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GayleL. McDowell | Founder/ CEO, CareerCup
gayle in/gaylemcdgayle
The Architecture of Interviews
Consistency+ Efficiency+ ...
&
candidates are
frustrated confused
gayle in/gaylemcdgayle 3Gayle Laakmann McDowell
They
Don’t
Know…
 Howmany interviews
 Who will be interviewing
 If they...
&
&
companies need
consistency efficiency
high bar happiness
Gayle Laakmann McDowell 5gayle in/gaylemcdgayle
Consistency & Efficiency
Consistency
 Outcome
 Process
 Questions
Effic...
Gayle Laakmann McDowell 6gayle in/gaylemcdgayle
High Bar & Happiness
High Bar
 Minimize false positives
 Good, adaptable...
7 gayle in/gaylemcdgayle
The Process
Resume Selection
Intro Call w/
Recruiter
Email that outlines
process
Code Assessment
...
gayle in/gaylemcdgayle 8Gayle Laakmann McDowell
Stuff
I’ll
Discuss
 BarRaisersvs. Hiring Committees
 OfflineWork
 Homew...
Bar Raisers or
Hiring Committees
So different, yet so similar
01
Gayle Laakmann McDowell 10gayle in/gaylemcdgayle
Bar Raisers andHC
Offer transparency
Offer consistency
Keepbar high
F...
gayle in/gaylemcdgayleGayle Laakmann McDowell 11
HiringCommittee
Cons
 Overhead
 Delays
 Un-empowering
 Can feel “blac...
Gayle Laakmann McDowell 12gayle in/gaylemcdgayle
Who’s it good for?
Companies that:
 See5or more devcandidatesperweek
 ...
gayle in/gaylemcdgayleGayle Laakmann McDowell 13
HiringCommittee: Best Practices
Meet at least 2x per week
Multiple HCs:...
gayle in/gaylemcdgayleGayle Laakmann McDowell 14
Bar Raisers
Cons
 Need consistency across
company
 Need to scale team
P...
gayle in/gaylemcdgayleGayle Laakmann McDowell 15
Bar Raisers:Best Practices
 Select people who areinherently good
 Exper...
Offline
Assessments
Homework, code assessment tools,
etc
02
Gayle Laakmann McDowell 17gayle in/gaylemcdgayle
OfflineAssessments
Homework Projects Code Assessment Tools
gayle in/gaylemcdgayleGayle Laakmann McDowell 18
Homework Projects
Big
Very Practical
Some love this
Lesscheating
 Ex...
gayle in/gaylemcdgayleGayle Laakmann McDowell 19
Homework: Best Practices
Show candidate
interestfirst
< 4 hours
 If >4...
gayle in/gaylemcdgayleGayle Laakmann McDowell 20
Homework: Who It’s Good For
Language focused
 Low priority on algorithm...
gayle in/gaylemcdgayleGayle Laakmann McDowell 21
Code Assessment Tools
Fast, cheap eval
 Morecandidates
 Non-traditiona...
gayle in/gaylemcdgayleGayle Laakmann McDowell 22
ImplementationOptions
Everyone
Just your “maybe” candidates
Fast-Track
gayle in/gaylemcdgayleGayle Laakmann McDowell 23
Who It’s GoodFor
Small, mid-sized, and big companies
Value algorithms /...
gayle in/gaylemcdgayleGayle Laakmann McDowell 24
Code Assessment: Best Practices
Show candidate interest
first
Beware of...
Question Style
Pair programming, algorithms,
knowledge
03
Gayle Laakmann McDowell 26gayle in/gaylemcdgayle
What ToAsk
Knowledge
Algorithms
Design/Architecture
Pairprogramming
Gayle Laakmann McDowell 27gayle in/gaylemcdgayle
Knowledge Questions
Good whenyou can’t train skilleasily
Best practice:...
Gayle Laakmann McDowell 28gayle in/gaylemcdgayle
Algorithm Questions
Smartmatters.
Good for everyone
Best practices:
 ...
Gayle Laakmann McDowell 29gayle in/gaylemcdgayle
Design/Architecture
Great for experienced candidates
Shows communicatio...
gayle in/gaylemcdgayleGayle Laakmann McDowell 30
PairProgramming
 Many candidates enjoy it
 Feels fair & real world
 As...
Gayle Laakmann McDowell 31gayle in/gaylemcdgayle
PairProgramming: Best Practices
 Prep/warn candidates
 Need GREAT inter...
Coding Platform
Whiteboard vs. Computers
04
Gayle Laakmann McDowell 33gayle in/gaylemcdgayle
Why We Make Them Code
Can theyput“thoughts”into “actions”?
Do they show...
Why not pseudocode?
A Game with Secret Rules
… and this is for a
simple problem
Gayle Laakmann McDowell 36gayle in/gaylemcdgayle
Don’t Allow Pseudocode
Unpredictable playing field
Detailsmatter
If “r...
gayle in/gaylemcdgayleGayle Laakmann McDowell 37
How toCode
Big Practical Stuff
Use computer
Pair Programming
Small Stuf...
gayle in/gaylemcdgayleGayle Laakmann McDowell 38
Buthow to code?
whiteboard computer
gayle in/gaylemcdgayleGayle Laakmann McDowell 39
A Case for Computers
 Realistic. Allows tools.
 Candidates feel more co...
gayle in/gaylemcdgayleGayle Laakmann McDowell 40
The Downsideof Computers
Oftenwrite stupid stuff
Desperate attemptfor c...
gayle in/gaylemcdgayle 41
z
Gayle Laakmann McDowell
Computer
Best
Practices
Let candidate bring laptop
Instruct: not eve...
gayle in/gaylemcdgayleGayle Laakmann McDowell 42
A Case for Whiteboards
Encourages thinking & communication
More languag...
gayle in/gaylemcdgayleGayle Laakmann McDowell 43
The Downsideof Whiteboards
Slow to write
Artificial environment
Can be...
gayle in/gaylemcdgayle 44
z
Gayle Laakmann McDowell
Whiteboard
Best
Practices
Encourage shorthand
Be upbeat & encouragin...
gayle in/gaylemcdgayleGayle Laakmann McDowell 45
Recommendations
If skill-focused:
then Computer
If algos-focused:
then Wh...
Last Remarks
05
gayle in/gaylemcdgayleGayle Laakmann McDowell 47
Thingsto Consider
 BarRaisersor Hiring Committees
 Code assessmenttools...
there is no
perfect system
THANK YOU
gayle@gayle.com
gayle in/gaylemcdgayle
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Architecture of Tech Interviews

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Bar raisers, hiring committees, hackerrank and coding assessment tools, and more.

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Architecture of Tech Interviews

  1. 1. GayleL. McDowell | Founder/ CEO, CareerCup gayle in/gaylemcdgayle The Architecture of Interviews Consistency+ Efficiency+ High Bar + Happiness June7, 2016 | Talent42
  2. 2. & candidates are frustrated confused
  3. 3. gayle in/gaylemcdgayle 3Gayle Laakmann McDowell They Don’t Know…  Howmany interviews  Who will be interviewing  If they’ll code?How?  What they need to know  Howdecision gets made  WHY? Lotsofmyths (andmisinformation)!
  4. 4. & & companies need consistency efficiency high bar happiness
  5. 5. Gayle Laakmann McDowell 5gayle in/gaylemcdgayle Consistency & Efficiency Consistency  Outcome  Process  Questions Efficiency  Speedy process  Able to expedite  Minimal overhead  Minimal false negatives
  6. 6. Gayle Laakmann McDowell 6gayle in/gaylemcdgayle High Bar & Happiness High Bar  Minimize false positives  Good, adaptable people Happiness  Enjoyable experience  Makes company look good  Transparency
  7. 7. 7 gayle in/gaylemcdgayle The Process Resume Selection Intro Call w/ Recruiter Email that outlines process Code Assessment Phone Interview ~4 onsite interviews Discussion & Decision “Sell” Call / Dinner
  8. 8. gayle in/gaylemcdgayle 8Gayle Laakmann McDowell Stuff I’ll Discuss  BarRaisersvs. Hiring Committees  OfflineWork  Homework vs code assessment tools  QuestionStyle  Knowledge, algorithms, pair programming  Coding Platform  Real code vs. pseudocode  Whiteboard vs. computer
  9. 9. Bar Raisers or Hiring Committees So different, yet so similar 01
  10. 10. Gayle Laakmann McDowell 10gayle in/gaylemcdgayle Bar Raisers andHC Offer transparency Offer consistency Keepbar high Facilitatechange Can override manager
  11. 11. gayle in/gaylemcdgayleGayle Laakmann McDowell 11 HiringCommittee Cons  Overhead  Delays  Un-empowering  Can feel “black box”  Need good feedback Pros  Cross-company consistency  Keeps barhigh  Easierto improveprocess
  12. 12. Gayle Laakmann McDowell 12gayle in/gaylemcdgayle Who’s it good for? Companies that:  See5or more devcandidatesperweek  Wanttoimproveprocess  Hireforcompany,notteam  Arenotveryknowledgefocused Easier to implement early!
  13. 13. gayle in/gaylemcdgayleGayle Laakmann McDowell 13 HiringCommittee: Best Practices Meet at least 2x per week Multiple HCs:  Beware ofbarcreep /inconsistencies Let interviewers observe HC Traininterviewers to write feedback Quality of decisions rests onfeedback
  14. 14. gayle in/gaylemcdgayleGayle Laakmann McDowell 14 Bar Raisers Cons  Need consistency across company  Need to scale team Pros  Many ofHC benefits:  Consistency  High bar  Transparency  But easierto implement  No bottleneck
  15. 15. gayle in/gaylemcdgayleGayle Laakmann McDowell 15 Bar Raisers:Best Practices  Select people who areinherently good  Experiencedatinterviewing  Nice, empathetic  Smart&can challengecandidate  Train them thoroughly  Empowerthem  Assign outside of team  Watch out for scale/exhaustion!
  16. 16. Offline Assessments Homework, code assessment tools, etc 02
  17. 17. Gayle Laakmann McDowell 17gayle in/gaylemcdgayle OfflineAssessments Homework Projects Code Assessment Tools
  18. 18. gayle in/gaylemcdgayleGayle Laakmann McDowell 18 Homework Projects Big Very Practical Some love this Lesscheating  Except:algos Too immediate Needs eng time Disproportionate workload Scales poorly for candidate
  19. 19. gayle in/gaylemcdgayleGayle Laakmann McDowell 19 Homework: Best Practices Show candidate interestfirst < 4 hours  If >4, onsite project review Architecture, not algorithms Define review criteria Avoid confusion with company work
  20. 20. gayle in/gaylemcdgayleGayle Laakmann McDowell 20 Homework: Who It’s Good For Language focused  Low priority on algorithms / thought process Experienced candidates (maybe)
  21. 21. gayle in/gaylemcdgayleGayle Laakmann McDowell 21 Code Assessment Tools Fast, cheap eval  Morecandidates  Non-traditional Sets expectations for onsite Consistent data point Cheating May turn off senior candidates
  22. 22. gayle in/gaylemcdgayleGayle Laakmann McDowell 22 ImplementationOptions Everyone Just your “maybe” candidates Fast-Track
  23. 23. gayle in/gaylemcdgayleGayle Laakmann McDowell 23 Who It’s GoodFor Small, mid-sized, and big companies Value algorithms / problem solving Lots of candidates Want to look at non-traditional candidates
  24. 24. gayle in/gaylemcdgayleGayle Laakmann McDowell 24 Code Assessment: Best Practices Show candidate interest first Beware of cheating  (But nobiggie!) Clearexpectations Pick GREAT questions  Similar to real interviews  Unique questions 1 – 2 hour test
  25. 25. Question Style Pair programming, algorithms, knowledge 03
  26. 26. Gayle Laakmann McDowell 26gayle in/gaylemcdgayle What ToAsk Knowledge Algorithms Design/Architecture Pairprogramming
  27. 27. Gayle Laakmann McDowell 27gayle in/gaylemcdgayle Knowledge Questions Good whenyou can’t train skilleasily Best practice:  In-depth,ifat all  Keepita discussion
  28. 28. Gayle Laakmann McDowell 28gayle in/gaylemcdgayle Algorithm Questions Smartmatters. Good for everyone Best practices:  Clear expectations with interviewers & candidates  Ask medium-to-hard & unusual questions
  29. 29. Gayle Laakmann McDowell 29gayle in/gaylemcdgayle Design/Architecture Great for experienced candidates Shows communicationskills Best practice:  Prepcandidates.Big unknown!
  30. 30. gayle in/gaylemcdgayleGayle Laakmann McDowell 30 PairProgramming  Many candidates enjoy it  Feels fair & real world  Assesses codestyle / structure  Shows interpersonal interaction  Less understood  Not greatfor algos  Interviewer really matters  Biased by tools
  31. 31. Gayle Laakmann McDowell 31gayle in/gaylemcdgayle PairProgramming: Best Practices  Prep/warn candidates  Need GREAT interviewer  Give choice of problems  Okay/good to pick unreasonably big problems  Guide candidates  (Okaytoaskquestions,notknowtools,etc.)
  32. 32. Coding Platform Whiteboard vs. Computers 04
  33. 33. Gayle Laakmann McDowell 33gayle in/gaylemcdgayle Why We Make Them Code Can theyput“thoughts”into “actions”? Do they show good structure and style? Do they thinkabout theimpact of decisions?
  34. 34. Why not pseudocode?
  35. 35. A Game with Secret Rules … and this is for a simple problem
  36. 36. Gayle Laakmann McDowell 36gayle in/gaylemcdgayle Don’t Allow Pseudocode Unpredictable playing field Detailsmatter If “real code” is too hard for them…
  37. 37. gayle in/gaylemcdgayleGayle Laakmann McDowell 37 How toCode Big Practical Stuff Use computer Pair Programming Small Stuff Algorithm-focused Computer or whiteboard
  38. 38. gayle in/gaylemcdgayleGayle Laakmann McDowell 38 Buthow to code? whiteboard computer
  39. 39. gayle in/gaylemcdgayleGayle Laakmann McDowell 39 A Case for Computers  Realistic. Allows tools.  Candidates feel more comfortable  (Especially experienced &diversity candidates)  Faster to write (often)  Morecode
  40. 40. gayle in/gaylemcdgayleGayle Laakmann McDowell 40 The Downsideof Computers Oftenwrite stupid stuff Desperate attemptfor compilation Communicationshutsdown Biased by tools/laptop “Transition” betweenalgorithm & code
  41. 41. gayle in/gaylemcdgayle 41 z Gayle Laakmann McDowell Computer Best Practices Let candidate bring laptop Instruct: not every detail Encourage communication and thinking Recognize the bias!
  42. 42. gayle in/gaylemcdgayleGayle Laakmann McDowell 42 A Case for Whiteboards Encourages thinking & communication More language agnostic Consistent across candidates  Better laptop/tools doesn’t matter It’s “standard”
  43. 43. gayle in/gaylemcdgayleGayle Laakmann McDowell 43 The Downsideof Whiteboards Slow to write Artificial environment Can be intimidating
  44. 44. gayle in/gaylemcdgayle 44 z Gayle Laakmann McDowell Whiteboard Best Practices Encourage shorthand Be upbeat & encouraging Reasonable expectations
  45. 45. gayle in/gaylemcdgayleGayle Laakmann McDowell 45 Recommendations If skill-focused: then Computer If algos-focused: then Whiteboard If a little of each: then Either/or  Both can work!  … with proper training  Whynot let candidate choose?
  46. 46. Last Remarks 05
  47. 47. gayle in/gaylemcdgayleGayle Laakmann McDowell 47 Thingsto Consider  BarRaisersor Hiring Committees  Code assessmenttools  Pairprogramming(forpracticalstuff)  Whiteboard(orpick-your-poison)foralgorithmsstuff
  48. 48. there is no perfect system
  49. 49. THANK YOU gayle@gayle.com gayle in/gaylemcdgayle

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