Tag Archives: Work

Work

How I have been using knowledge graphs

Within a week of using Roam Research’s implementation of a knowledge graph or Zettlekasen I decided to sign up because there was something special in this way of organising information. My initial excitement was actually around cooking, the ability to organise recipes around multiple dimensions (a list of ingredients, the recipe author, the cuisine) meant you could both search and browse by the ingredients that you had or the kind of food you wanted to eat.

Since then I’ve started to rely on it more for organising information for work purposes. Again the ability to have multiple dimensions to things is helpful. If you want to keep some notes about a library for handling fine grained authorisation you might want to come back to that via the topic of authorisation, the implementation language or the authorisation model used.

But is this massively different from a wiki? Well a private wiki with a search function would probably do all this too. For me personally though I never did actually set up something similar despite experiments with things like Tiddlywiki. So I think there are some additional things that make the Zettelkasten actually work.

The two distinctive elements missing from the wiki setup are the outliner UI and the concept of daily notes. Of the two the daily notes is the simplest, by default these systems direct you a diary page by default, giving you a simple context for all your notes to exist in. The emphasis is getting things out of your head and into the system. If you want to cross-link or re-organise you can do so at your leisure and the automatic back-referencing (showing you other pages that reference the content on the page you are viewing) makes it easy to remind you of daily notes that maybe you haven’t consciously remembered you want to re-organise. This takes a good practice and delivers a UI that makes it simple. Roam also creates an infinite page of daily notes that allows you to scroll back without navigating explicitly to another page. Again nothing complicated but a supportive UI feature to simplify doing the right thing.

The outliner element is more interesting and a bit more nuanced. I already (and continue to use) an outliner in the form of Workflowy. More specifically, I find it helpful for outlining talks and presentations, keeping meeting notes and documenting one to ones (where the action functionality is really helpful to differentiate items that need to be actioned from notes of the discussion). The kind of things where you want to keep a light record with a bit of hierarchical structure and some light audit trail on the entries. I do search Workflowy for references but I tend to access it in a pretty linear way and rarely access it without a task-based intention.

Roam and Logseq work in exactly the same way, indeed many of the things I describe above are also use-cases for those products. If I wanted to I could probably consolidate all my Workflowy usage into Roam except for Roam’s terrible mobile web experience. However there is a slight difference and that is due to the linking and wiki-like functionality. This means you can have a more open discovery journey within the knowledge graph. Creating it and reading, I have found, are two different experiences. I think I add content in much the same way as an outliner but I don’t consume it the same way. I am often less task-orientated when reviewing my knowledge graph notes and as they have grown in size I have had some serendipitous connection making between notes, concepts and ideas.

What the outliner format does within the context of the knowledge graph is provide a light way of structuring content so that it doesn’t end up a massive wall of text in the way that a wiki page sometimes can. In fact it doesn’t really suit a plain narrative set of information that well and I use my own tool to manage that need and then link to the content in the knowledge graph if relevant.

In the past I have often found myself vaguely remembering something that a colleague mentioned, a link from a news aggregator site or a newsletter or a Github repo that seemed interesting. Rediscovering it can be very hard in Google if it is neither recent nor well-established, often I have ended up reviewing and searching my browser history in an almost archaeological attempt to find the relevant content. Dumping interesting things into the knowledge graph has made them more discoverable as individual items but also adds value to them as you gain the big picture understanding of how things fit together.

It is possible to do achieve any outcome through any misuse of a given set of tools but personal wikis, knowledge graphs and outliners all have strengths that are best when combined as much as possible into a single source of data and which have dedicated UIs for specific, thoughtful task flows over the top. At the moment there’s not one tool that does it all but the knowledge graph is the strongest data structure even if the current tools lack the UI to bring out the best from it.

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Software, Work

The problem with developer job titles

Job titles are hard. This exchange on Twitter prompted a few thoughts that I couldn’t quite fit into a few smart-arsed twits.

In Chris’s Tweet he mentions that engineer is a co-opted title and that engineering is a discipline in its own right which most software groups don’t subscribe to because they aren’t really trying to do engineering. Not that this is a criticism but there is a massive difference between building a bridge or a road and creating a new web service. For a start there is a lot more established practice, science and understanding in physical engineering and more established and understood formal qualifications.

When I briefly worked in government helping create the Digital Careers framework people who were associated with Defence rightly objected to the confusion between software “engineering” and other engineers within professional frameworks. No-one is going to ask a developer to fix the combat damage on an airfield. I’ve previously joked that if we were honest we’d talk about “software overengineers” given that most developers struggle to find the simplest thing that works.

For the framework we settled on “developer” for people who wrote code and inconsistently used “engineering” for operational roles. I think on the basis that they created “infrastructure” where maybe the analogy makes a sort of sense.

I would also have gotten rid of “architect” if I’d had a chance; for exactly the same confusion but that term was too deeply embedded and still is a badge of prestige within the industry. Even now in the commercial world I have experienced hires wanting to be involved in “architecture” (and sadly not wanting to help me remodel my ground floor).

In Chris’s tweet he asks about what happened to the title “Programmer”. When I started in the industry this was indeed the coveted title and ideally I still think of myself this way even though it’s blatantly not true in the same way now.

However the issue with being a programmer is that jobs that literally involve just programming are few and far between. When I started in the industry the experienced developers were people who were at the tail-end of mainframe programming and a bit of what they were doing was still persuading machines to perform the tasks that were needed. The end was already in sight for pure programming jobs though. Some of my first professional programming work involved networking, a slightly dirty topic for the mainframe types.

Nowadays the emphasis is on understanding the domain space you are working on as well as the technical aspects of programming. I prefer the term “developer” (as others do) with the implication of being someone who develops systems of value via the medium of technology.

However that term also has its problems. When I worked at the Guardian I had a personal SEO battle with the Pune-based property development group for the search term “Guardian developers”. That battle seems to have been won now via sub-domain. This seems to be true more generally and now it is property developers who are having to use the prefix “property” on their job titles.

For a new profession not even past it’s first century, creating our professional lexicon is always going to be hard but in borrowing titles so shamelessly we are always creating problems for ourselves.

Programmer is probably the closest, truest name for what most of us do at the core of our role. For web developers though, assembling the typical bricolage of libraries and tooling is often an exercise in minimal programming and maximum duct taping. Perhaps it fairest to say that we are “software assemblers”, expect that might get confused with, you know, assemblers. Painful.

So in the end most of us are expected to bring capability in programming within teams that are creating technological systems of value. As long as programmers realise that programming is not the activity of value in itself then maybe we don’t need to worry so much about titles.

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Work

Please stop showing me “the data”

This isn’t a reactionary rant against data-driven decision making and it isn’t about nostalgia for gut-driven benevolent dictators.

Instead it is an appeal for reason to play an equal part in decision making.

The seed of this post was planted by a keynote Ines Montani gave at EuroPython. At the time I was more interested in her central argument that paying customers are the most important metric a business can have.

But in part of the talk she talks about the cliche of “show me the data”, a phrase that I think originated at NASA where, in context, it makes a lot of sense but when transplanted to the world of small business quickly becomes expensive, slow and farcical.

In part of her talk Ines mentioned that when making decisions on how to run a small business there shouldn’t be a need to provide data for or against every decision. “Why can’t we use reason?” she asked.

The question had huge resonance for me. The emphasis on data-driven decisions in businesses has not led to improved data or statistical literacy. Instead it has led to the generation of fig-leaf numbers, impenetrable spreadsheets of data as obfuscation and irrelevant but voluminous data collection. I see little evidence that decision-making is better.

It has also exposed the idea that the problem is data collection. The more information we collect then the more it feels like the more any decision can be justified or any course of action advocated or vetoed. Interpretation, selection and analysis of the data is more important than ever, and this at its heart requires reasoning.

Reason is different from “common sense” in that it should be produce self-consistent decision making that can be justified and interrogated. Reasoning is a process applied to instinct, insight, intuition, experience and knowledge.

So please don’t show me your data, explain your decision instead.

 

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Work

Agile: are scrummasters the masters?

One of the fault lines in modern Agile development remains the purpose and application of process. For me the fundamental conflict between a developer and a “scrummaster” is to do with what the main purpose of that role is. Scrummasters often profess a servant manager role for themselves while actually enacting a traditional master hierarchical function.

The following is the acid test for me. The servant manager is one who takes the work I am doing and expresses it in a form that allows people outside the team to understand what I am doing, the progress I have made on it and make predictions about when my work will be complete.

The traditional manager instead tries to control my work so that it fits neatly into the reporting tools that they want to use. They don’t hesitate to interfere, manipulate and control to make their life easier with their own superiors.

Calling yourself a servant manager but then telling people how to structure their work is paying lipservice to a popular slogan while continuing a strand of managerial behaviour that has been proven to fail for decades.

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Work

Agile software development defers business issues

My colleague Michael Brunton-Spall makes an interesting mistake in his latest blog post:

much of our time as developers is being completely wasted writing software that someone has told us is important.  Agile Development is supposed to help with this, ensuring that we are more connected with the business owners and therefore only writing software that is important.

Most Agile methodologies actually don’t do what Michael says here. Every one I’ve encountered in the wild treats it as almost axiomatic that there exists someone who knows what the correct business decision is. That person is then given a title, “product owner” for example and then is usually assigned responsibility for three things: deciding what order work is to be done, judging whether the work has been done correctly and clarifying requirements until they can be reduced to a programming exercise.

That’s why it was liberating to come across System Thinking which does try to take a holistic approach and say that any organisation is only really as good as its worst performing element. Doing that does not eliminate all the process improvements in development that Agile can provide but also illustrates that a great development team doing the wrong thing is a worse outcome than a poor development team doing the right thing.

The invention of the always correct product owner was a neat simplification of a complex problem that I think was probably designed to avoid having multiple people telling a development team different requirements. Essentially by assigning the right to direct the work of the development team to one person the issue of detail and analysis orientated developers getting blown off-course by differing opinions was replaced by squabbling outside the team to try and persuade the decision maker. Instead of developer versus business the problem was now business versus business.

Such a gross simplification has grave consequences as the “product owner” is now a massive point of failure and few software delivery teams can effectively isolate themselves from the effects of such a failure. I have heard the excuse “we’re working on the prioritised backlog” several times but I’ve never seen it protect a team from a collectivised failure to deliver what was really needed.

Most Agile methodologies essentially just punt and pray over the issue of business requirements and priorities, deferring the realities of the environment in the hoping of tackling an engineering issue. Success however means to doing what Michael suggests and trying to deal with the messy reality of a situation and providing an engineering solution that can cope with it.

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Work

Breaking the two-week release cycle

I gave a lightning talk about some of the work I did last year at the Guardian to help break the website out of the two-week release cycle and make it possible to switch to a feature-release based process. It’s the first time I’ve given a public talk about it although I have discussed with friends and obviously within the Guardian as well where we are still talking about how best to adopt this.

I definitely think that feature-releasing is the the only viable basis for effectively software delivery, whether you are doing continuous delivery or not.

In a short talk there’s a lot you have to leave out but the questions in the pub afterwards were actually relatively straight-forward. The only thing I felt I didn’t necessarily get across (despite saying it explicitly) was that this work was done on the big Enterprise Java monolith at the Guardian. We aren’t talking about microapps or our new mobile platform (although they too are released on a feature basis rather than on a cycle) we are talking about the application that is sometimes referred to as the “Monolith”. It was really about changing the world to make it better rather than avoid difficulty and accepting the status quo.

Feature-releasing has real benefits for supporting and maintaining software. On top of this, if you want to achieve collective team effort then focussing on a feature it going to better rather than doing a swath of work in a mini-waterfall “sprint”. The team stands a better chance of building up a release momentum and cadence and from that building up stakeholder confidence and a reputation for responsive delivery.

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Programming, Work

Optimizely testing like a hacker

At work we use Optimizely and I am a fan of the product; I think it has had a massive impact on the way we work and should really help guide us to decide what we choose to do.

However I am not a product manager, user testing expert or statistician (that last part is a lie, I’m a statistician who hasn’t done any stats for seventeen years) I am a dirty hacker programmer and I use Optimizely in a way that probably makes my colleagues weep but which I think actually makes it more valuable as a product. I want to talk about breaking some of the common rules that people put up around this testing.

Note that you need to understand what you’re doing here, I am not recommending this if you are new to the product or multi-variate testing. You also need a good stream of traffic to work on. I do, this is working out for me. One piece of good practice I would keep is: decide how you are going to judge the test before you start it and don’t change your measure once you’ve started. If it is clear your initial metrics aren’t helpful, design a new test. The knowledge you’ve gained is valuable for formulating the right measures.

Don’t change the test once you’ve started it

Only once the test has started can you understand what the problem you are dealing with is and what responses you can take to the issues. If you have a question about what is happening in the test feel free to create a new variation (always with a good name!) and throw it into the mix. I sometimes start with one variation and end the test with nine. It’s better to test immediately than speculate.

Changing a variation (no matter how tempting) is dangerous though as you’ll have to remember the differences and when you applied them. I prefer to spawn variations to changing an in-flight variation. Of course fixing bugs and unintentional consequences is fine. You’re looking at the long term rate not the initial performance.

Don’t change the traffic

I’m not sure this is a general shibboleth but I play around with traffic massively during the test. The great thing about Optimizely is that it takes care of the math so feel free to mix the allocation of traffic freely. If you have a run-away winner early on then don’t be afraid to feed the majority of traffic to it.

Make the test work for the whole audience

I don’t believe in this, make the test work for the easiest audience segment to access. I frequently only test on modern browsers. If you find a trend then shock, horror it often works for the whole audience. It’s about fast feedback not universal truth.

The biggest advantage is that you can use CORS-compliant browsers to do bigger changes to the pages under test.

Don’t change the underlying content

If you take your best performing variation and apply it to the page then the “Original” variation should trend to the variation. If it doesn’t then you know something is up with your measuring. I actually think it is really helpful to make a succession of changes to the base content, based on the tests until the Original variation is performing better than the individual variations.

Once Original is top performing variation you can stop testing the page.

A/A testing has problems

So what? Optimizely has a few issues, you need to deal in big numbers. A/A can be helpful but if you are working in five digit numbers or double-digit percentages then don’t worry about the noise.

Tests have to look good

If your theory is accurate it absolutely does not have to look good. If you are worried that your hypothesis is not working because of the visuals: get over yourself and admit that the idea was weak and you need to rethink it.

I like to start off all variations looking a bit crappy and then seeing whether they can be outperformed by an improved appearance. Often the answer is no; there is a rule of diminishing returns on the appearance of a variation. Things get over-designed on the web all the time. However by trying better looking variations in increments you know exactly how much effort to invest.

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Web Applications, Work

Guardian May 2013 Hackday

You can see the reportage in these two liveblogs: Day 1 and Day 2 (note the terrible naming conventions). The theme of the hackday was “growth”. For the most part I took the theme to mean growth hacking and I did a lot of work along those lines which is difficult to talk publicly about.

However my prior lunchtime hacks had revealed to me that one of the fundamental problems the Guardian has is the volume of content it produces. This is not inherently a bad thing but the key thing to understand is that there is vastly more content than can fit onto what are called “fronts” in the jargon. A front is something like the front page of the site or the Environment section. These fronts produce a lot of traffic to content and for regular readers they are the essential navigation tool for the Guardian’s content.

Therefore I was interested in how we consider the dimension of time and perhaps use it to our advantage to help present content. This aspect of my hackday work is more open because actually I need a lot of help to understand to and because I’ve made some effort to try and use the public Content API rather than our internal content.

I called this work the “Time Trilogy” because it consists of three web apps that each use time as a way of accessing Guardian content.

The three apps are Guardian Word Count which was the original and gives you a sense of the challenge of navigating the content. It is also pretty fun to watch during the day and see the words tick up. So the Word Count spawned TickTickTick and Guardian In Review. TickTickTick is really a daily content explorer and was the first tool I needed to start sorting and exploring the breakdown of what we produce. It is a tool at its heart for exploring the daily news cycle. In Review is slightly different, it takes the one hundred most popular pieces of content over the last seven days and renders it. Initially I wanted it to be a kind of automatically generated magazine but actually looking at what people liked meant that I couldn’t make my initial idea work. People really like videos of meteors and Russian car crashes. What it is now is a way to explore material in the medium term, for content that perhaps has left the news cycle but is still relevant.

Neither app is really finished and the way I work is that I am very reliant on having working software to understand what I am doing and what is wrong or right about my approach. TickTickTick is much closer to being a complete product than In Review and it is providing more insight into the nature of the content being produced. For example there is a massive cluster of material between three and five minutes long.

I am going to continue to work on the apps because they help give me feedback into my work and ultimately these prototypes and toys tend to graduate into working components or theory on the main site itself. I may blog a bit more about them individually as I move them closer to something that genuinely creates value. I’m curious about feedback but acting on it is limited by my aims for the apps and realistically the time I have available.

I also wanted to talk a little bit about how I was working this hack day because I decided to reject advice and work solo rather than part of a team (although I did a little bit of backseat driving on the online magazines product and I did come up with the idea that actually won the hackday (and will hopefully be implemented and awesome)). Working alone does mean that your creations are going to be quite rough but it helps cover a lot of ground, I ended up doing five hacks and working on a total of seven. Working with other people means communicating well whereas solo you just need to express what you want very quickly.

My preferred tool for these kinds of hacks is Python on App Engine, which is what I use for my lunchtime hacks and for which I have a standard application template. With each new application that I do I can start to move the common patterns into the template. To avoid having to faff around with testing I use a loosely functional paradigm that I’ve carried over from Wazoku. It generally works quite well but there are a lot of rules to doing it.

This time around I was doing a bit more frontend work than my day job requires because I was working solo. Again having the startup experience was useful because I was more rediscovering a skillset than learning it. Hacks also means selecting your platform and choosing for optimal output.

For that reason I only targeted Firefox and Chrome (Firefox was actually easier to develop for in terms of standards) and I made liberal use of client-side Less and Coffeescript. I was impressed with how good the error-handling was in both. An obscure bug can wipe out all the productivity gains of a higher-order language but both worked great for me.

On top of that I tried experimenting with the new departmental standard of SMACSS (or at least my cherry-picking of it) and I made a lot of use of both Knockout and Bacon.js.

When I say I made use of SMACSS essentially what I did was namespace my classes to produce simple selectors. This did get me out of a problem I had in In Review so while it is truly the ugliest CSS standard and I suspect in time we may come to hate its rejection of rich functionality I concede that it is effective. Expect to see some of it applied to the main website sometime soon.

Knockout isn’t that popular in the department due to performance issues at a particular level of complexity but for me it did a brilliant job of simply syncing the visual DOM to the data feeds. I was really happy with it, other people were using AngularJS for more dynamic applications but they also had a lot more code than I did and again working solo less is so much more.

Bacon.js was really interesting. A lot of my approach to Javascript is functional and event-based but so far the events have been manually worked via jQuery. Bacon made it easier to create event sources with generic handlers and I probably didn’t use 10% of its full features. I’m curious to see what the rest of the department thinks of it but for my hacks it has definitely earned a place.

It was nice to do something outside the run of normal work and one thing that is quite cool about the hackday is that you can use it to tackle a technology that is entirely new to you and not have to worry about whether you succeed or fail.

Next time (May I believe) I think I want to learn about browser plugins as this is a way of producing better functionality for the Guardian without the hassle of having to make it work for the general population of browsers. Some people’s hacks this time around could have been released to the app/plugin stores and we could have been getting valuable user feedback by now.

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Work

The BBC “across”

The term “across” is absolutely endemic at the BBC and because so many people in UK media pass through the BBC it also crops up across the sector generally. Although I was initially scornful of it as a term I have long since caved to the inevitable and use it as well.

Being “across” seems to have originated in the fact that the BBC have multiple media streams and when a journalist talks about being “across” things they might well mean that they are producing pieces on a topic across multiple media, say television and radio. It might also mean that they are tracking a breaking story and are watching other media outlets for what they are saying about a story.

Outside this context though the word more or less means “understanding”. So when someone from the BBC is “across” something it means they understand it, sometimes if they are “across” it enough they can also make decisions about it. When someone isn’t “across” something then they do not feel they understand it or they are unprepared to answer questions about it.

Ironically this meaning then seems to seep back into broadcast journalism and I have heard journalists on air saying that they are “across” developments such as the formation of the coalition.

At this point “across” feels kind of ubiquitous apart for people who have been raised in single stream media so I think it’s worth you being “across” it too.

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Work

Success looks like success

One useful thing I have learnt by working in an early stage startup is that success looks and feels like success. If you are doing something and it does not seem like it is being successful then it isn’t. This might seem like something that is completely obvious but it is really not.

There are many kinds of “not success” (or failure to give it it’s true but cruel name). The worst is the “almost success” where something works and delivers on its promise, but not very well. Almost success creates this dilemma where perhaps with a little iterating and more effort you could turn it into a real success.

When this kind of success creates ongoing liabilities in terms of customer expectations then the situation is even worse. If you try and cancel things or do a lean startup pivot then you are guaranteed to alienate your current customers with only the hope of gaining more of the true customer base you originally envisaged.

Weak success is a little better, weak success is not outright failure but is so unsuccessful that people completely understand if you want to knock it on the head.

In a large organisation though things are far more difficult. Both almost success and weak success are ironically more dangerous in a big and profitable organisation due to two factors: personal reward and hidden cross-subsidy.

If someone achieves any degree of success in an organisation they expect to be rewarded for it. Perhaps justifiably, perhaps not. Either way there are serious morale implications if at the end of period of exertion by any group or individual you kill off the object of all their efforts, no matter how rational and correct that decision may be.

In general people are conflict averse so they prefer to reward almost success and move on to other activities that might be more successful.

However a set of almost successful activities all have real costs and the minute any of them fail to generate revenue sufficient to carry their costs then you are in the world of the hidden cross-subsidy where all your almost successful projects and products start to drag down any aspect of the business that is profitable.

It is a tar pit that can be difficult to escape unless you have really good accounting to see where money is coming and going. It is only easy in a startup because generally you only have one product and therefore all profit and loss is easy to tally and attribute.

So everything in your business that is not a success is a potentially business-killing failure. And for that reason, even though it is hard, you need to end almost success just as much as you need end failure.

The question to ask is not “Is this successful?”; if you are asking that question then the answer is simply no. If you are successful then the question you ask is “How are we going to deal with all this success?”.

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