Spoke to a candidate yesterday who told me this podcast interview was very helpful to understand what we do at Parable, and why it matters. So reposting it here: https://t.co/zv41BjS5we
Fair point on figures of history whose story may not apply to business. I'm still seeking examples of business leaders who built extraordinary companies without putting in the hours. Do you have any?
Hadn't heard of Cook Ding's story before — beautiful. And in a way, 19 years _is_ the kind of commitment hard work/long hours tends to get associated with, maybe conflated with.
Yeah putting in hours is just the proxy. Worth more nuance than my list gave it. My experience is less about long hours and more about the fact that something's gotta give.
For the last few years I've tracked my time in 30-min increments across ~40 categories. This exercise increased awareness around what I do with my time, and whether my attention aligned with my intentions/goals. Also made obvious that I had to make some choices. Time is finite.
Being present for my kid and partner while building the business has meant putting social life on the back burner for now. It's also also made me respect people who are highly intentional about their time and attention.
This is a way to price the meeting – on an ongoing basis.
Twice a year, I price meetings differently: at the time budget level.
Time-track every 30 minutes for two months.
Set targets per category. I end up trading 0.25% here and there b/c time is so finite. Painful way to surface and cut out what's non-essential.
Then compare results to intentions. And cut again for next round.
Meetings cut themselves. But they come back. Curious how the paragraph discipline could keep them out.
Honestly, early signals are encouraging.
First pass was a little bumpy. Second pass - which we just completed - was smooth. Shipping way more features. And the team is stoked.
I'm not married to 3-5 weeks. The goal is to have a near-term focus on prioritized well-bounded features. When done, we reshuffle the deck.
Long-term outcomes are defined in our strategy. This operating model acknowledges there are many roads to get there.
We're committed to our long-term convictions, AND this operating model allows us to remain agile instead of being too strongly attached to things we thought we were true 3-4 months ago when we set the roadmap but that may have evolved.
100%. I call it: entropy on steroids.
@t_blom – context is 50% of the response. That's what we've been focused on at Parable, and it *does* help. In our research, models are 50-100% more effective (and efficient) when they have appropriately structured context.
The other 50% is people (i.e. the people building agents).
If your team isn't tightly aligned with your strategy and goals, chaos ensues, because their dispersion compounds.
That's the news i like to hear. From @apolloglobal
"there is zero evidence of job losses because of AI... Instead, many firms are hiring AI implementation experts... It is Jevons paradox playing out in real time: cheaper technology is creating more demand and more jobs."
Doomers be damned.
https://t.co/BVf2tEdgU4
This is brilliant.
'I write a paragraph about why I should take a meeting.'
If you should take the meeting it's easy to do, but if you start writing and you're like “I don’t want to do this,” then the meeting is a waste of time.
"For the things that I think are really important when I’m like, “I got to write that paragraph, I could write 20 pages. It's easy”
A lot of otherwise smart people, don't spend enough time thinking about what they're working on.
100%. I call it: entropy on steroids.
@t_blom – context is 50% of the response. That's what we've been focused on at Parable, and it *does* help. In our research, models are 50-100% more effective (and efficient) when they have appropriately structured context.
The other 50% is people (i.e. the people building agents).
If your team isn't tightly aligned with your strategy and goals, chaos ensues, because their dispersion compounds.
Tokens are to AI what time is to humans.
We're using the infra we've built to understand where time (and attention) is allocated in the enterprise, to now understand where tokens are allocated.
Was your 7-figure token spend allocated to your roadmap and goals? To maintenance work? To critical bugs?
It's amazing that 6 months ago, this was *not* part of the conversation with any executives. Now, this is the dominant conversation.
100%. I call it: entropy on steroids.
@t_blom – context is 50% of the response. That's what we've been focused on at Parable, and it *does* help. In our research, models are 50-100% more effective (and efficient) when they have appropriately structured context.
The other 50% is people (i.e. the people building agents).
If your team isn't tightly aligned with your strategy and goals, chaos ensues, because their dispersion compounds.
Yep. Exactly what we're seeing too in the enterprise and midmarket: CEOs/CFOs asking about ROI. But still lacking maturity on how to really measure AI ROI. What's the baseline? Measured in top line growth? Bottom line growth? Top line per employee? Knee deep in this with our customers right now.
@wadefoster Isn't it straightforward, though, to port skills, memory, harnesses and other md files to another model provider if you want to change? Been mostly using Claude Code but don't feel locked into it either.
This is very cool @collinmathilde. Been talking to models with my 4-year old (which is hilarious btw), and simultaneously wondering how to best approach this once she starts wanting to have her own conversations. Incredible effort. Grateful for your work.
Productivity gains are real, but accrue to the individuals, not the companies. In some cases, i'd say it's net negative for the companies. AI is incredible when small teams are *tightly* aligned with goals. In most cases they aren't. Entropy reigns. People are "doing more work" but aren't necessarily creating more business impact.