What started off as a trial-and-error approach to improve the state of software development by a bunch of tinkerers, is today dominated by management consultants, "Thou-Shall" codified frameworks and rigid, expensive tools. Over the last 20 years, we've gone from, "I'm not sure, let's try this in a small-safe environment" to "you/your-team sucks; you guys have a very poor agile maturity because you are not doing _x_y_z_ (not conforming to the standards)." Along the way, we've lost the purpose of being agile .i.e. to embrace uncertainty and simplicity. Instead we've been forced to believe that consistency via top-down standardisation and predictability by increasing the rigour on process is our eternal quest. Anything that sounds simple and works 80% of the cases is discarded as being naive. What once drove thought-leader into agile, is now driving them insane. This is the unfortunate fate of Agile. Luckily there has been some fresh perspectives from Nassim Taleb, author of Antifragile. His work explains how some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty. More importantly why antifragility is beyond resilience or robustness. In this talk, I'll use some of Nassim's thoughts (and some of my own) to explain what is wrong with our current approach to Agile and how we can bring life back into Agile. Particularly how we can leverage Volatility, Uncertainty, Complexity, and Ambiguity to make product development more antifragile.

1. D E C L I N E A N D FA L L O F A G I L E
A N T I F R A G I L E M I N D S E T T O R E S C U E
Naresh Jain
@nashjain
http://nareshjain.com

2. Agile is for totally dysfunctional teams!
I think you deserve something better…

4. I N T H E 8 0 ’ S - S O F T WA R E D E V E L O P M E N T P R O C E S S E S
L O O K E D L I K E T H I S

5. T H I S L E D T O …

6. Heavyweight Process

7. More and more Upfront Planning

8. Strict Change Control

9. Over-reliance on documentation

10. Even if you saw things
were going wrong,
unable to React

11. Communication Gaps

12. R E S U LT ?

13. 50+% of Projects fall in Challenged Category
Succeeded
Failed
Challenged
Chaos Report 2006. Standish Group
We need to do beBer than this ….
IT Projects

14. Cost and Time Overruns….

15. Always
7%
OKen
13%
SomeNmes
16%
Rarely
19%
Never
45%
Standish Group study reported at XP2002 by Jim Johnson, Chairman
O"en or Always
Used: 20%
Rarely or Never
Used: 64%
64% of Features Rarely or Never Used

16. How significant is requirements change on a project?
“The average project has 30% requirements change”
Requirements Change Increase ExponenNally

17. Frustration

20. Agile was about Embracing
Uncertainty/Change via
Simplicity

21. Agile was about Embracing
Uncertainty/Change via
Simplicity
Its origins were rooted in
Antifragile thinking

22. O V E R T H E Y E A R S …
A G I L E H A S B E C O M E V E RY F R A G I L E

23. • F R A G I L E
• R O B U S T &
R E S I L I E N T
• A N T I F R A G I L E
A N T I F R A G I L E

24. F R A G I L E
E a s i l y B ro k e n O r D a m a g e d B y A p p l y i n g S t re s s / P re s s u re

25. P R O P E R T I E S O F F R A G I L E

26. P R O P E R T I E S O F F R A G I L E
• Dislikes variability and stress

27. P R O P E R T I E S O F F R A G I L E
• Dislikes variability and stress
• Seek to eliminate variability, noise, and tension

28. P R O P E R T I E S O F F R A G I L E
• Dislikes variability and stress
• Seek to eliminate variability, noise, and tension
• Consistency/Standardisation driven

29. P R O P E R T I E S O F F R A G I L E
• Dislikes variability and stress
• Seek to eliminate variability, noise, and tension
• Consistency/Standardisation driven
• Overly optimised for specific use-case/scenario

30. P R O P E R T I E S O F F R A G I L E
• Dislikes variability and stress
• Seek to eliminate variability, noise, and tension
• Consistency/Standardisation driven
• Overly optimised for specific use-case/scenario
• Prediction based

31. P R O P E R T I E S O F F R A G I L E
• Dislikes variability and stress
• Seek to eliminate variability, noise, and tension
• Consistency/Standardisation driven
• Overly optimised for specific use-case/scenario
• Prediction based
• Typically large

32. R E S I L I E N T
A b l e To W i t h s t a n d O r R e c o v e r Q u i c k l y F ro m D i ff i c u l t C o n d i t i o n s

34. A N T I F R A G I L E
A n t i f r a g i l e S y s t e m G a i n s F ro m D i s o rd e r /
C h a o s , R a n d o m n e s s , U n c e r t a i n t y,
Vo l a t i l i t y, C o m p l e x i t y & A m b i g u i t y.
T h r i v e s O n Va r i a b i l i t y O r R a n d o m n e s s

38. Venture Capitalist

40. P R O P E R T I E S O F A N T I F R A G I L E

41. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact

42. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact
• decentralized system with buffers & inventories (Opp. of J.I.T)

43. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact
• decentralized system with buffers & inventories (Opp. of J.I.T)
• dislike consistency/standardisation

44. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact
• decentralized system with buffers & inventories (Opp. of J.I.T)
• dislike consistency/standardisation
• less is more / keep it small and simple (KISS) - large is vulnerable

45. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact
• decentralized system with buffers & inventories (Opp. of J.I.T)
• dislike consistency/standardisation
• less is more / keep it small and simple (KISS) - large is vulnerable
• encourage optionality by deferring decisions to the last responsible
moment (hence is more opportunistic)

46. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact
• decentralized system with buffers & inventories (Opp. of J.I.T)
• dislike consistency/standardisation
• less is more / keep it small and simple (KISS) - large is vulnerable
• encourage optionality by deferring decisions to the last responsible
moment (hence is more opportunistic)
• dislike prediction (system based on prediction are fragile)

47. P R O P E R T I E S O F A N T I F R A G I L E
• builds layers of redundancy to localise impact
• decentralized system with buffers & inventories (Opp. of J.I.T)
• dislike consistency/standardisation
• less is more / keep it small and simple (KISS) - large is vulnerable
• encourage optionality by deferring decisions to the last responsible
moment (hence is more opportunistic)
• dislike prediction (system based on prediction are fragile)
• safe-fail, fail-frequently, fail-diversely

48. Commercial Break!

49. Copyright
© 2012,
Naresh Jain (@nashjain)

50. Mumbai

54. Tech Talks!

57. O V E R T H E Y E A R S …
A G I L E H A S B E C O M E V E RY F R A G I L E

58. W H AT ’ S W R O N G W I T H A G I L E T O D AY ?
W R I T E D O W N A F E W P O I N T S B A S E D O N Y O U R E X .
Q U I C K P O L L :

59. S T O RY P O I N T S A N D V E L O C I T Y
V E L O C I T Y I S K I L L I N G A G I L I T Y
S T O P I T 1 :

60. # N O E S T I M AT E & C O N T I N U O U S D E P L O Y M E N T S
C O N S TA N T LY D E L I V E R I N G VA L U E & VA L I D AT I N G I T
A N T I F R A G I L E 1 :
X

61. D E F I N I T I O N O F D O N E
H A N G O V E R F R O M C H E C K L I S T D R I V E N P R O J E C T M A N A G E M E N T
S T O P I T 2 :

62. # D E V O P S
B U I L D P I P E L I N E S & S A F E - FA I L R O L L O U T
A N T I F R A G I L E 2 :
X

63. D E AT H B Y M E E T I N G S / C E R E M O N I E S
M O R E P R O C E S S I S N O T T H E A N S W E R
S T O P I T 3 :

64. N E G AT I VA
T H R O W O U T P R A C T I C E S ( L E S S I S M O R E ) - R E D U C E D O W N S I D E
A N T I F R A G I L E 3 :
X

65. C O L L A B O R AT I O N A M P L I F I E D
W H AT A B O U T S O L O - D E E P T H I N K I N G & A U T O N O M Y ?
S T O P I T 4 :

66. Think of your best work-related idea

67. Think of your best work-related idea
Where were you when you come up with this idea?

68. Think of your best work-related idea
Where were you when you come up with this idea?
How many of you were collaborating/working
with other people when you come up with your
most profound idea?

69. H O W M A N Y P E O P L E W R O T E T H E A G I L E M A N I F E S T O ?

70. S E T- B A S E D D E V E L O P M E N T
I N D E P E N D E N T, A U T O N O M O U S , PA R A L L E L S A F E - FA I L E X P E R I M E N T S
A N T I F R A G I L E 4 :
X

71. T E C H N I C A L D E B T O V E R F L O W
H O W L O N G W I L L E N G I N E E R I N G E X C E L L E N C E B E I G N O R E D ?
S T O P I T 5 :

72. T H R O W AWAY C O D E F R E Q U E N T LY
U S E F U L L - S TA C K P R O G R A M E R S T O B U I L D M I C R O S E R V I C E S
A N T I F R A G I L E 5 :
X

73. M I C R O - M A N A G E M E N T
G O O D P E O P L E N E E D T H E I R S PA C E A N D T I M E
S T O P I T 6 :

74. P R O G R A M M E R A N A R C H Y O R O P E N S O U R C E M O D E L
H I R E G O O D P E O P L E A N D L E T T H E M B E S E L F - D I R E C T E D
A N T I F R A G I L E 6 :
X

75. S M & P O A R E H A L F - A * * E D R O L E S
L A C K O F O W N E R S H I P & A C C O U N TA B I L I T Y
S T O P I T 7 :

76. G A R A G E S TA RT U P S T Y L E L E A D E R S H I P
L E T P O W E R C E N T R E S E M E R G E D Y N A M I C A L LY
A N T I F R A G I L E 7 :
X

77. P E R F O R M A N C E A P P R A I S A L
S O M E E M P L O Y E E S W I L L A LWAY S G A M E T H E S Y S T E M
S T O P I T 8 :

78. “Simple, clear purpose and
principles give rise to complex
and intelligent behaviour.
Complex rules and
regulations give rise to simple
and stupid behaviour.”
Dee Hock

79. O P E N S A L A R I E S A N D S K I N I N T H E G A M E
B U I L D P O L I C I E S T O M A K E L I F E E A S Y F O R M A J O R I T Y N O T M I N O R I T Y
A N T I F R A G I L E 8 :
X

80. S C A L I N G A N D S U S TA I N I N G N I G H T M A R E S
L A R G E I S V U L N E R A B L E A N D C O M P L E X
S T O P I T 9 :

81. A U T O N O M O U S - A L I G N E D T R I B E S
K E E P I T S M A L L A N D S I M P L E
A N T I F R A G I L E 9 :
X

82. C E RT I F I C AT I O N
A B I L L I O N D O L L A R B U S I N E S S
S T O P I T 1 0 :

83. G E N E R A L I S I N G S P E C I A L I S T S W I T H H A N D S - O N S K I L L S
S P E C I A L I S T S C A N B E C O M E Q U I C K LY I R R E L E VA N T
A N T I F R A G I L E 1 0 :
X

84. A N D T H E L I S T G O E S O N …

85. T H A N K Y O U !
Q U E S T I O N S ?
Naresh Jain
@nashjain
http://nareshjain.com