John Kessler

Co-founder / CTO @AaruHQ. Simulating human behavior; prev. city simulation @MIT

[John Kessler @john_k]

@yitong This seems well-calibrated; in a successful scenario where people can dedicate more time towards leisure and community, value of non-fungible cultural institutions will go up. Sports teams, destination restaurants, historical hotels, etc. will benefit.

[John Kessler @john_k]

An interesting consequence of productivity gains as a result of newly introduced agentic tooling is that it seems to invert the standard time discount on labor. The typical assumption is that an hour today is worth more than an hour a year from now. But, if the hour a year from now is 10x more productive, the discount flips and the future hour is much more useful. Rationally, one might expect to stop spending the hours of today on work that becomes much cheaper, redirecting that time towards accumulating durable, compounding assets that aren’t subject to the time discount inversion (e.g. capital, trust, mindshare).

Consider Brunelleschi and the Duomo of Florence. If Brunelleschi learned that within the year, a crew of engineers equipped with hydraulic cranes would magically appear, he’d be likely to stop laying bricks. He may spend more time refining the dome’s geometry or thinking about how to best change the dome’s design to accommodate these new tools.

There’s probably two caveats here – firstly (and most obviously), this only applies where productivity is compounding fast enough to flip the discount. Furthermore, this is hard to project–certain spaces may incur this inversion only some N% of the time–and experimenting may not be viable when the penalty of an undershoot or miscalibrated prediction has exponential downside.

Secondly, some games are Red Queen’s Races. Failing to produce in the short-term would foreclose the long-term payoff. Consider Brunelleschi, who’s now competing with the hypothetical, equally-acclaimed renaissance architect Ihcsellenurb. Brunelleschi and Ihcsellenurb are competing for a grant from a wealthy patron who’s unaware of the incoming cranes, instead intending to award the grant based on visible quarterly progress. Brunelleschi might know the cranes are coming, yet still be forced to lay bricks, as without this grant, he’d be unable to pay the crane operators when they arrive.

Seemingly, this model only works when an actor can afford short-term output illegibility in pursuit of a better long-term output. My sense is that the distribution of these actors is barbelled. On one hand, entrenched incumbents with reservoirs of trust and capital are able to absorb quiet quarters (Apple, for instance). On the other hand, small players can afford illegibility simply because nobody cares enough to punish it.

It seems the losers of this game sit in the middle of the barbell; this makes sense, given it’s the only segment where short-term legibility is (1) required and (2) existential. Incumbents and upstarts alike can absorb misses in a way that the squeezed middle can’t. Private markets will see two middle-of-the-barbell companies, where one is externally missing whilst the other seems to just keep winning, and reward the one with the legibly positive result. So, the middle must survive by laying soon-to-be-obsolete bricks, simply to keep up in the Red Queen’s Race

[Aaru @aaruHQ]

Thank you to the @WSJ and @VranicaWSJ for writing the first page in the story of Aaru. More soon.

[John Kessler @john_k]

@j_dekoninck @gooby_esq probably
- validate post code formatter length
- reward using all language syntax features (e.g. walrus operator, dict | dict)
- penalize lybl slop (e.g. .get(), .hasattr(), .getattr())
- rewarding using stdlibs (e.g. itertools, collections)
- penalize cylcomatic complexity

[Aaru @aaruHQ]

We’re partnering with @InterpublicIPG to bring predictive capabilities and enhanced foresight to Interpublic Group’s portfolio of companies. Together, we will accelerate creative expertise with the power of human simulation.

[Aaru @aaruHQ]

Launching our collaboration with @Accenture. Together, we plan to harness the power of human simulation to provide our clients with a clearer lens into the future.