ASWEC Day 3 (SE Education Track), Keynote, “Teaching Gap: Where’s the Product Gene?” (#aswec2014 #AdelED @jmwind)Posted: April 9, 2014
Today’s speaker is Jean-Michel Lemieux, the VP of Engineering for Atlassian, to open the Education track for the ASWEC Conference. (I’m the track chair so I can’t promise an unbiassed report of the day’s activities.) Atlassian has a post-induction reprogramming idea where they take in graduates and then get people to value products over software – it’s not about what’s in the software, it’s about who is going to be using it. The next thing is to value experiences over functionality.
What is the product “gene” and can we teach it? Atlassian has struggled with this in the past despite having hired good graduates in the past, because they were a bit narrow and focused on individual features rather than the whole product. Jean-Michel spoke about the “Ship-it” event where you have to write a product in 24 hours and then a customer comes and pick what they would buy.
Jean-Michel is proposing the addition of a new degree – to add a product engineering course or degree. Whether it’s a 1 year or 4 year is pretty much up to the implementers – i.e. us. EE is about curvy waves, Computer Engineering is about square waves, CS is about programs, SE is about processes and systems, and PE is about product engineering. PE still requires programming and overlaps with SE. Atlassian’s Vietnam experience indicates that teaching the basics earlier will be very helpful: algorithms, data structures, systems admin, programming languages, compilers, storage and so on. Atlassian wants the basics in earlier here as well (regular readers will be aware of the new digital technologies curriculum but Jean-Michel may not be aware of this).
What is Product Engineering about? Customers, desirable software over a team as part of an ecosystem that functions for years. This gets away from the individual mark-oriented short-term focus that so many of our existing courses have (and of which I am not a great fan). From a systems thinking perspective, we can look at the customer journey. If people are using your product then they’re going through a lifecycle with your product.
Atlassian have a strong culture of exposure and presentation: engineers are regularly explaining problems, existing solutions and demonstrating understanding before they can throw new things on top. Demoing is a very important part of Atlassian culture: you have to be able to sell it with passion. Define the problem. Tell a story. Make it work. Sell with passion.
There’s a hypothesis drive development approach starting from hypothesis generation and experimental design, leading to cohort selection, experiment development, measurement and analysis and then the publishing of results. Ideally, a short experiment is going to give you a prediction of behaviour over a longer term timeframe with a larger number of people. The results themselves have to be clearly communicated and, from what was demonstrated, associated with the experiment itself.
Atlassian have a UI review process using peer review. This has two parts: “Learn to See” and “Learn to Seek”. For “Learning to See”, the important principles are consistency, alignment, contrast and simplicity. How much can you remove, reuse and set up properly so the UI does exactly what it needs to do and no more? For “Learning to Seek”, the key aspects are “bring it forward” (bring your data forward to make things easier: you can see the date when your calendar app is closed). (This is based on work in Microinteractions, a book that I have’t read.) The use of language in text and error messages is also very important and part of product thinking.
No-one works alone at Atlassian and team work is default. There’s a lot of team archeology and look at what a team has been doing for the past few years and learn from it. The Team Fingerprint shows you how a team works, by looking at their commit history, bug tracking. If they reject commits, when do they do it and why? Where’s the supporting documentation and discussion? Which files are being committed or changed together? If two files are always worked on together, can we simplify this?
In terms of the ecosystem, Atlassian also have an API focus (as Google did yesterday) and they design for extensibility. They also believe in making tools available with a focus on determining whether the product will be open source or licensed and how the IP is going to be handled. Extensibility can be very hard because it’s a commitment over time and your changes today have to support tomorrow’s changes. It’s important to remember that extending something requires you to build a community who will use the extensions – again, communication is very important. An Atlassian platform team is done when their product has been adopted by another team, preferably without any meetings. If you’re open source then you live and die by the number of people who are actually using your product. Atlassian have a no-meeting clause: you can’t have a meeting to explain to someone why they should adopt your product.
When things last for years you have to prepare for it. You need to learn from your running code, rather than just trusting your test data. You need to validate assumptions in production and think like an “ops” person. This includes things like building in consistency checks across the board.
Where’s the innovation in this? The Atlassian approach is a little more prescriptive in some ways but it’s not mandating tools so there’s still room for the innovative approaches that Alan mentioned yesterday.
Question time was interesting, with as many (if not more) comments than questions, but there was a question as to whether the idea for such a course should be at a higher level than an individual University: such as CORE, ACDICT, EA,or ACS. It will be interesting to see what comes out of this.
Today’s keynote was given by Alan Noble, Engineering Director for Google Australia and long-term adjunct at the University of Adelaide, who was mildly delayed by Sydney traffic but this is hardly surprising. (Sorry, Sydney!) Whn asked to talk about Google’s Software Engineering (SE) processes, Alan thought “Wow, where do I began?” Alan describes Google’s processes as “organic” and “changing over time” but no one label can describe an organisation that has over 30,000 employees.
So what does Alan mean by “organic”? Each team in Google is empowered to use the tools and processes that work best for them – there is no one true way (with some caveats). The process encouraged is “launch and iterate” and “release early, release often”, which many of us have seen in practice! You launch a bit, you iterate a bit, so you’re growing it piece by piece. As Alan noted, you might think that sounds random, so how does it work? There are some very important underlying commonalities. In the context of SE, you have an underlying platform and underlying common principles.
Everything is built on Google Three (Edit: actually it’s google3, from Alan’s comment below so I’ll change that from here on) – Google’s third iteration of their production codebase, which also enforces certain approaches to the codebase. At the heart of google3 is something called a package, which encapsulates a group of source files, and this is associated with a build file. Not exciting, but standard. Open Source projects are often outside: Chrome and Android are not in google3. Coming to grips with google3 takes months, and can be frustrating for new hires, who can spend weeks doing code labs to get a feeling for the codebase. It can take months before an engineer can navigate google3 easily. There are common tools that operate on this, but not that many of them and for a loose definition of “common”. There’s more than one source code control system, for example. (As a note, any third party packages used inside Google have the heck audited out of them for security purposes, unsurprisingly.) The source code system used to be Perforce by itself but it’s a highly centralised server architecture that hasn’t scaled for how Google is now. Google has a lot of employees spread around the world and this presents problems. (As a note, Sydney is the 10th largest engineering centre for Google outside of Mountain View.) In response to this scaling problem, Google have tried working with the vendor (which didn’t pan out) and have now started to produce their own source control system. Currently, the two source control systems co-exist while migration takes place – but there’s no mandated move. Teams will move based on their needs.
Another tool is a tracking tool called Buganizer which does more than track bugs. What’s interesting is that there are tools that Google use internally that we will never see, to go along with their tools that are developed for public release.
There’s a really strong emphasis on making sure that the tools have well-defined, well-documented and robust APIs. They want to support customisation, which means documentation is really important if sound extensions and new front ends can be built. By providing a strong API, engineering teams can build a sensible front end for their team – although complete reinvention of the wheel is frowned upon and controlled. Some of the front ends get adopted by other teams, such as the Mondrian UI front-end for Buganizer. Another front end for Google Spreadsheets is Maestro. The API philosophy is carried from the internal tools to the external products.
Google makes heavy use of their own external products that they produce, such as Docs, Spreadsheets and Analytics. (See, dog food, the eating thereof.) This also allows the internal testing of pre-release and just-released products. Google Engineers are slightly allergic to GANTT charts but you can support them by writing an extension to Spreadsheets. There is a spreadsheet called Smartsheet that has been approved for internal use but is not widely used. Scripting over existing tools is far more common.
And now we move onto programming languages. Or should I say that we Go onto programming languages. There are four major languages in use at Google: Java, C++, Python, and Go (the Google language). Alan’s a big fan of Go and recommends it for distributed and concurrent systems. (I’ve used it a bit and it’s quite interesting but I haven’t written enough in it to make much comment.) There are some custom languages as well, including scripting languages for production tasks. Teams can use their own language of choice, although it’s unlikely to be Ruby on Rails anytime soon.
Is letting engineers pick their language the key to Google’s success? Is it the common platform? The common tools? No. The platforms, tools and languages won’t matter if your organisational culture isn’t right. If the soil is toxic, the tree won’t grow. Google is in a highly competitive space and have to be continually innovating and improving or users will go elsewhere. The drive for innovation is the need to keep the users insanely happy. Getting the organisational settings right is essential: how do you foster innovation?
Well, how do they do it? First and foremost, it’s about producing a culture of innovation. The wrong culture and you won’t get interesting or exciting software. Hiring matters a LOT. Try to hire people that are smarter than you, are passionate, are quick learners – look for this when you’re interviewing. Senior people at Google need to have technical skills, yes, but they have to be a cultural fit. Will this person be a great addition to the team? (Culture Fit is actually something they assess for – it’s on the form.) Passion is essential: not just for software but for other things as well. If people are passionate about one thing, something, then you’d expect that this passion would flow over into other things in their lives.
Second ingredient: instead of managing, you’re unmanaging. This is why Alan is able to talk today – he’s hired great people and can leave the office without things falling apart. You need to hire technical managers as well, people who have forgotten their technical skills won’t work at Google if they’re to provide a sounding board and be able to mentor members of the team.
The third aspect is being open to sharing information: share, share, share. The free exchange of information is essential in a collaborative environments, based on trust.
“Info sharing is power, info hoarding is impotence.” (Alan Noble)
The fourth thing is to recognise merit. It’s cool to do geeky things. Success is celebrated generously.
Finally, it’s important to empower teams to be agile and to break big projects into smaller, more manageable things. The unit of work at Google is about 3-4 engineers. Have 8 engineers? That’s two 4 person teams. What about meetings? Is face-to-face still important? Yes, despite all the tech. (I spoke about this recently.) Having a rich conversation is very high bandwidth and when you’re in the same room, body language will tell you if things aren’t going across. The 15 minute “stand up” meeting is a common form of meeting: stand up in the workplace and have a quick discussion, then break. There’s also often a more regular weekly meeting which is held in a “fun” space. Google wants you to be within 150m of coffee, food and fuel at all times to allow you to get what you need to keep going, so weekly meetings will be there. There’s also the project kick-off meeting, where the whole team of 20-30 will come together in order to break it down to autonomous smaller units.
People matter and people drive innovation. Googlers are supposed to adapt to fast-paced change and are encouraged to pursue their passions: taking their interests and applying them in new ways to get products that may excite other people. Another thing that happens is TGIF – which is now on Thursday, rather than Friday, where there is an open Q and A session with the senior people at Google. But you also need strong principles underlying all of this people power.
The common guiding principles that bring it all together need to be well understood and communicated. Here’s Alan’s list of guiding principles (the number varies by speaker, apparently.)
- Focus on the user. This keeps you honest and provides you with a source of innovation. Users may not be articulate what they want but this, of course, is one of our jobs: working out what the user actually wants and working out how many users want a particular feature.
- Start with problems. Problems are a fantastic source of innovation. We want to be solving real, important and big problems. There are problems everywhere!
- Experiment Often. Try things, try a lot of things, work out what works, detect your failures and don’t expose your users to any more failures than you have to.
- Fail Fast. You need to be able to tolerate failure: it’s the flip side of failure. (A brief mention of Google Wave, *sniff*)
- Paying Attention to the Data. Listen to the data to find out what is and what is not working. Don’t survey, don’t hire marketing people, look at the data to find out what people are actually doing!
- Passion. Let engineers find their passion – people are always more productive when they can follow their passion. Google engineers can self-initiate a transfer to encourage them to follow their passion, and there is always the famous Google 20% time.
- Dogfood. Eat your own dogfood! Testing your own product in house and making sure that you want to use it is an essential step.
The Google approach to failure has benefited from the Silicon Valley origins of the company, with the approach to entrepreneurship and failure tolerance. Being associated with a failed start-up is not a bad thing: failure doesn’t have to be permanent. As long as you didn’t lie, cheat or steal, then you’ve gained experience. It’s not making the mistake, it’s how you recover from it and how you carry yourself through that process (hence being ethical even as the company is winding down).
To wind it all up, Google doesn’t have standard SE processes across the company: they focus on getting their organisation culture right with common principles that foster innovation. People want to do exciting things and follow new ideas so every team is empowered to make their own choices, select their own tools and processes. Launch, iterate, get it out, and don’t hold it back. Grow your software like a tree rather than dropping a monolith. Did it work? No? Wind it back. Yes? Build on it! Take the big bets sometimes because some big problems need big leaps forward: the moon shot is a part of the Google culture.
Embrace failure, learn from your mistakes and then move on.
The Australasian Software Engineering Conference has been around for 23 years and, while there have been previous efforts to add more focus on education, this year we’re very pleased to have a full day on Education on Wednesday, the 9th of April. (Full disclosure: I’m the Chair of the program committee for the Education track. This is self-advertising of a sort.) The speakers include a number of exciting software engineering education researchers and practitioners, including Dr Claudia Szabo, who recently won the SIGCSE Best Paper Award for a paper in software engineering and student projects.
Here’s the invitation from the conference chair, Professor Alan Fekete – please pass this on as far as you can!:
- Keynote by a leader of SE research, Prof Gail Murphy (UBC, Canada) on Getting to Flow in Software Development.
- Keynote by Alan Noble (Google) on Innovation at Google.
- Sessions on Testing, Software Ecosystems, Requirements, Architecture, Tools, etc, with speakers from around Australia and overseas, from universities and industry, that bring a wide range of perspectives on software development.
- An entire day (Wed April 9) focused on SE Education, including keynote by Jean-Michel Lemieux (Atlassian) on Teaching Gap: Where’s the Product Gene?