Dancing for a product release


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Discussion on how to set up a team to be ready to release many versions of a product

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Dancing for a product release

  1. Dancing for a product release lcerveau@nephorider.com
  2. • From general (over) simplistic things to practical tricks • Mix of big company and startup experiences • From inside (direct management) and outside (consulting)
  3. • Idea of creating one identified entity • With a name, possibly a brand • That has multiple releases with different importances • And where each release is infused by the personality of its creator team Product??
  4. • The team has to deliver it • The team has to evolve So that a product lives
  5. Put the Team in place
  6. Years of cultural organization (Europe, East Coast…) Tester Dev Product Marketing BOSS High level glorious thinker Low level manual stinker Add the Project Manager as mid level wannabee parasite Inside Outside
  7. Impact of the 201X Startup paradigm • Let’s pretend this does not exist because there are not enough people in the company and everyone is multitasked • Let’s not hide anymore the engineering geek and make it a selling argument • Let’s pretend a product/app is a common work But it takes more to fight your reptilian/cultural/religious brain
  8. Change your mental schema Tester DevProductMarketing Dictatorial Boss Project Manager —> Engineering Project Manager EPM
  9. Engineering Project Manager • Duty to make reporting and have a rigorous no lie/ no bullshit attitude • Must have no favorite partner among the other core team group • Must anticipate (and do) the work that other do not want to do : bug triage, reporting • Should be number one product knowledge source
  10. Technical or not? • Decide from the start if you are a technological company • If yes make sure that you can show your technical assets at any time • If not think if having a technical team is a good thing • If not Keep a QA instead of an engineer
  11. About QA • It always come at last. Whatever you announce. • QA people are always considered as “not good enough to be an engineer” • They are always right • They must feed the machine (bug), especially to do what automation can’t
  12. Don’t break the cycle Especially at day 1
  13. Develop Release Use/Test
  14. Versioning • When you repeat yourself change the version each time. Reporting is essential. • Build version versus marketing version (iOS has agvtool - set up your project). • Version all components, make the version easy to find Question most heard in product life cycle. Save 20% of useless talk
  15. Release • If there is one automated piece in your system this is the release tool • The boss should be able to make a build • Release at regular and fixed intervals. Do not wait for engineers/designer to complete their fixes • EPM should make sure everyone knows what’s new there. Track history
  16. Distribute (especially mobile) • Use third party tools for mobile applications (Testflight) • Make sure everyone is over-notified of a new build • If you worry about who is on your distribution list, do not put her/him there. Remove people who do not install • Use distribution to validate a development. This is NOT final release
  17. Measure • A bug system is a metric system. It provides cold facts. • If you argue philosophically about what is a bug (or not), a feature (or not), then stop doing this job and do cocktails • Make sure it can integrate at all level of the workflow (gathering of bugs) • The best tool for your team is the one people use
  18. The cycle is for everyone • Product designer could be ask to provide 10 variations of one design • Product launch is not done with talk : text to write, translation to make, videos to prepare • The EPM must gather all elements
  19. Process or not? • Process is a mean not a goal but “Without process there is no product” . • Do not make process or tools a topic of discussion inside your company. • Once a process decision is here, stick to it… until you change it • If it is not adopted try again later Yaka, Fokon happens here
  20. Tech management
  21. Landscape • Software Engineers are the kings of today • ….but statistically this can’t be • And everyone like to think they are in the late part of the Gaussian curve me = fXXXing genius
  22. 2 books to read
  23. Dreyfus model of skill acquisition • Developed by two (Stuart and Hubert) brothers in the 1980 • Model of skill acquisition and mastering • 5 levels from Novice to Expert: they see the world in different ways • Per skill model but….
  24. Dreyfus model Expert Expert work from intuition Proficient Proficient practitioners can self correct Competent Competent can troubleshoot Advanced Beginners Advanced beginners don’t want the big picture Novices Novices needs recipes
  25. Build your team • Decide how to balance the skills and levels: e.g one architect (expert), one debugger (expert), 3 monkeys coders (Beginners) Skills Level
  26. Some management experience • Startup does not give you legitimacy. This is a constant fight. • Recruiting is the entry point: “Smart and get things done” • Applying “best practices” should be done according to where the team stands in the Dreyfus model • No concession should be made on the company code identity. If it looks good and coherent it probably is.
  27. Make a set of common knowledge • Everey engineer should know this • Some examples - Stop and start the infrastructure - Know an HTTP API - Know the database model - Measure performance of a system
  28. Technology choice • There is no technology fundamentally better than an other. Just different paths to the same point Tech A Tech B
  29. So where are the differences? • Someone who deadly wants to prove a technology is better will be better • Depending on what are the company goal the technical target goal should be adapted,as long as you are conscious about it • In the end the quality will come from coming back to what has been done. It takes one year to write a piece of code
  30. The signs to fire an engineer/consultant • “We need to redo everything” • “This is not in my code” • “We should change to this new library”
  31. Product evolution technical impact • Ways to upgrade between versions. Be forward and backward compatible • Have a way to notice that there is maintenance • Make a version obsolete with a nice feedback • Be as much crash prone in your data technology From day 1 have in your product
  32. Stay manual
  33. • You can not go so much faster than the speed of team • But you must always try to do it Team learning can be slow process
  34. • Release tool • Automatic Bug reporting • Automatic test • Monitoring and notification of problems Automation is useful
  35. But sometimes keep it manual • Automation is good only if someone read the reports • Understanding what needs automated need manual try