Learning speed itself is a learnable skill; people who have developed good learning habits can pick up new fields much faster than the average person, which means the real skill distribution is around 'how good are you at learning' rather than 'how much do you know'.

During the first year of Shopify operations during the pandemic, Tobi worked 14-16 hour days, seven days a week for approximately one and a half to two years, eventually burning out some executives who couldn't sustain that pace.

The convergence of Transformer models, large language models, and diffusion models is creating possibilities that will define the next era of human capability; this is the most exciting time in technology and requires both theoretical breakthroughs and practical engineering to implement.

Machine learning progress is accelerating so rapidly that Tobi is having difficulty keeping up with all developments despite paying attention, suggesting that tracking and understanding all progress requires dedicated effort and even well-informed people are losing sight of the pace.

The Turing machine, and by extension all computing, represents something more fundamental to life and human civilization than is commonly appreciated; it is as fundamental as DNA and deserves to be integrated into how we understand human history.

Stock options and equity compensation exist largely because of historical tax optimization, not because they are the best way to align incentives; in many jurisdictions (like Canada), there is no tax advantage, yet equity compensation persists, suggesting path dependency rather than rational design.

The key to fixing insomnia is understanding that sleep comes when you are sleepy (not tired), and the way to build sleep hygiene is to only go to bed when sleepy, create a bedside reading chair for when you wake up and can't immediately fall back asleep, and stick to a consistent sleep schedule.

The transition from financial optimization of compensation systems (using stock options for tax benefits) to explicit, auditable systems (clear salary + choice of how to receive it) represents applying engineering thinking to HR, making it more transparent and adaptable.

Best practices are actually just average risk-adjusted practices; they encode the wisdom of conventional wisdom and discourage deviation, but innovation requires doing things differently, and therefore taking on risk that best practices explicitly avoid.

Founder-led companies are often described as immature, but this is incorrect; they are instead 'spiky objects' with very strong aptitudes in specific areas (often matching the founder's strengths) and sometimes surprising weaknesses, but organized around solving a particular set of problems.

Revision to the mean (entropy) is the default state for companies; bureaucracy, best practices, and process sediment all pull organizations toward the ambient industry competency level, which is typically mediocre, and the only way to fight this is through constant subtraction and strategic focus.

The previous model of acquiring all innovation from outside companies (acquire-to-innovate) is fundamentally opposed to Tobi's philosophy; instead, he wants Shopify to innovate everywhere internally because that requires founders to demonstrate that they can solve the full spectrum of problems.

Shopper's new compensation system gives employees a transparent base salary and then lets them choose how to receive additional value (cash, stock options, and potentially other instruments), treating them as adults who can make informed choices rather than using complex financialized derivatives that obscure the actual value exchange.

All of business should be rederived from programming and systems design principles because programming uniquely solves the problem of building resilient systems that must operate in chaotic, non-deterministic environments with incomplete information.

Programming synthesizes key properties of mathematics (theoretical purity and abstraction through symbols and equivalence) with practical linguistics, creating a new field that can reason about computable, resource-constrained systems that mathematics alone cannot address.

Computer science and its practitioners were historically sidelined by academia and industry as a cost center, but the 'revenge of the nerds' is that companies founded on computing principles are now out-performing traditionally managed firms, though the broader public has not yet integrated this into their understanding of why the world is the way it is.

Business systems should be thought of like software systems with explicit models, configurations, and auditable functions that can be tested, versioned, and iterated; this allows organizations to make changes systematically rather than ad-hoc, making them more adaptive to changing conditions.

Media institutions have a grudge against technology because they have been negatively affected by it, but this is a mistake; new media forms (podcasts, founder-operated video, newsletters) are thriving and this is actually a Golden Age of media, not a decline.

Technology IS progress, and if people adopt a pessimistic view of technology, they are adopting a pessimistic view of human progress itself, which is both factually incorrect based on data and also corrosive to optimism and agency.

All models are wrong but some are useful; the key skill is not finding the perfectly accurate model but finding the model with the right level of abstraction for the decision at hand and being able to assess whether you had enough information to make a good choice.