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Videos zgNvts_2TUE

State of the Claw — Peter Steinberger

index_state ready data_status ok

AI Engineer· published 2026-04-17· 0:44:12· en-US· indexed 2026-08-10 19:45

Open on YouTube

Scene timeline

  1. Shot 0, 0:00 to 0:05, 1 of 1 keyframes kept
  2. Shot 1, 0:05 to 0:09, 1 of 1 keyframes kept
  3. Shot 2, 0:09 to 0:15, 1 of 1 keyframes kept
  4. Shot 3, 0:15 to 0:31, 1 of 1 keyframes kept
  5. Shot 4, 0:31 to 0:34, 1 of 1 keyframes kept
  6. Shot 5, 0:34 to 0:42, 1 of 1 keyframes kept
  7. Shot 6, 0:42 to 0:49, 1 of 1 keyframes kept
  8. Shot 7, 0:49 to 0:51, 1 of 1 keyframes kept
  9. Shot 8, 0:51 to 0:53, 1 of 1 keyframes kept
  10. Shot 9, 0:53 to 0:58, 1 of 1 keyframes kept
  11. Shot 10, 0:58 to 1:00, 1 of 1 keyframes kept
  12. Shot 11, 1:00 to 1:02, 1 of 1 keyframes kept
  13. Shot 12, 1:02 to 1:03, 1 of 1 keyframes kept
  14. Shot 13, 1:03 to 1:49, 1 of 1 keyframes kept
  15. Shot 14, 1:49 to 2:21, 1 of 1 keyframes kept
  16. Shot 15, 2:21 to 2:52, 1 of 1 keyframes kept
  17. Shot 16, 2:52 to 3:18, 1 of 1 keyframes kept
  18. Shot 17, 3:18 to 3:43, 1 of 1 keyframes kept
  19. Shot 18, 3:43 to 3:49, 1 of 1 keyframes kept
  20. Shot 19, 3:49 to 3:54, 0 of 1 keyframes kept
  21. Shot 20, 3:54 to 4:00, 1 of 1 keyframes kept
  22. Shot 21, 4:00 to 4:03, 1 of 1 keyframes kept
  23. Shot 22, 4:03 to 4:07, 1 of 1 keyframes kept
  24. Shot 23, 4:07 to 4:11, 1 of 1 keyframes kept
  25. Shot 24, 4:11 to 4:14, 0 of 1 keyframes kept
  26. Shot 25, 4:14 to 4:44, 1 of 1 keyframes kept
  27. Shot 26, 4:44 to 5:15, 1 of 1 keyframes kept
  28. Shot 27, 5:15 to 5:25, 1 of 1 keyframes kept
  29. Shot 28, 5:25 to 5:49, 1 of 1 keyframes kept
  30. Shot 29, 5:49 to 6:22, 1 of 1 keyframes kept
  31. Shot 30, 6:22 to 6:25, 1 of 1 keyframes kept
  32. Shot 31, 6:25 to 6:32, 1 of 1 keyframes kept
  33. Shot 32, 6:32 to 6:38, 1 of 1 keyframes kept
  34. Shot 33, 6:38 to 6:49, 1 of 1 keyframes kept
  35. Shot 34, 6:49 to 7:06, 1 of 1 keyframes kept
  36. Shot 35, 7:06 to 7:21, 1 of 1 keyframes kept
  37. Shot 36, 7:21 to 7:27, 1 of 1 keyframes kept
  38. Shot 37, 7:27 to 7:47, 1 of 1 keyframes kept
  39. Shot 38, 7:47 to 7:59, 1 of 1 keyframes kept
  40. Shot 39, 7:59 to 8:05, 0 of 1 keyframes kept
  41. Shot 40, 8:05 to 8:28, 1 of 1 keyframes kept
  42. Shot 41, 8:28 to 8:30, 0 of 1 keyframes kept
  43. Shot 42, 8:30 to 8:42, 1 of 1 keyframes kept
  44. Shot 43, 8:42 to 9:14, 1 of 1 keyframes kept
  45. Shot 44, 9:14 to 9:47, 1 of 1 keyframes kept
  46. Shot 45, 9:47 to 9:56, 1 of 1 keyframes kept
  47. Shot 46, 9:56 to 10:03, 1 of 1 keyframes kept
  48. Shot 47, 10:03 to 10:13, 1 of 1 keyframes kept
  49. Shot 48, 10:13 to 10:32, 1 of 1 keyframes kept
  50. Shot 49, 10:32 to 10:53, 1 of 1 keyframes kept
  51. Shot 50, 10:53 to 11:01, 1 of 1 keyframes kept
  52. Shot 51, 11:01 to 11:08, 0 of 1 keyframes kept
  53. Shot 52, 11:08 to 11:09, 1 of 1 keyframes kept
  54. Shot 53, 11:09 to 11:15, 1 of 1 keyframes kept
  55. Shot 54, 11:15 to 11:22, 1 of 1 keyframes kept
  56. Shot 55, 11:22 to 11:36, 1 of 1 keyframes kept
  57. Shot 56, 11:36 to 11:47, 1 of 1 keyframes kept
  58. Shot 57, 11:47 to 12:24, 1 of 1 keyframes kept
  59. Shot 58, 12:24 to 12:31, 1 of 1 keyframes kept
  60. Shot 59, 12:31 to 12:49, 1 of 1 keyframes kept
  61. Shot 60, 12:49 to 12:58, 1 of 1 keyframes kept
  62. Shot 61, 12:58 to 13:02, 1 of 1 keyframes kept
  63. Shot 62, 13:02 to 13:24, 1 of 1 keyframes kept
  64. Shot 63, 13:24 to 13:30, 1 of 1 keyframes kept
  65. Shot 64, 13:30 to 13:42, 1 of 1 keyframes kept
  66. Shot 65, 13:42 to 14:01, 1 of 1 keyframes kept
  67. Shot 66, 14:01 to 14:20, 1 of 1 keyframes kept
  68. Shot 67, 14:20 to 14:22, 1 of 1 keyframes kept
  69. Shot 68, 14:22 to 14:37, 1 of 1 keyframes kept
  70. Shot 69, 14:37 to 14:43, 1 of 1 keyframes kept
  71. Shot 70, 14:43 to 14:47, 1 of 1 keyframes kept
  72. Shot 71, 14:47 to 14:52, 1 of 1 keyframes kept
  73. Shot 72, 14:52 to 15:02, 1 of 1 keyframes kept
  74. Shot 73, 15:02 to 15:33, 1 of 1 keyframes kept
  75. Shot 74, 15:33 to 15:38, 1 of 1 keyframes kept
  76. Shot 75, 15:38 to 15:49, 1 of 1 keyframes kept
  77. Shot 76, 15:49 to 16:06, 1 of 1 keyframes kept
  78. Shot 77, 16:06 to 16:11, 1 of 1 keyframes kept
  79. Shot 78, 16:11 to 16:31, 0 of 1 keyframes kept
  80. Shot 79, 16:31 to 16:51, 0 of 1 keyframes kept
  81. Shot 80, 16:51 to 17:05, 1 of 1 keyframes kept
  82. Shot 81, 17:05 to 17:15, 1 of 1 keyframes kept
  83. Shot 82, 17:15 to 17:23, 1 of 1 keyframes kept
  84. Shot 83, 17:23 to 17:33, 0 of 1 keyframes kept
  85. Shot 84, 17:33 to 17:44, 1 of 1 keyframes kept
  86. Shot 85, 17:44 to 17:45, 1 of 1 keyframes kept
  87. Shot 86, 17:45 to 17:48, 1 of 1 keyframes kept
  88. Shot 87, 17:48 to 17:53, 1 of 1 keyframes kept
  89. Shot 88, 17:53 to 17:59, 1 of 1 keyframes kept
  90. Shot 89, 17:59 to 18:05, 1 of 1 keyframes kept
  91. Shot 90, 18:05 to 18:30, 1 of 1 keyframes kept
  92. Shot 91, 18:30 to 18:32, 1 of 1 keyframes kept
  93. Shot 92, 18:32 to 18:54, 1 of 1 keyframes kept
  94. Shot 93, 18:54 to 18:59, 1 of 1 keyframes kept
  95. Shot 94, 18:59 to 19:09, 1 of 1 keyframes kept
  96. Shot 95, 19:09 to 19:13, 1 of 1 keyframes kept
  97. Shot 96, 19:13 to 19:48, 1 of 1 keyframes kept
  98. Shot 97, 19:48 to 20:08, 1 of 1 keyframes kept
  99. Shot 98, 20:08 to 20:09, 1 of 1 keyframes kept
  100. Shot 99, 20:09 to 20:42, 1 of 1 keyframes kept
  101. Shot 100, 20:42 to 21:00, 0 of 1 keyframes kept
  102. Shot 101, 21:00 to 21:45, 0 of 1 keyframes kept
  103. Shot 102, 21:45 to 22:19, 1 of 1 keyframes kept
  104. Shot 103, 22:19 to 22:50, 1 of 1 keyframes kept
  105. Shot 104, 22:50 to 23:16, 1 of 1 keyframes kept
  106. Shot 105, 23:16 to 23:42, 1 of 1 keyframes kept
  107. Shot 106, 23:42 to 24:08, 1 of 1 keyframes kept
  108. Shot 107, 24:08 to 24:19, 1 of 1 keyframes kept
  109. Shot 108, 24:19 to 24:57, 1 of 1 keyframes kept
  110. Shot 109, 24:57 to 25:28, 1 of 1 keyframes kept
  111. Shot 110, 25:28 to 25:45, 0 of 1 keyframes kept
  112. Shot 111, 25:45 to 25:47, 0 of 1 keyframes kept
  113. Shot 112, 25:47 to 25:48, 1 of 1 keyframes kept
  114. Shot 113, 25:48 to 25:51, 0 of 1 keyframes kept
  115. Shot 114, 25:51 to 26:07, 0 of 1 keyframes kept
  116. Shot 115, 26:07 to 26:12, 1 of 1 keyframes kept
  117. Shot 116, 26:12 to 26:26, 1 of 1 keyframes kept
  118. Shot 117, 26:26 to 27:06, 1 of 1 keyframes kept
  119. Shot 118, 27:06 to 27:22, 1 of 1 keyframes kept
  120. Shot 119, 27:22 to 27:56, 1 of 1 keyframes kept
  121. Shot 120, 27:56 to 28:30, 1 of 1 keyframes kept
  122. Shot 121, 28:30 to 28:40, 1 of 1 keyframes kept
  123. Shot 122, 28:40 to 28:55, 1 of 1 keyframes kept
  124. Shot 123, 28:55 to 29:24, 1 of 1 keyframes kept
  125. Shot 124, 29:24 to 29:42, 1 of 1 keyframes kept
  126. Shot 125, 29:42 to 29:54, 1 of 1 keyframes kept
  127. Shot 126, 29:54 to 30:15, 1 of 1 keyframes kept
  128. Shot 127, 30:15 to 30:39, 1 of 1 keyframes kept
  129. Shot 128, 30:39 to 31:08, 1 of 1 keyframes kept
  130. Shot 129, 31:08 to 31:41, 1 of 1 keyframes kept
  131. Shot 130, 31:41 to 31:58, 1 of 1 keyframes kept
  132. Shot 131, 31:58 to 32:04, 1 of 1 keyframes kept
  133. Shot 132, 32:04 to 32:33, 1 of 1 keyframes kept
  134. Shot 133, 32:33 to 33:01, 1 of 1 keyframes kept
  135. Shot 134, 33:01 to 33:28, 1 of 1 keyframes kept
  136. Shot 135, 33:28 to 33:40, 1 of 1 keyframes kept
  137. Shot 136, 33:40 to 33:50, 1 of 1 keyframes kept
  138. Shot 137, 33:50 to 34:18, 1 of 1 keyframes kept
  139. Shot 138, 34:18 to 34:45, 1 of 1 keyframes kept
  140. Shot 139, 34:45 to 35:14, 1 of 1 keyframes kept
  141. Shot 140, 35:14 to 35:24, 1 of 1 keyframes kept
  142. Shot 141, 35:24 to 35:49, 1 of 1 keyframes kept
  143. Shot 142, 35:49 to 36:20, 1 of 1 keyframes kept
  144. Shot 143, 36:20 to 36:56, 1 of 1 keyframes kept
  145. Shot 144, 36:56 to 37:32, 1 of 1 keyframes kept
  146. Shot 145, 37:32 to 37:51, 1 of 1 keyframes kept
  147. Shot 146, 37:51 to 38:22, 1 of 1 keyframes kept
  148. Shot 147, 38:22 to 38:47, 1 of 1 keyframes kept
  149. Shot 148, 38:47 to 39:33, 1 of 1 keyframes kept
  150. Shot 149, 39:33 to 39:55, 1 of 1 keyframes kept
  151. Shot 150, 39:55 to 40:23, 1 of 1 keyframes kept
  152. Shot 151, 40:23 to 40:37, 1 of 1 keyframes kept
  153. Shot 152, 40:37 to 41:11, 1 of 1 keyframes kept
  154. Shot 153, 41:11 to 41:35, 1 of 1 keyframes kept
  155. Shot 154, 41:35 to 41:52, 1 of 1 keyframes kept
  156. Shot 155, 41:52 to 42:40, 1 of 1 keyframes kept
  157. Shot 156, 42:40 to 42:46, 0 of 1 keyframes kept
  158. Shot 157, 42:46 to 42:47, 0 of 1 keyframes kept
  159. Shot 158, 42:47 to 43:21, 1 of 1 keyframes kept
  160. Shot 159, 43:21 to 43:55, 1 of 1 keyframes kept
  161. Shot 160, 43:55 to 43:57, 0 of 1 keyframes kept
  162. Shot 161, 43:57 to 44:11, 1 of 1 keyframes kept

162 shot(s).

keyframes kept every frame deduplicated

What was stored

cues
568
whisperx 568
chunks
80
from 568 cues
keyframes
145
kept of 162 captured
frames with text
145
4,828 lines read
chapters
16
from the source metadata
keyframe bytes
21.2 MB
word timings on 568 cues

Provenance

Each pipeline stage, its state and the model that produced it
stage state model started took
fetch done 2026-08-10 01:09 2m 46s
stt done 2026-08-10 01:12 43s
chunk done 2026-08-10 01:13 0s
text_embed done 2026-08-10 19:45 1s
keyframe done 2026-08-10 01:13 4m 27s
ocr done 2026-08-10 01:17 1m 23s
frame_embed done 2026-08-10 19:45 26s

Frames, and what the machine read

  • 0:02 #0 done2 line(s)

    shot 0·sharpness 666.1

    1. AlEngineer0.98
    2. EUROPE1.00
  • 0:06 #1 done2 line(s)

    shot 1·sharpness 822.7

    1. PRESENTING SPONSOR0.97
    2. Google DeepMind1.00
  • 0:11 #2 done3 line(s)

    shot 2·sharpness 939.5

    1. PLATINUM SPONSORS0.98
    2. # Braintrust0.96
    3. WorkOS OpenAI0.96
  • 0:29 #3 done6 line(s)

    shot 3·sharpness 426.0

    1. AlEngineer0.97
    2. AlEngineer0.98
    3. OperClaw1.00
    4. EUROPE1.00
    5. EUROPE1.00
    6. AIF0.97
  • 0:32 #4 done3 line(s)

    shot 4·sharpness 932.3

    1. PETER1.00
    2. STEINBERGER1.00
    3. OpenClaw1.00
  • 0:35 #5 done4 line(s)

    shot 5·sharpness 794.2

    1. PETER1.00
    2. STEINBERGER1.00
    3. AIE1.00
    4. AIE1.00
  • 0:48 #6 done28 line(s)

    shot 6·sharpness 888.2

    1. AlEngineer0.96
    2. EUROPE1.00
    3. AIEngineer0.98
    4. together.ai0.98
    5. AlEngineer0.99
    6. EUROPE1.00
    7. EUROPE1.00
    8. :tailscale0.96
    9. SA0.98
    10. qineer0.98
    11. Braintrust1.00
    12. AlEngineer0.98
    13. IN-0.98
    14. EUROPE1.00
    15. AlEngineer0.96
    16. Microsoft1.00
    17. EUROPE1.00
    18. AlEngineer0.97
    19. EUROPE1.00
    20. er0.97
    21. Trigger.dev1.00
    22. AlEngineer0.96
    23. Google DeepMind0.98
    24. EUROPE1.00
    25. 1al0.78
    26. AlEngineer0.99
    27. tailscale1.00
    28. EUROPE1.00
  • 0:51 #7 done28 line(s)

    shot 7·sharpness 1003.9

    1. EUROPE1.00
    2. together.ai0.98
    3. AlEngineer0.98
    4. BLUMOPE0.75
    5. AlEngineer0.96
    6. Braintr1.00
    7. AIEngineer0.96
    8. Google DeepMind1.00
    9. EUROPE0.89
    10. arize1.00
    11. AIEngi0.88
    12. Microsoft1.00
    13. AlEngineer0.99
    14. BUROPE0.94
    15. Engineer1.00
    16. EUROPE0.99
    17. RESENTED BY0.98
    18. AIEngineer0.95
    19. Trigger.0.97
    20. Engineer1.00
    21. WorkOS1.00
    22. gle DeepMind1.00
    23. EUMOPE0.81
    24. Modal1.00
    25. AIEnginee0.95
    26. tailscale1.00
    27. AlEngineer0.98
    28. BUROPE0.79
  • 0:52 #8 done38 line(s)

    shot 8·sharpness 1160.6

    1. EUROPE1.00
    2. together.ai1.00
    3. AlEngineer0.98
    4. EUROPE1.00
    5. AlEngineer0.99
    6. Braintrust1.00
    7. ngineer1.00
    8. Google DeepMind1.00
    9. AlEngin0.89
    10. EUROPE1.00
    11. ROPE1.00
    12. EUROP1.00
    13. arize1.00
    14. AlEngineer0.98
    15. crosoft1.00
    16. AlEngineer0.96
    17. nec0.87
    18. EUROPE1.00
    19. EUROPE1.00
    20. neer1.00
    21. E1.00
    22. ED BY1.00
    23. AlEngineer0.98
    24. △Trigger.de0.94
    25. Engineer1.00
    26. WorkOS0.99
    27. AIEngir0.90
    28. eepMind0.96
    29. EUROPE1.00
    30. EUROPE1.00
    31. EUROPE0.96
    32. Modal1.00
    33. AlEngineer0.98
    34. tailscale1.00
    35. AlEngineer0.96
    36. So0.92
    37. EUROPE1.00
    38. EUROPE1.00
  • 0:56 #9 done30 line(s)

    shot 9·sharpness 1032.5

    1. AIEngineer0.95
    2. WorkOS1.00
    3. AlEngineer0.99
    4. EUROPE1.00
    5. EUROPE1.00
    6. SAFE1.00
    7. AlEngi0.83
    8. Braintrust1.00
    9. AlEngineer0.99
    10. Goo0.85
    11. INTELLIGENCE1.00
    12. El0.65
    13. EUROPE1.00
    14. AlEngineer0.96
    15. Microsoft1.00
    16. EUROPE1.00
    17. AlEngineer0.96
    18. EUROPE1.00
    19. PRESENTED BY1.00
    20. AlEng0.94
    21. Trigger.dev1.00
    22. AlEngineer0.97
    23. Google DeepMind1.00
    24. 1/ 290.92
    25. EURO1.00
    26. EUROPE1.00
    27. NJa0.91
    28. AlEngineer0.96
    29. tailscale1.00
    30. EUROPE1.00
  • 0:59 #10 done37 line(s)

    shot 10·sharpness 1203.3

    1. EUROPE1.00
    2. ineer0.98
    3. WorkOS0.99
    4. AlEngineer0.98
    5. PE0.97
    6. EUROPE1.00
    7. FE1.00
    8. AlEngineer0.97
    9. Braintr'0.94
    10. AlEngineer0.95
    11. Google DeepMind1.00
    12. LIGENCE1.00
    13. EUROPE1.00
    14. EUROPE1.00
    15. arize1.00
    16. AIEng0.92
    17. r0.91
    18. Microsoft1.00
    19. AlEngineer0.98
    20. EUROPE1.00
    21. EUROPE1.00
    22. AlEngineer1.00
    23. EUROPE1.00
    24. PRESENTED BY0.97
    25. AIEngineer0.95
    26. △Trigge0.91
    27. AlEngineer0.98
    28. WorkOS1.00
    29. ogle DeepMind1.00
    30. EUROPE1.00
    31. EUROPE1.00
    32. Modal1.00
    33. AIEngir0.93
    34. tailscale1.00
    35. AlEngineer0.97
    36. EUROP1.00
    37. EUROPE1.00
  • 1:01 #11 done31 line(s)

    shot 11·sharpness 1021.1

    1. EUROPE1.00
    2. WEngineer0.94
    3. WorkOS0.95
    4. AlEngineer0.99
    5. EUMOPE0.90
    6. SAFE1.00
    7. AlEngineer0.99
    8. intrust1.00
    9. AlEngineer0.96
    10. Google DeepMin1.00
    11. INTELLIGENCE1.00
    12. EUBOPE0.92
    13. EUROPE0.99
    14. arize1.00
    15. Microsoft1.00
    16. AlEngineer0.98
    17. EUROPE0.96
    18. AlEngineer0.98
    19. EUROPE1.00
    20. PRESENTED BY1.00
    21. AlEngineer0.96
    22. er.dev1.00
    23. AlEngineer0.97
    24. WorkOS1.00
    25. Google DeepMind0.99
    26. EUROPE0.99
    27. EUMOPE0.89
    28. Modal1.00
    29. tailscale1.00
    30. AlEngineer0.96
    31. EUROPE0.97
  • 1:02 #12 done29 line(s)

    shot 12·sharpness 921.9

    1. AIEngineer0.97
    2. WorkOS0.98
    3. AlEngineer0.98
    4. EUROPE1.00
    5. EUROPE1.00
    6. SAFE1.00
    7. ineer0.97
    8. Braintrust1.00
    9. AlEngineer0.98
    10. INTELLIGENCE1.00
    11. EUROPE1.00
    12. ze1.00
    13. AlEngineer0.97
    14. Microsoft1.00
    15. EUROPE1.00
    16. AlEngineer0.99
    17. EUROPE1.00
    18. PRESENTED BY1.00
    19. jineer1.00
    20. Trigger.dev1.00
    21. AlEngineer0.97
    22. Google DeepMind1.00
    23. 1/ 290.93
    24. ROPE1.00
    25. EUROPE1.00
    26. Modal1.00
    27. AlEngineer0.96
    28. tailscale1.00
    29. EUROPE1.00
  • 1:26 #13 done34 line(s)

    shot 13·sharpness 1445.5

    1. State of the0.99
    2. Clawdbot-0×openclaw b ×Security- 0 ×0.89
    3. Waring: Cr0.93
    4. NVIDIA/Nem ×Security Ad×0.91
    5. YClawHub0.94
    6. codex yolo0.99
    7. Claude Coc0.98
    8. eer1.00
    9. Fie /Users/steipete/obsidian/state-of-the-claw-slides.html0.99
    10. a0.71
    11. O0.56
    12. trus1.00
    13. VEngineer0.98
    14. EUROPE1.00
    15. neer1.00
    16. Microsoft1.00
    17. // 010.93
    18. Five Months,1.00
    19. er.de1.00
    20. Engineer1.00
    21. One Lobster0.99
    22. EUROPE1.00
    23. From first commit to the fastest-growing project in0.98
    24. GitHub history.1.00
    25. neer1.00
    26. ailscale1.00
    27. 2 / 290.84
    28. AlEngineer0.98
    29. OPENCLAW UPDATE1.00
    30. EUROPE1.00
    31. PRESENTED BY1.00
    32. OpenClaw1.00
    33. Google DeepMind1.00
    34. PETER STEINBERGER / Creator0.99
  • 2:11 #14 done54 line(s)

    shot 14·sharpness 1593.8

    1. State of the1.00
    2. Clawdbot-0 ×0.92
    3. openclaw bi x0.89
    4. Security - 0 ×0.84
    5. Waming: Cri x0.86
    6. openshell ×0.92
    7. NVIDIA/Ne ×0.87
    8. Security Ad×0.99
    9. ClawHub1.00
    10. The lethal t0.98
    11. codex yolo0.99
    12. Claude Cod:0.96
    13. Fie /Users/steipete/obsidian/state-of-the-claw-slides.html0.98
    14. ngineer0.99
    15. WorkOS0.98
    16. UROPE1.00
    17. AlEngineer0.95
    18. EUROPE1.00
    19. Commit velbcity: the ramp1.00
    20. arize1.00
    21. 8,7100.98
    22. 7,0060.99
    23. AlEngineer0.99
    24. 6,1171.00
    25. 5,076*0.99
    26. EUROPE1.00
    27. PRESENTED BY1.00
    28. AlEngineer0.97
    29. Google DeepMind0.99
    30. EUROPE1.00
    31. 2,1511.00
    32. 2881.00
    33. Modal1.00
    34. 20251.00
    35. Nov1.00
    36. 20251.00
    37. Dec1.00
    38. 20261.00
    39. Jan1.00
    40. 20261.00
    41. Feb1.00
    42. 20261.00
    43. Mar1.00
    44. 9 days in1.00
    45. Apr1.00
    46. openclaw.ai0.98
    47. 4/290.92
    48. AlEngineer0.97
    49. OPENCLAW UPDATE1.00
    50. EUROPE1.00
    51. PRESENTED BY1.00
    52. OpenClaw1.00
    53. Google DeepMind1.00
    54. PETER STEINBERGER / Creator0.99
  • 2:24 #15 done35 line(s)

    shot 15·sharpness 1533.5

    1. State of the1.00
    2. Clawdbot-0×openclaw bl ×Security- 0×Waming:Cri ×0.87
    3. openshell m ×NVIDIA/Nem ×Security Ad × ClawHub0.87
    4. The lethal t0.97
    5. codex yolo0.99
    6. Claude Cod0.98
    7. Fie /Users/steipete/obsidian/state-of-the-claw-slides.html0.97
    8. Engineer1.00
    9. WorkC0.99
    10. EUROPE1.00
    11. SAFE1.00
    12. AlEngineer0.99
    13. NTELLIGENCE1.00
    14. EUROPE1.00
    15. 40.72
    16. arize0.99
    17. 1/ 020.76
    18. AlEngineer0.98
    19. The Maintainer1.00
    20. EUROPE1.00
    21. PRESENTED BY1.00
    22. AlEngineer0.96
    23. Problem1.00
    24. Google DeepMind1.00
    25. EUROPE1.00
    26. Growing a maintainer team at the speed of an Al project.0.99
    27. Mod1.00
    28. 5/ 290.88
    29. AlEngineer0.99
    30. OPENCLAW UPDATE1.00
    31. EUROPE1.00
    32. PRESENTED BY1.00
    33. Google DeepMind1.00
    34. PETER STEINBERGER / Creator0.99
    35. OpenClaw1.00
  • 3:15 #16 done39 line(s)

    shot 16·sharpness 2607.8

    1. State of the0.99
    2. Clawdbot-D×openclaw bi ×0.88
    3. Security -0 ×0.84
    4. NVIDIA/Nem ×Security Ad ×0.88
    5. ClawHub1.00
    6. The lethal t0.99
    7. codex yolo0.99
    8. Claude Cocd0.87
    9. AlEngine0.98
    10. Fe /Users/steipete/obsidian/state-of-the-claw-slides.html0.98
    11. O0.58
    12. EUROPE1.00
    13. Open1.00
    14. Who showed up to maintain a lobster0.98
    15. NVIDIA — security ops, infra hardening, HPC/RAG expertise0.99
    16. AlEngine0.94
    17. Microsoft — Windows node, A365 integration, M365 Copilot DevEx0.99
    18. EUROPE1.00
    19. Red Hat — Kubernetes, OpenShift, connecting us with the vLLM team0.98
    20. AlEngineer0.99
    21. Tencent & ByteDance — local model benchmarks, inference optimization, CJK0.99
    22. EUROPE1.00
    23. SEN1.00
    24. ecosystem1.00
    25. OsS veterans — creators of Jest, Yarn, Pl, and other foundational tools0.97
    26. PRESENTED BY1.00
    27. Google DeepMind1.00
    28. Worldwide community — builders from Brazil, India, Taiwan, Vietnam, Israel, China,0.99
    29. Belgium, Austria...0.99
    30. AlEngin0.99
    31. EUROPE1.00
    32. 7 / 290.82
    33. AlEngineer0.98
    34. OPENCLAW UPDATE1.00
    35. EUROPE1.00
    36. PRESENTED BY1.00
    37. Google DeepMind1.00
    38. PETER STEINBERGER / Creator1.00
    39. OpenClaw1.00
  • 3:33 #17 done34 line(s)

    shot 17·sharpness 2537.6

    1. UROPE0.99
    2. State of the0.95
    3. NVIDIA/Nem×0.95
    4. Security Ad×0.97
    5. ClawHub1.00
    6. codex yolo0.99
    7. Claude Codi:0.91
    8. Fie /Users/steipete/obsidian/state-of-the-claw-slides.html0.99
    9. Work0.99
    10. AlEngineer0.98
    11. EUROPE1.00
    12. Who showed up to maintain a lobster1.00
    13. NVIDIA — security ops, infra hardening, HPC/RAG expertise0.99
    14. AIEI0.90
    15. Microso0.91
    16. Microsoft — Windows node, A365 integration, M365 Copilot DevEx0.99
    17. Red Hat — Kubernetes, OpenShift, connecting us with the vLLM team0.98
    18. AlEngineer0.99
    19. Tencent & ByteDance — local model benchmarks, inference optimization, CJK0.99
    20. EUROPE0.99
    21. ecosystem1.00
    22. PRESENTED BY1.00
    23. OsS veterans — creators of Jest, Yarn, Pl, and other foundational tools0.97
    24. Google DeepM1.00
    25. Worldwide community — builders from Brazil, India, Taiwan, Vietnam, Israel, China,0.99
    26. Belgium,Austria...1.00
    27. 7 / 290.85
    28. AlEngineer0.97
    29. OPENCLAW UPDATE1.00
    30. EUROPE1.00
    31. PRESENTED BY1.00
    32. Google DeepMind1.00
    33. PETER STEINBERGER / Creator0.99
    34. OpenClaw1.00
  • 3:48 #18 done31 line(s)

    shot 18·sharpness 1450.5

    1. State of the0.99
    2. Warming: Cx0.87
    3. NVIDIA/Nem ×Security Ad×0.90
    4. ClawHub1.00
    5. codex yolo1.00
    6. Claude Cod0.95
    7. NE0.97
    8. Fie /Users/steipete/obsidian/state-of-the-claw-slides.html0.98
    9. <>0.68
    10. Open0.97
    11. 40.85
    12. 1/ 030.87
    13. AIEng0.90
    14. The Security1.00
    15. DDoS1.00
    16. AlEngineer0.98
    17. EUROPE1.00
    18. Te1.00
    19. 1,142 security advisories in 69 days. This is what the0.99
    20. future of open source looks like.1.00
    21. PRESENTED BY1.00
    22. Google DeepMind0.97
    23. AlEngi0.83
    24. 8 / 290.85
    25. AlEngineer0.98
    26. OPENCLAW UPDATE1.00
    27. EUROPE1.00
    28. PRESENTED BY1.00
    29. Google DeepMind1.00
    30. PETER STEINBERGER / Creator0.99
    31. OpenClaw1.00
  • 3:52 #19 skipped

    shot 19·duplicate of #15

  • 3:57 #20 done32 line(s)

    shot 20·sharpness 1482.3

    1. State of the1.00
    2. Clawdbot-O0.94
    3. Security - 0 x0.86
    4. openshell m ×NVIDIA/Nem × Security Ad ×0.85
    5. ClawHub0.99
    6. The lethal t0.96
    7. codex yolo0.98
    8. Claude Coc0.96
    9. AIEngineer0.96
    10. Wo0.98
    11. p.kagi.com/proxy/openclaw%20blog%20hero%20banner.png?c=a3IkLEOGzdCFb6d9avtchlIGmle6vmoM_rK3unyhDiOzqJ3R0-KA2Ge8z6bjiDGSPQxUUcVxu6P2OEc5g776KznCHbP593G5kmiASviHNeJoyo_4W3Y7...0.98
    12. EUROPE1.00
    13. SAFE0.90
    14. AIEngi0.93
    15. INTELLIGE1.00
    16. EUROI0.99
    17. Ah, welcome, sirs.1.00
    18. Λar0.84
    19. Do come in.0.98
    20. AlEngineer0.98
    21. EUROPE1.00
    22. PRESENTED BY1.00
    23. AlEngi0.96
    24. Google DeepMind1.00
    25. EURO1.00
    26. AlEngineer0.98
    27. OPENCLAW UPDATE1.00
    28. EUROPE1.00
    29. PRESENTED BY1.00
    30. OpenClaw1.00
    31. Google DeepMind1.00
    32. PETER STEINBERGER / Creator0.99
  • 4:01 #21 done100 line(s)

    shot 21·sharpness 2214.8

    1. Chrome1.00
    2. File0.97
    3. Edit0.94
    4. View1.00
    5. History1.00
    6. Bookmarks0.95
    7. Profiles0.95
    8. Tab1.00
    9. Window1.00
    10. Help1.00
    11. 0.53
    12. Thu Apr 9 10:180.98
    13. State of the0.99
    14. Clawdbot-Op0.92
    15. Security - Op0.96
    16. Warming: Cri0.86
    17. openshell m0.90
    18. NVIDIA/Nem0.86
    19. Security Adv0.92
    20. YClawHub0.80
    21. Thelethal tn0.92
    22. codex yolo0.87
    23. Claude Cod0.93
    24. AlEngineer0.95
    25. Wo1.00
    26. C0.62
    27. docs.openclaw.al/gateway/security0.99
    28. 0.55
    29. 0.75
    30. D0.57
    31. EUROPE1.00
    32. engrisn0.74
    33. U searcn ...0.85
    34. Hereases0.80
    35. uiscoru0.95
    36. Got started0.99
    37. Install1.00
    38. Channels1.00
    39. Agents1.00
    40. Tools & Plugins0.98
    41. Models1.00
    42. Platforms0.99
    43. Gateway & Ops0.98
    44. Reference0.97
    45. Help0.95
    46. SAFE0.95
    47. AIEngi0.95
    48. Gateway0.98
    49. Security and eandboxing0.98
    50. EOn this page0.96
    51. INTELLIGE1.00
    52. EURO1.00
    53. Gateway Runbook1.00
    54. Configuration and1.00
    55. Security1.00
    56. Scope first: personal1.00
    57. Security1.00
    58. operations1.00
    59. assistant security model1.00
    60. an0.78
    61. Security and sandboxing0.98
    62. Security0.99
    63. Sandboxing1.00
    64. Personal assistant trust model: this guidance assumes one trusted operator0.98
    65. sharing one agent/gateway. If you need mixed-trust or adversarial-user0.99
    66. boundary per gateway (single-user/personal assistant model). OpenClaw is1.00
    67. not a hostile multi-tenant security boundary for multiple adversarial users0.99
    68. operation, split trust boundaries (separate gatemay + credentials, ideally1.00
    69. Quick check: openclaw security0.99
    70. audit0.98
    71. Deployment and host trust1.00
    72. Shared Slack workspace: real0.99
    73. OpenShel10.95
    74. separate OS users/hosts).1.00
    75. risk1.00
    76. AlEngineer0.98
    77. EUROPE1.00
    78. Sandbox vs Tool Policy0.98
    79. vs Elevated1.00
    80. On this page: Trust model | Quick audit | Hardened baseline | DM access0.97
    81. Company-shared agent:1.00
    82. acceptable pattern0.99
    83. PRESENTED BY1.00
    84. AlEngi0.91
    85. Protocols and APIs1.00
    86. model | Configuration hardening | Incident response0.98
    87. Gateway and node trust concept1.00
    88. Trust boundary matrix1.00
    89. Google DeepMind0.97
    90. EURO1.00
    91. Networking and discovery0.99
    92. Scope first: personal assistant security model0.99
    93. Not vulnerabilities by design0.99
    94. Researcher preflight checklist1.00
    95. Remote access1.00
    96. OpenClaw security guidance assumes a personal assistant deployment: one0.99
    97. Hardened baseline in 600.98
    98. Remote Access1.00
    99. trusted operator boundary, potentially many agents.1.00
    100. seconds1.00
  • 4:04 #22 done

    shot 22·sharpness 1865.6

  • 4:08 #23 done

    shot 23·sharpness 1869.5

The page's on-screen-text budget of 600 lines is spent, so the last cards in this grid list fewer lines than they hold. Narrow the page with ?frames= to read them.

Transcript

568 cues· 6,341 words· 33,489 chars

  1. 0:15 Our next presenter is the creator of OpenClaw, the world's fastest growing open source AI.
  2. 0:22 He recently joined OpenAI to work on bringing agents to everyone.
  3. 0:26 Please join me in welcoming to the stage Peter Steinberger.
  4. 0:52 Good morning, everyone.
  5. 0:57 So Swiss asked me to do a state of the claw.
  6. 1:01 Who here is running open claw?
  7. 1:03 Give me some hands.
  8. 1:05 Oh, it's like 30%, 40%.
  9. 1:07 Very good.
  10. 1:10 Yeah.
  11. 1:10 It's been quite a few months.
  12. 1:16 The project is now five months old.
  13. 1:20 I think it's fair to say by now that we are the fastest growing project in GitHub's history.
  14. 1:25 If you've seen the graph, usually it's some projects look like a hockey stick, but also just like a straight line, and a friend called it stripper pole growth.
  15. 1:38 And that comes with its own challenges.
  16. 1:39 So we have, I think now we are the
  17. 1:43 the largest number on GitHub stars.
  18. 1:45 There's a few that are bigger, but they're basically an educational target.
  19. 1:48 No other software project is that big.
  20. 1:51 It's around 30,000 commits.
  21. 1:54 They're closing in 2,000 contributors, soon to be 30,000 PRs.
  22. 2:04 And we're not slowing down.
  23. 2:06 So you see that it's a ramp.
  24. 2:08 But you know, we only have April 9.
  25. 2:13 So velocity keeps being good.
  26. 2:20 And at the same time, it hasn't been easy.
  27. 2:26 I had two roads when I decided what I want to do.
  28. 2:29 And I did the whole company thing.
  29. 2:31 I was like, I don't want to do this again.
  30. 2:33 And then I joined OpenUI.
  31. 2:35 But then we also created the OpenCloud Foundation.
  32. 2:37 And now I kind of have two jobs.
  33. 2:39 And running the foundation is like running a company in hard mode, because you have all the things that you need to take care of.
  34. 2:48 But also, you have a lot of volunteers that you can't really direct.
  35. 2:54 One of my goals has been working on the bus vector, like who does commits.
  36. 3:00 And you see that it's slowly improving.
  37. 3:04 Vincent's actually talking after me.
  38. 3:06 But we're still not there.
  39. 3:11 In the last months, I talked to a lot of companies.
  40. 3:16 So we now have people from NVIDIA on board.
  41. 3:19 We have someone from Microsoft on board to help with MS Teams with a Windows app.
  42. 3:25 We have someone from Red Hat who's really helping us with security and Dockerization.
  43. 3:30 We work with a lot of Chinese companies.
  44. 3:32 We have people from Tencent and ByteDance.
  45. 3:36 They're actually much larger users than any other continent.
  46. 3:42 And we have people from pretty much around the world.
  47. 3:45 But the main thing I want to talk a little bit about is about Open Claw is so insecure.
  48. 3:51 You've seen the memes of Open Claw invites the bad guys.
  49. 3:59 And you've probably also seen companies like Nvidia doing Nemo Claw, and everyone has little lobsters.
  50. 4:13 So you also notice that in the last two, three months, there's been a lot of releases where things broke.

Chapters

  1. 0:00 Project Growth and Statistics
  2. 2:23 Management Challenges and the OpenClaw Foundation
  3. 3:47 Addressing Security Advisories and Vulnerabilities
  4. 10:33 Misinformation and Media Fearmongering
  5. 14:50 The Burden of Open Source Maintenance
  6. 16:12 OpenAI Involvement and Future Independence
  7. 18:57 Audience Q&A Begins
  8. 19:53 OpenClaw's Relationship with OpenAI
  9. 22:28 The Importance of Open and Local Models
  10. 24:57 Coding Workflow and Agent Interactions
  11. 28:28 Defining 'Taste' in AI Development
  12. 30:31 Developing Personality for AI Agents
  13. 33:22 Future Vision: Ubiquitous Agents and Smart Homes
  14. 35:58 Addressing Prompt Injection Risks
  15. 38:33 Future Vision: Implementing 'Dreaming' and Modularity
  16. 40:24 Life as a Maintainer and Future Skills

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