how did we end up here – todd montgomery and tisha gee – qcon

This is part of my live blogging from QCon 2015. See my <a /2015/06/10/qcon/”>QCon table of contents</a> for other posts.

When new, we assume everone knows what they are doing and everything is logical/clean/organized. Yet, reality is messy. Sometimes get to the point where can’t touch anything. Sometimes get to the point where proud of over-engineered/terrible solutions.

Software process stats

  • agile and iterative have similar project success rate
  • Ad-hoc and waterfall are similar
  • Agile/iterative is only a little better
  • Projects with less than 10 people significantly better than twenty or more
  • Different reports mesure successful projects differently. 30%- 60%.
  • More expensive project not better “throwing more $ at projects don’t make it better” [wouldn’t this be because of size of project; not throwing $ at it?]

Enterprise architect == so good at job that no longer do development. Surgeons design systems not people who used to,

More organizations are looking at contributions to open source to prove can do development before start. No place to hide; mediocrity becomes visible. Open source is not a business plan, but can be a distribution model.


  • Minimal viable product – people don’t want to buy MVP. Why aim for it? [we don’t it is about doing that first so guaranteed to have a base]
  • Product owner – why can’t talk to real customer. Why need a proxy? Want direct feedback. Actually pairing with customer to see how use app brings up usabiity/process issues. Technology should be part of the business.
  • Poll: how many people doing agile release less than every 3 months? A few
  • Water-scrum-full – tiny waterful. Do scrum practices, but ignore retrospective and still waterfall. Should focus on learning, feedback cycles and outcomes
  • Projects often succeed because 1-2 people make it happen in spite of process. Find out by thinking “what would happen if you weren’t involved”

“Shared mutable state” should be scary. Should be for sysetms programming where domain is smaller and understand hardware. Otherwise, shouldn’t be taken for granted. Embrace append only, single writer and shared nothing designs.

Ambdal’s law says can only scale up to a certain # of CPUs before maxing out. Universal Scalability Law says it gests worse well before that. “Coherence penalty”

Simplicity is better

Text encoding (JSON, XML) doesn’t need to be human readable. It’s computers talking to each other

Have to deal with probems and lack of response for both synchronous and async communication

Errors need to be first class messages. Java Exceptions name imply they are unusual cases. Don’t know what to do with them anyway.

Abstractions shouldn’t mean generalization. hould be about creating a semantic level so can be more precise.

Issues: Superiority complex with different technologies/techniques and anyone who says otherwise is wrong. Religious wars. X is the solution to everything.

Functional programming is not the anwer to multi-core. The math (universal scalability law) still hits . [still helps up to a point though on the graph]

Think about transformation and flow of data; not code


  • Mobile makes us think about hardware again – battery and bandwidth. Free lunch on throwning hardware at problem is over
  • Hardware has been designed to make bets on locality and predictable for access. Pre-fetching and the like make an order of magnitude difference.
  • Bandwidth is increasing. Latency is staying the same.


  • Testosterone Driven Development
  • Increase in women went up with other STEM fields. Then in CS it started declining in 1980. This is when PCs were introduced at marketed to boys.
  • Can catch up in a year even if start coding in college.
  • Grace Hopper invented COBOL and the compiler
  • Margret Hamilton invented async programming via NASA

Don’t be afraid to fail

Impressions: great substitute keynote. I wonder how long they had to practicing together. Trisha said she’s seen it given before (with Martin Thompson)

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