Afterthoughts on Hive Minding

It’s a powerful thing to understand how your brain works, what motivates you, and what you don’t care about. There are so many things that can distract, but at the end of the day, there are very few things measurable immediately worth having done. Shipping myself to Europe until next week, for example, has already had measurable personal and professional impact.

One thing I experienced this week after injecting a little disruption to conformity yesterday was what I now call “hive minding”, or otherwise assisting independent contributors in rowing in the same direction. The classical stereotype of “herding cats” infers that actors only care about themselves, but unlike cats, a bee colony shares an intuitive, survival imperative to build and improve the structure that ensures their survival. Each bee might not consciously think about “lasting value”, but it’s built into their nature.

Be Kind, Rewind

I’m always restless, every success followed by a new challenge, and I wouldn’t have it any other way, but it does lead to a growing consideration about plateauing. Plateauing is a million times worse than burning out. There are plenty of people and companies that have burned out already but are still doing something “functional” in a dysfunctional industry, and if the decision is to flip that investment, it’s an easy one to make. Fire them, trade or cut funding; but what do you do with a resource when they plateau?

I think you’ll know you’ve plateaued when you find yourself without restlessness. If necessity is the mother of invention, restlessness is the chambermaid of clean mind. Al least for me, like a hungry tiger in a cave, I must feed my restlessness with purposeful and aligned professional work. The only problematic moment with me…I like to get ahead of the problem of someone telling me what to do by figuring out what we (everyone, me and them) should be doing before someone dictates it with less context.

The sweet spot of this motion is to do this together, not in isolation and not dictatorially, but coalescing the importance of arriving at the “right” goals and in alignment at the same time. The only surprises when you’re riding the wave together is what comes next, and when you engineer this into the process, surprises are mostly good.

It took a while to arrive at this position. I had to roll up sleeves, work with many different teams in multiple organizations, listen to those whose shoes I don’t have the time or aptitude to fill, figure out how to synthesize their inputs into cogent and agreeable outcomes, and do so with a level of continuity that distinguishes this approach from traditional forms of management and group facilitation.

Don’t Try This On Your Own

The cost of adaptability is very high. If I didn’t have an equally dedicated partner to run the homefront, none of this would work. She’s sought out the same kind of commitment and focus on raising the kids as I do with what goes into pays the bills. There are very few character traits and creature comforts we share, but in our obsession over the things that make the absolute best come out of what we have, she more than completes the situation.

In this lifestyle, I have to determine day by day and week by week what net-new motions/motivations I need to pick up and which I need to put down, either temporarily or permanently. This can feel like thrash to some, but for me, every day is a chance to re-assess based on all the days before now; I can either take that opportunity or not, but it is there despite whether I do or not take it. If my decisions are only made in big batches, similar to code/product releases, I inherit the complexities and inefficiencies of “big measurement”…namely, granularity in iterative improvement.

Feedback Loops, Everywhere

As I explore the dynamics of continuous feedback loops beyond software and into human systems, a model of frequency in feedback and software delivery not as separate mechanisms, but as symbiotic, emerges. The more frequently you release, the more chances there are for feedback. The more feedback you can synthesize into value, the more frequently you want to release. One does not ‘predict’ the other; their rate bounds each other, like a non-binary statistical model.

What I mean is that a slow-release cycle predicts slow feedback and slow feedback predicts low value from releasing frequently; a fast feedback mechanism addicts people to faster release cycles. They share the relationship and depending on how extreme the dynamics feeding into one side of the relationship, the other one suffers. Maybe at some point, it’s a lost cause.

An example from the performance and reliability wheelhouse is low/slow performance observability. When you can’t see what’s causing a severe production incident, the live investigation and post-mortem activity is slow and takes time away from engineering a more reliable solution. Firefighting takes dev, SRE, ops, and product management time…it’s just a fact. Teams that understand the underlying relationship and synthesize that back into their work tend to use SEV1 incidents as teachable moments to improve visibility on underlying systems AND behavioral predictors (critical system queue lengths, what levels of capacity use constitute “before critical”, architectural bottlenecks that inform priorities on reducing “tech debt”, etc.).

The point is that feedback loops take time and iterative learning to properly inject in a way that has a positive, measurable impact on product delivery and team dynamics.

Going from Feedback Loops to Iterations…Together

All effect feedback loops have one thing in common: they measure achievement levels framed by a shared goal. So you really have to work to uncovered shared goals in a team. If they suit you and/or if you can accept the awesome responsibility to challenge and change them over time, it’s a wild ride of learning and transforming. If not, find another team, company, or tribe. Everyone needs a mountain they can traverse and shouldn’t put themselves up to a trail that will destroy them. This is why occasionally stepping back, collaborating, and reporting out what works and what doesn’t is so important. Re-enter the concept of “team meetings”.

Increasingly, most engineers I talk to abhor the notion of more meetings, usually because they’ve experienced their fair share of meetings that don’t respect their time or where their inputs have not been respectfully synthesized in a way they can see. So what, meetings are a bad thing?

Well, no, not if your meetings are very well run. This is not one person’s job, though scrumbags and mid-level management with confirmation bias abound, and especially so because they don’t have built-in NPS (net promoter score). A solution I’ve seen to the anti-pattern of ineffective meetings is to establish common knowledge of what/how/why an “effective” meeting looks like and expect these behaviors from everyone in on the team and in the org.

How to Encourage Effective Collaboration in Meetings

Learn to listen, synthesize, and articulate back in real-time. Too much time goes by, delay and context evaporate like winter breath. Capture as much of this context as you can while respecting the flow of the conversation. This will help you and others with remembering and respecting the “why”, and will allow people to see what was missing (perspectives, thinking, constructs), afterward. Examples of capture include meeting minutes, pictures of post-its, non-private notes from everyone, and even recordings.

But in just about every team and organization there’s a rampant misconception that ALL meetings must produce outcomes that look like decisions or action items. These are very beneficial, but I’ve seen people become anti-productive when treating themselves and others as slaves to these outcomes. Taking decisions too early drives convergent attitudes that are often uninformed, under-aligned, and often destructive.

Some of the most effective meetings I’ve had share the following patterns:

  • know why you’re meeting, provide context before, and set realistic expectations
  • have the “right” people in the room
    • who benefit from the anticipated outcomes and therefore are invested in them
    • who bring absolutely critical perspective, where otherwise invalidates outcomes or cause significant toil to refactor back in afterward; not to few
    • who contribute to functional outcome (as opposed to those who are known to bring dysfunction, don’t respect the time of others, argue over align); too many
  • agree on what positive and negative outcomes look like before starting in
  • use communication constructs to keep people on track with producing outcomes
  • have someone to ensure (not necessarily do all the) capture; note and picture taker
  • outcomes are categorized as:
    • clear, aligned decisions (what will happen, what worked, what didn’t, what next)
    • concrete concerns and missing inputs that represent blockers to the above
    • themes and sense of directional changes (i.e. we think we need to change X)
    • all info captured and provided as additional context for others

Trust AND Verify

One thing I keep finding useful is to challenge the “but” in “trust, but verify”. In English, the word “but” carries a negating connotation. It invalidates all that was said before it. “Your input was super important, BUT it’s hard to understand how it’s useful”…basically means “Your input was not important because it was not usable.”

My alternative is to “trust and verify”, but with a twist. If you’re doing it right, trust is easy if you preemptively provided an easy means to verify it. If you provide evidence along with your opinion, reasonable people are likely to trust your judgment. For me, rolling up the sleeves is a very important tool in my toolbelt to produce evidence for or against a particular position. I know there are other methods, both legitimate and nefarious, but I find that practical experience is far more defensible than constructing decisions based on shaky foundations.

All this said, even if you’re delivering self-evident verification with your work, people relationships take time and certainly take more than one or two demonstrative examples of trustability to attain a momentum of their own. Trust takes time, is all.

Takeaways and Action Items from This Week

Democratic decision processes are “thrashy”. Laws and sausages: no one wants to know how they’re made. In small teams going fast, we don’t have the luxury of being ignorant of outcomes and the context behind them. For some people, “democracy” feels better than dictatorial decisions being handed down without context; but for those who still find a way to complain about the outcomes, they need to ask themselves, “did I really care enough to engage in a functional and useful way, and did I even bother to educate myself on the context behind the decision I don’t like?”

Just like missing a critical perspective in a software team, in a global organization, when one region or office dominates an area of business (U.S. on sales, EU on security, for instance), this will inevitably bias outcomes and decisions affecting everyone. As the individual that I report to puts it, “scalability matters to every idea, not just when we’re ready to deploy that idea”. Make sure you have the right “everyone” in the room, depending on the context of your work and organizational culture.

Someone I once met and deeply respect once told me “it’s not enough to be an ally, you need to be an accomplice“. In context, she was referring to improving the epic dysfunction of modern technology culture by purposefully including underrepresented persons. Even if we make a 10% improvement to women’s salaries, hire more African-American engineers, create a safer place for LGBTQ, I still agree with the premise that doing these things isn’t good enough. Put it another way, receiving critical medical treatment for a gushing head wound isn’t an “over-compensation”, it’s a measured response to the situation. The technology gushing head wound, in this case, is an almost complete denial from WGLM (white guys like me) that there is a problem, that doing nothing continuously enables the causes of the problem, that leadership on this doesn’t necessarily look or think like us, and that this isn’t necessarily needed now.

Bringing it back to the wheelhouse of this article, true improvement culture doesn’t just take saying “sure, let me wave at you as an ally while you go improve the team”. It takes being an accomplice (think a getaway driver), we should ALL be complicit in decisions and improvement. Put some skin in the game, figure out how something truly worth improvement and your effort maps to your current WiP (work in progress) limits, and you may find that you need to put something less worth your time down before you can effectively contribute to improvement work. Surrounding yourself with folks who get this too will also increase the chances that you’ll all succeed. This is not an over-compensation, it is what everyone needs to do now to thrive, not just survive.