct for Zig, which is the language that powers Bunn.
  18. 2:30 They essentially ban all use of AI.
  19. 2:31 You can't use it on pull requests or issues or even comments.
  20. 2:37 The reason for this is that, to them, the core Zig team
  21. 2:43 They value contributors more than they do the contributions.
  22. 2:47 And so the primary goal for reviewing PRs and things isn't to add new code, but it's to help grow new contributors who can become trusted over time.
  23. 2:55 And AI assistance completely breaks that.
  24. 3:00 This is a post from the CEO of Curl, who says that his project is effectively being DDoSed by AI-generated bug reports, and they're even considering shutting down their bug bounty program for the first time in decades.
  25. 3:18 And this is TL Draw.
  26. 3:22 automatically just closing all pull requests, whether they're AI-generated or not.
  27. 3:27 And it's gone so bad that GitHub added a feature to disable third-party pull requests altogether, which is really sad, because pull requests were the thing that made GitHub what it is today, and we're probably gonna see a lot of big open-source projects opt into this.
  28. 3:45 And so when I say that open source is dead, I mean some parts of it, like the community.
  29. 3:52 It's just not worth cultivating anymore, especially because building software is so cheap.
  30. 3:58 And also the risk of supply chain attacks.
  31. 4:01 I'm sure you've seen all the reports of things getting compromised.
  32. 4:05 It's become more dangerous than ever to depend on third-party software, where it takes a single compromise and a massive chain of contributors to get pwned.
  33. 4:14 So just as an example, LiteLLM is a Python package.
  34. 4:20 It gets like three and a half million downloads a day.
  35. 4:23 They were compromised for three hours where attackers used a GitHub app that they used to steal their PyPI publishing tokens and publish a compromised version of the package that would install a credential harvester that would steal your API keys, your SSH keys, your crypto keys,
  36. 4:44 and also install a backdoor that lets them do remote command execution.
  37. 4:49 And the only reason this was even caught as quickly as it was was just pure luck.
  38. 4:54 Because the malware had a bug in it where it would cause cursor to crash if you ran the light LLM MCP server.
  39. 5:02 And a security researcher noticed that and
  40. 5:06 was able to figure it out, but if this had been out any longer, it would have caused catastrophic damage, especially because a lot of the people using LightLLM are the enterprise customers and developers that have their own internal gateways.
  41. 5:23 But despite all of this, I believe there are some parts of open source that are sticking around and becoming more important, like allowing others to use your thing freely in the public domain and build on top of.
  42. 5:36 And those parts about it are gonna become more important than ever, particularly with open weights models because of the economic impact.
  43. 5:43 And so to help explain why, I wanna look at what's happening with inference spend right now.
  44. 5:48 So this is a report from
  45. 5:51 An anonymous report from a CFO at an unnamed company where they accidentally spent $500 million on Claude in a single month because they didn't set the usage limits on their thousands of employees on their anthropic dashboard.
  46. 6:06 This is another report by Uber CTO where after they rolled Cloud out to their organization, 95% of their engineers were using it, 70% of their committed code came from Cloud, and their monthly spend per user was up to $2,000, and they said they used their entire 2026 budget in just four months.
  47. 6:27 And the crazy part is that the AI labs are losing money too.
  48. 6:32 This is a chart from Semi Analysis where they ran experiments with Cloud, Code, and Codex subscriptions where they would give them long horizon coding tasks until they exhausted their weekly limits.
  49. 6:42 And they found that a $200 plan for Cloud would give them about $8,000 worth of API usage and a $200 subscription to Codex would give them about $14,000 worth of API usage.
  50. 6:56 So I think the strategy is pretty obvious.

Chapters

  1. 0:00 Introduction to Cline and the early open source coding agent era.
  2. 1:30 The decline of the open source community and the rise of AI-driven distrust.
  3. 2:22 How projects like Zig, curl, and tldraw are responding to AI-generated noise.
  4. 3:45 Systemic risks: The litellm supply chain compromise example.
  5. 5:22 The economic case for the survival of "open weights" models.
  6. 5:49 Real-world impact: Corporate AI spending and infrastructure lock-in.
  7. 8:50 Comparing model intelligence vs. system-level AI verification (GLM vs. Opus).
  8. 10:57 The Open Compute precedent: How open standards commoditize the industry.
  9. 12:36 Future projections for AI inference costs and hardware capacity.
  10. 14:22 A call to action for American labs regarding open weights models.
  11. 16:01 Cline's shift to an open weights subscription model.

Open at this second