Waking Up recently told me I’ve passed 300 hours of practice across just over 2,000 active days. That works out to about 10 minutes a day for five years, which is a small commitment that has compounded into something I care about.
So, why do I keep going? The most honest answer comes from the times I’ve skipped a couple of days: I feel more distractable and less centred. That’s the counterfactual and it’s more persuasive than any in-session feeling.
Beyond the functional benefit, I’m genuinely fascinated by consciousness—what it is, how it relates to experience, and whether attention can be trained in ways that matter. Waking Up is excellent here. The app has dozens of quality series with practitioners who take these questions seriously, and Sam Harris draws from both contemplative tradition and people doing rigorous philosophical and scientific work on the nature of mind.
The harder question, though, is whether any of this carries over. A couple of years ago, I went through some challenging work experiences and found that the equanimity I’d cultivated in practice didn’t transfer reliably. I found I was getting frustrated, saying to myself “but I meditate!”, which really just made the point that equanimity in a quiet room is not the same as out in life.
Over the past year, I’ve been deliberately working on that gap—paying attention to how I respond to frustration, pressure, and distraction in daily life, not just during a morning session. It’s slow going, but I’m noticing a real difference. This work connects well with my ongoing effort to be less distracted by technology, which also requires noticing when attention has been captured.
Everything seems to be coming together. Slowly, ten minutes at a time, but it is. That’s why I keep going.
I like the new heart rate distribution graphs in HealthFit.
Here’s an example from a recent intervals run that shows decent recovery back to Zone 2 in between each hard effort. This helps me make sure I’m neither pushing too hard nor slacking in those intervals.
There’s a different profile for a recent HIT session that kept me in a pretty steady high effort once the warmup was done.
The overall distributions by activity type are fun. Although no one is surprised to see that yoga is less intensive than running or cycling.
HealthFit remains my app of choice for integrating all of my fitness data.
Something is happening. The dam has burst on almost two decades of tightly-managed, coordinated and targeted political messaging. In its place we’re seeing a communications approach that’s more free-flowing, discursive, open and adaptable.
Such a welcome change. I hope it lasts.
Finished reading: Arctic Passages by Kieran Mulvaney nicely integrates the past, present, and future of the Arctic into a compelling story about climate change, geopolitics, history, and exploration 📚
Finished reading: Count Zero by William Gibson is great. Not sure why I waited almost thirty years after reading Neuromancer to read this one. I certainly won’t wait as long to read the third book of the trilogy 📚
Finished reading: The Prime Ministers by J.D.M. Stewart was exactly what I wanted: a concise and clear summary of each Candian Prime Minister. That was a gap in my knowledge that is now closed 📚
As we approach the start of a new fiscal year, I’m thinking through performance metrics and targets for my capital finance team.
A classic metric in finance is comparing forecasts to actuals: take a look at what you expected, relative to what actually happened, and keep that within some tolerance – like 10%. Nothing wrong with this. We want small variances! But, this is a lagging indicator. Whatever caused the variance happened out on a construction site many months ago and is only now showing up in the financials. We can use this to get better, perhaps, at forecasting. It doesn’t retroactively fix the problem on site.
I’ve been thinking through potential metrics to get ahead of issues, measure our internal project communications, and adherence to governance. Basically a metric for how surprised we are each month by financial changes.
First, some background, without turning this into an AACE paper. An important role for my team is the assembly of an Estimate at Completion (EAC), which is basically what we think the project will actually cost by the end of delivery. It includes incurred costs, approved change orders, commercial claims, and trends. Adding these together yields the EAC and there’s all sorts of discipline around them. In addition, the project has a risk tracker that quantifies the likelihood and financial impact of a whole host of things that could happen, but haven’t, yet. The EAC is expected to fluctuate each month as risks materialize, trends and claims are adjusted, and new scope gets approved.
So, my experimental metric is tracking the proportion of a monthly change in the EAC that can be attributed to an item in the risk tracker from the previous month. In other words, our estimate changes because a risk we were tracking materialized. This is much better from a controls perspective than unexpected things happening each month that change the EAC.
I don’t want to get too hung up on “attributable”. I’m sure there will be changes that can only be partially attributed to a specific risk, as well as changes that could be attributed to many risks simultaneously. I’m good with at least a predominance of attribution to something in the risk register. This does, though, require that we have some good version control on the register. So that we don’t just change what it says to suddenly be attributable to what happened. This will be a new step of archiving the risk register each month, since we ordinarily want it to be continuously updated.
Of course, no one expects that all changes would be anticipated. This affects the target to be set. Given we’d be new at this, something like 80% of changes to the EAC this month being attributable to a risk from last month seems like a reasonable starting point. Aiming for 100% right away could drive the wrong behaviour.
That’s my proposal. We’ll pilot it on a few contracts and adjust, as necessary. If the metric is trending well, that gives our forecasts credibility and our executives comfort that they’re well informed. If it is trending poorly, we’ll know there’s work to do, likely through more careful risk reviews.
So I propose (years late, many bucks short) we just toss it all in the bin and go back to the beginning. Blogs, newsletters, IRC, mailing groups, and, sure why not, Usenet, go nuts. (The jury is still out on forums, but I suspect they are actually a stunted malformed sapling sprung from the same seed of evil that created modern social media.) These things are time tested, functional even in the face of overwhelming lack of interest from the general internet, and are, most importantly, utterly unbreakable. A specific blog, irc etc etc might disappear, but that won’t take anything besides that one facet of a larger whole with it.
I don’t think this is just nostalgia, though there is some of that. The “old” internet was robust and vibrant in a way that modern sites aren’t.
Finished reading: The Song of Achilles by Madeline Miller is very well done. Really fleshes out the Achilles myth and brings Greek heros and gods to life 📚
Although I don’t hate Liquid Glass, it is odd enough to motivate exploring approaches by indie developers. To be honest, I’ve really missed using indie apps, so this is a great excuse to make some changes.
Many of Apple’s apps emphasize discovery too much. I like opening Overcast and only seeing a list of unplayed podcasts that I’ve chosen to follow or opening Albums and seeing colourful album art exclusively from artists I like. These apps are designed for me to access content I’ve chosen, not to upsell me on other things.
Like many others, I’m accumulating some vague ickiness with Apple these days. I’m nowhere near switching, but want to reduce some dependencies. Of course, I’m still using lots of Apple devices and services, so this is a very small step.
Applying the Online Harms Act to AI chatbot conversations now risks reopening the very issues policymakers previously sought to avoid. In fact, it is difficult to see the difference between something posted to an AI chatbot or similar content entered into a search query or included in text message or email correspondence. If proactive monitoring of searches, emails or texts is subject to privacy safeguards, so too should be AI chatbot engagement.
I’m all for smart regulation of AI, but agree that this isn’t the way to go.
Noticing your life doesn’t require depth. It requires attention.
Once I stopped trying to use my journal as a memoir and just captured daily thoughts, feelings, and happenings, my journal became useful and enjoyable.
