I’ve noticed this phrase creep its head above ground when someone is rationalizing a strategy or tactic that is initially highly inefficient and will create headaches in the future, but at the delight of increased revenue/traffic/whatever.

It has now entered my cage of canaries. When I hear this excuse uttered, it is a signal that something has not been properly thought out to the fullest extent necessary to make a sound decision. It triggers a personal moment of reflection; it prompts me to take time to analyze all the variables at hand.

Let’s break down the phrase’s two key parts.

“Will Be” — Future tense prediction of some turning point. But when? Can you tell me when it will shift from an acceptable poor decision to an unacceptable one? You’re also assuming that at some point it will shift.

“Good Problem” — A subtle oxymoron. You’re qualifying a decision as a positive problem, one that’s ok to deal with, because of the net good its causing. While not a ridiculous idea on its own, it assumes that the future problem will inherently be good. And good, in this context, is obnoxiously generic. Good how? To what extent? Relatively compared to what?

Next time you hear this phrase, stop and think. Notice if it’s being used as a way to validate or rationalize a side of an argument. Or as a way to sidestep further questioning or discussion of a point. You’ll come to realize it’s a red flare for poor planning.

Challenge 1: De-coupling the Reptilian Brain

We all understand the Triune Brain concept. It’s an easily explainable story, and equally practical. It applies to basically everything.

So it’s difficult to prevent an untrained JTBD thinker from scaling down to lizard thought.

Far too often, they will associate the “job to be done” with some core primal outcome. Of course it’s always about sex, food, sleep, poop, pride, fear, love, or predicability. But that doesn’t help us properly assess the job to be done and subsequently design a product or service someone would hire.

Instead, I challenge them to look at the situation. Then I urge them to describe what capabilities are needed to solve the problem. That’s the job to be done.

Challenge 2: Situation Taxonomy

Speaking of the situation, I find it difficult to properly define its scope. We’ll scale up and down, often for far too long, in search of the real and complete situation.

Let’s take the classic milkshake example. What would you say is the situation? Some options, in order of broadest to narrowest:

• I’m hungry
• I’m hungry and in my car
• I’m hungry and in my car and by an on-ramp
• I’m hungry, in my car by an on-ramp and don’t want to be hungry again in a few hours
• I’m hungry, in my car by an on-ramp, it’s 8am and I don’t want my breakfast to be so light that I’m hungry again by lunch
• I’m hungry, coming up to an on-ramp in my car at 8am, I want to be full until lunch, have a free hand and cup holder, $3 in cash, and don’t care about my next dental check up

And what if I’m hungry, but 10 minutes after I get on the free way? What situation beholdens to other situations?

What’s the real situation? It’s tough to draw a line. When do core parts of the situation transition to simple attributes? I see the uneasiness of being unable to answer happen all the time.

My response is that it doesn’t matter. Just pick one. Eventually you’ll circle in on a true description of the situation, but that only happens after deeper consideration. Until then, don’t let the taxonomy of the situation hold you up.

Challenge 3: Comfort with 2D Thinking

Extending the thought from Challenge 1, I see linear thinking as a problem. People will set up a progression, almost like mental dominos, and strive to follow point to point. The deeper desire here is to find the “root”. Without realizing, they think that A causes B causes C etc. So obviously the goal should be to find A, then solve for A. They think solving A is the job to be done.

But that’s not the case. It is not linear. (This is how we get mixed in with the lizard brain thinking.) Even if there is a chain of cause and effect, a major error happens along the way: we discount the importance of B, C, D, and so on. We ignore them.

Instead, I urge 2D thinking. Solving JTBD is understanding relationships and connections between ideas. A map is a better framework. Fill in areas for empathy, cost, demographics, and so forth. This way you won’t discount anything you document. Eventually you’ll understand the situation in more detail, and how to approach the solution.

Challenge 4: Where Do Attributes Belong?

The object? The situation? The person? The job? It can be confusing which attributes belong where.

I don’t have a sound explanation for this challenge yet, but so far I have taken a similar approach to Challenge 2: it doesn’t really matter as long as your documenting, contemplating, and testing.

The song I probably listened to most. The song I thought was best constructed. The song that sounded the best. And a great music video. Tough to beat this one.

2. “Baby” – Ariel Pink

I know it’s a cover, but hot damn it’s good.

3. “Her Fantasy” – Matthew Dear

My favorite “party” song. I forced it on everyone every party I went to so we didn’t have to listen to Usher. I have no regrets.

4. “Myth” – Beach House

This one means a lot to me. It’s easily the most emotional of the group. It’s just a touch too short, or else it’d be number one.

5. The Fall – Rhye

Who? What? Only a few singles out, but she’s great.

6. “House Shape” – Mount Eerie

This and “Through The Trees pt. 2″ made for a great album. This one was my favorite of the two though.

7. “Oblivion” – Grimes

Best song off the album of the year for me. It beats out “Genesis” because it has a better music video.

8. “Feels Like We Only Go Backwards” – Tame Impala

Alright, I get it.

9. “Modern Driveway” – Luke Abbott

Title track from his five-song EP. The song I listened to most through headphones while walking. It makes me feel happy and refreshed when it’s done.

10. “Flower Lane” – Ducktails

This song was an early single off Matt’s full length album coming out early 2013. He knows how to tweak my heart.

Honorable Mentions

“Lover” – Blondes
https://soundcloud.com/blondes/lover

Great “get in the groove” song.

“Sweetie & Shag (The Field Remix)” – Battles

No list is complete without Four Tet or The Field in my mind.

“Cooking Up Something Good” – Mac DeMarco

Late 2012 entry. Glad I found him.

“Headcage” – Matthew Dear

Matthew Dear had two spectacular singles. This wasn’t quite as good as “Her Fantasy”, but it’s a blast.

“Depak Ine” – John Talabot

When music was sparse in Spring, I found myself listening to this album more than I probably should have. Part of the reason was because I could not get this song out of my mind. It’s fun.

2) Beach House – Bloom
With subjective rankings, often we have personal reasons for rating something higher or lower. This year, Bloom is overloaded with personal moments that admittedly puts it higher than others.

See, I share a lot of music with my lovely wife, Rena. Most of the time it’s a miss, but once in a while I hit a bullseye that becomes something fun to share with her. In the past, Animal Collective, Passion Pit, Grizzly Bear, and Real Estate were major successes. (Sadly, Grimes is not!) Well, this year Beach House was the hit, which I parlayed into an introduction to her first music festival, Pitchfork in July 2012. Beach House was tremendous closing out a fine summer Saturday, a day we’ll soon not forget.

The duo’s impact didn’t stop there. During their tour, they stopped in Milwaukee to play at The Pabst the weekend of our one-year anniversary, and promptly blew our minds. One of the better shows I’ve seen.

So what about Bloom itself, beyond just seeing it live? It’s a style all its own, and it doesn’t deviate from it. So if you like the style, you’ll love the album. If you struggle to get past the first song, everything else will be difficult. For me personally, it’s great summer music.

3) Luke Abbott – Modern Driveway
Luke is my little gem. I found him via a Four Tet remix in 2010. Kieren covered Holkham Drones in a two-hour DJ set. The sound was so unique I had to find out the source. After much research, I discovered Luke. This year saw him release two separate EPs, one in summer and one in winter. Frankly, the winter EP was only average. But summer’s effort, Modern Driveway, was my second most-played album this year. Five songs to play anywhere, anytime. I always feel good about tomorrow when I’m done listening.

4) Grizzly Bear – Shields
Not as good as Yellow House nor Vecktamist. I see a lot of Modest Mouse in them—the history, not the sound. The gritty, folksy, honest, unpolished sound that made their first work so real is slowly giving way to nicer studios and evolving musical ambitions, resulting in music that is well done but missing heart. But it’s fun and well crafted, and guldarnit, I play it loud every time.

5) Lotus Plaza – Spooky Action At A Distance
Late entrant. Deerhunter’s Lockett Pundt sure does do simple, strong bedroom rock well. Spooky rose up my list as I realized how much I love Deerhunter’s sound. Retrospectively, I don’t praise Halcyon Digest enough. This album is the closest thing to Deerhunter’s sound, and included heartfelt personal anguish. This one is filed under “I didn’t realize I liked it this much until I thought about it.”

6) Matthew Dear – Beams
I’m a Matthew Dear apologist. Why can’t I find more Matthew Dear fans? Beams did not get a lot of pump, both by press or peers, but I loved it. A few of my favorite dance tracks lead the charge—if you haven’t given “Her Fantasy” or “Headcase” a good strong listen to on a Friday night before you’re about to meet friends, you’re missing out.

7) Tame Impala – Lonerism
Alright, I get it.

8) Lower Dens – Nootropics
Man I love these guys. “Brains” is one of the best singles of the year. They could have risen higher, but quality really drops after “Propagation”. All good stuff, but to go from the perfection of the first four tracks to the average display in the last six was disappointing.

9) Mac DeMarco – 2
Weird and fun.

10) Blah
Couldn’t even make it to number 10. I’m proving a point: this was a disappointing year in music for me. I look back at years past—like the best-music-year-ever 2010—and scratch my head why I couldn’t find as many diverse works of art this year. Frankly, only the top three albums on this list will stay in my roation long-term. Everything else is just average and I’ll revisit in a couple years.

Another way to phrase it: I like to collect vinyl records, but I make it a point to only buy albums that I hold in high regard and wish to play 30 years from now with my kids. Grimes, Beach House, and Luke Abbott were the only albums this year I plan to purchase. Everything else is relegated to MP3 consumption.

It’s striking to me how many bands, with past music I adored, produced clunkers this year:

• Animal Collective (so, so bad)
• Blondes (Touched EP made my top 5 in 2010, think about that! Terrible LP follow up)
• Lower Dens (could have been better)
• Matthew Dear (could have been better)
• Grizzly Bear (could have been better)
• Nada Surf (meh)
• Bear In Heaven (lost what made them great)
• AIR (not AIR like)
• Of Montreal (nothing catchy)
• Sleigh Bells (not as good)
• Andrew Bird (forgot about it)
• The Shins (commercial music)
• Sigur Ros (boring)
• Sun Kil Moon (good, not great)
• Ariel Pink’s Haunted Graffiti (great singles, always too much wink wink nudge nudge; very frustrating music)
• The xx (also boring)
• Ben Folds Five (he should stop)
• Tame Impala (I honestly think Innerspeaker was much better)
• Crystal Castles (they keep getting weirder)

I’m sure there are others I missed, which proves the point further.

And the biggy… Four Tet! I appreciate Kieren Hebden’s adaptation the most. He moves with what interests him. So Pink gets a pass because this year he was simply more interested in making club music. But boy what a letdown. Let me be clear: Four Tet is my favorite musician of all time. The shear amount of beautiful music he makes is staggering. It’s remarkable how he can make music as uplifting and positive as Bob Marley without using lyrics. So any year with a Four Tet album is a good year. But Pink is easily his worst effort to date.

Before I part ways, there are several musicians I would like to give a hat tip to. They produced great music, but simply did not resonate with me, so did not make my list.

• Frank Ocean
• Jack White
• Godspeed You! Black Emperor
• Kendrick Lamar
• Sharon Van Etten
• Norah Jones
• Fiona Apple
• Yppah

I’m looking forward to 2013.

We have since ported it to a live, independent experience available at Nodal.me. For more information about the project as a whole, check out Matt’s release post.

It’s a single line in space that starts and ends. You never know where you are on that line at any given time. You can be listening to a podcast and you won’t know that there are 42 minutes left just by listening—you need the aid of a screen or someone telling you.

You have no idea what content is ahead of you. You only know what content was behind you if you happend to listen and remember it. It’s impossible to scan or skim. It’s impossible to summarize.

Advanced navigation is impossible. You simply play and sound marches forward until it stops.

Unfortunately, most audio design focuses on this single dimension. But the secret to better audio user experience is to think two-dimensionally.

Let’s work backwards. Since audio is a single dimension, it only has one axis, the X axis, commonly linked to “time”. That is one thing we do have with audio, specifically digital audio. A single point on the axis maps to a timestamp. This is the only card dealt to designers, but it happens to be the key to unlocking a second dimension.

If we have a timestamp, we can create a symbollic link at that point in time to endless metadata types.

• This person was talking then.
• These people were not talking.
• I clicked a button at that moment.
• An image or file was uploaded or downloaded.
• This was the active state of a specific state machine.
• These were the inactive states.
• The audio had these types of levels and frequencies.
• This unique action was conducted within 5 seconds of that timestamp.
• The audio file is related to this domain object at that point in time.
• And these are the preferences and attributes of that object.
• This time is related to these other times in the same call. And those other times in several other calls.
• And the list goes on—it’s virtually limitless.

Now that we have the metadata and relationships, we can begin to use the tools in our designer’s toolbox to craft ways to navigate the timestamps.

Conceptually, we are adding bulleted lists and headers, boldness and contrast, color and grid. And built within an existing framework—e.g. email, project management tools, CRMs—the ways to get to a specific moment of an audio stream become intuitive and simplified.

I believe audio does not play a bigger role within digital productivity tools because it is cumbersome to consume. Ultimately, we prefer the brevity and flexibility of text to the enhanced emotional intelligence of audio. But I also believe it is possible to bring a the UX benefits of text to audio by combining the two worlds. The way to do that is to think two-dimensionally.

Symposia has been a fun project. It’s a standard conference calling tool similar to GoToMeeting, WebEx and ÜberConference, but has the unique added value to record the call and tie all notes back to the specific moment of the conversation. Participants can review the call by navigating the one-dimensional audio stream in two-dimensional visual space. Another way to say it is Symposia adds bulleted lists, colors, boldness, and margin to a dull MP3 file. You can now skim recorded phone conversations like you would a memo or Google search results.

We designed around the job of once in a while trying to remember a specific conversation with colleagues or customers.

This novel approach has been valuable to some. It’s like Gmail: when you need to find a specific message amongst your thousands of threads, you’re really glad it’s there. But like Gmail, it turns out the review action is seldom used relatively speaking to other features. We still live in a transport world, and users will conduct 10+ calls before they review one. Not unlike composing 10+ messages or replies in Gmail before you search for that missing receipt.

This insight led us to re-examine the flows for creating and hosting conference calls. Although not our core value nor differentiator, if these flows are primarily what our users interact with every day, we need to be sure the design is optimal.

I observed a key pattern during this re-examination. There are four distinct stages to a conference call: Schedule, Join, Conduct, Post-Process.

Most people use another tool for stage one, like a calendar application, email, or unstructured communication (instant message). Scheduling is a hassle and often the source of wasted time. Key outcomes are syncing time zones, providing local international dial-in numbers, and the right call to action on how to join.

Joining is the second stage and is over looked by almost every vendor. I find this ironic because it’s also the single largest source of frustration with conference calls. Take a moment to contemplate everything that can go wrong:

• Phone number and join link is old because the host had to recreate the meeting or accidentally created multiple meetings.
• Participant doesn’t have a local dial-in number.
• People generally need to download something (we’ve all used WebEx or GoToMeeting, right?), and the process is slow. Plus often the systems are problematic. IT administrators may prevent the downloading of a Java client, or lock down an IP range.
• People are late. People arrive early.
• Someone misses the call entirely.
• Participants might need to remember authentication, and who likes to remember usernames/passwords?

It’s a full process unto itself and deserving of a separate stage. I find it surprising and exhausting how poorly this stage is designed, resulting in calls starting out negatively before anyone even speaks. People tend to be in a bad mood entering a conversation because of this stage.

The third stage is the actual meeting. Other products tend to focus on this stage. You got interactive white boards, call management widgets, screen sharing, social media plugins, LinkedIn profiles, liking-sharing-posting-chatting-talking … you name it. All in the name of making the call “more useful” by making it more interactive. Sometimes I feel it’s actually making a conversation more distracting. Many users resent the tools found during this stage.

The fourth stage is a never-ending ray extending out from the moment the call ends. Products tend to not associate this stage with a conference calling application, but it is a vital portion. Users create follow ups, assign tasks, share files, and log information in systems—like a CRM, ATS, or Basecamp.

I see this stage as the connector to other jobs participants need to do. The fourth stage is a launching point to other actions. However, it is important to remember Des Traynor’s point about staying true to what your product is meant to do. You don’t want to extend beyond that line. For example, it’s difficult sometimes to remember that Symposia is not a calendar scheduling tool or meant to be a framework for to-do’s, but is a conference calling application.

It has helped me to think of a conference call like a single line that has a beginning but no ending, then cutting that line into four sections.

I see the Post-Processing phase as the most fertile area for innovation. Users might come back to the call at a later point. They might need to extract context to a follow up. We have yet to fully understand the full value, but the possibilities for aiding specific jobs to be done are rich.

It has helped us to think about a conference call in four stages. Addressing each stage and targetting features and flows that focus on enabling the successful completion of the job to be done within those stages has made the product more useful overall.

Part of the interest behind the Nodal project was to push our understanding of how to browse data. We built it under the simple question, “What if data could be more interactive?”

The D3 JavaScript library and work that Mike Bostock has been doing is truly inspiring. If you don’t know Mike, he splits time at Square, one of the most admirable growth startups in recent years, and the NY Times. He is responsible for many of the interactive graphs you see on nytimes.com every week. My favorite was this one leading up to the election.

Matt, Jesse and I looked through the type of graphs D3 provides out of the box, as Nodal was to be a Hello World experiment. We stumbled upon an example of a node graph that used physics and thought What if these nodes were people? We brainstormed until we landed on the idea of letting GitHub users explore their network graph.

This is not novel, we acknowledge that. It’s nothing new. But what comes next became intriguing to us.

See, when you have hundreds of nodes representing people and connect them based on a relationship, filters become increasingly more powerful.

For example, let’s say I’m looking at a graph of 1,000 StackOverflow users. I want to filter to just those who are considered Python experts. Trivial, I know, but seeing the results in an interactive network graph compared to a table is a fascinatingly different experience because interactivity is richer. Now let’s say I’m looking at that grouping of Python experts. I find a few I want to contact and drag their node over to a side. When I have my group, I simply drag to select them and cast a command via a context menu.

In the end, Nodal is just a simple experiment that isn’t anything too mind-blowing. But it sparked curiosity. What interface innovations can be done to make navigating a data set more intuitive? Is there a framework that can work across any type of data set? Which heuristics are better than others? And so on.

We are thinking of expanding Nodal to different social networks and types of data sets. Each time we anticipate learning something new.

Lately my favorite approach is to build responsive device-based layouts at the same time I build the normal desktop layout. I focus on a singular view or flow, and design each of the responsive layouts at that point in time. This is in contrast to building the entire application for one specific layout type (e.g. desktop min-width 1024px) then starting over again with the next layout type, and so on.

For example, I will take the login process and design/build all responsive layouts at the same moment before I move on to the reset password flow.

My main reasoning is catalyst. It forces me to think of responsive options and build them right away instead of telling myself I’ll come back to it. I do come back—I’m not lazy per se—but I tend to forget some of the deep thoughts and learning moments I had when designing the first layout option.

But I admit that may not be the optimal reason to decide on a responsive approach. I’m eager to learn more and watch my perspective evolve. So far my latest projects have been of the personal nature. I have yet to approach responsive layout design at a production level. My perspective may change due to code optimization concerns and speed of development. My colleagues might have insights or needs that alter my approach too. Perhaps after a while, I’ll discover something better.

Granted, Photoshop has some problems of its own, most noticeably the poor font management and lack of reliable alignment tools. But I’ve learned to work around them like I’m sure Illustrator pros have their work arounds.

Lately, the poor font treatment in Photoshop has driven me to explore more with Illustrator. One day I noticed an annoyance while exporting images for the web. They would often be blurry! Crisp, anti-aliased lines would be blurry. In Photoshop it’s easy to tighten up aliasing. This is an example of a shape where one line is between two pixels. Notice how there is an aliased edge?

I later learned that the dimensions of the vector file in Illustrator are important. If you aren’t structuring all your lines to be exactly on the closest pixel, you’re going to get the aliasing like above. In this image, note how my edge was not lined up perfectly with the 56px guide.

There are other preference tweaks you can do to combat exported blurriness. I found this article by Tony Thomas to be the most thorough.