Eli Mintz

Artificial general intelligence (AGI) may be the biggest technological shift of our lifetime yet not be where most of the money is made. @phineasb, cofounder and managing partner at @thegp, expects AI to fragment into thousands of “not really AGI” systems that are good enough at general reasoning and exceptional at one particular job. This specialization—not general intelligence—is where most of AI’s economic value will be captured. Read Phin’s Thesis Statement: every.to/thesis-statements/p…

Mamdani: Today, I am proud to announce a collection of essential staples that will be predictably 30% cheaper at all five of our city-run grocery stores. This core set of goods will include all fresh produce, meat, and seafood, along with 20 other essential items like cheese, milk, and bread. Here's how it will work. Once a month, our five city-run grocery stores will set prices for this core set of goods at 30% below typical retail prices. No exceptions, no gimmicks. The savings will last for the entire month. That means no weekly fluctuations or sticker shock at the checkout line—not for our seniors living on fixed incomes, nor for the parents who rely on a regular supply of apple slices to keep toddler tantrums at bay.

Mamdani: Today, I am proud to announce a collection of essential staples that will be predictably 30% cheaper at all five of our city-run grocery stores. This core set of goods will include all fresh produce, meat, and seafood, along with 20 other essential items like cheese, milk, and bread. Here's how it will work. Once a month, our five city-run grocery stores will set prices for this core set of goods at 30% below typical retail prices. No exceptions, no gimmicks. The savings will last for the entire month. That means no weekly fluctuations or sticker shock at the checkout line—not for our seniors living on fixed incomes, nor for the parents who rely on a regular supply of apple slices to keep toddler tantrums at bay.

This is quite a remarkable result: Posed in 1939, the Jacobian conjecture is one of the central open problems in algebraic geometry, but was just disproved by Alpoge, Matthew, and Claude Fable 5. The Jacobian conjecture roughly says that a multivariable polynomial F has an inverse function (made out of polynomials) provided the Jacobian is non-singular (i.e. matrix of partial derivatives has non-zero determinant). This condition is neccessary by the Inverse Function Theorem from multivariable calculus. The hard question is whether it is also sufficient. Evidently, Fable found that F(x,y,z) = ((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z) has det(J_F) = -2 non-zero. However F is not invertible, since F sends three different pts (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to the same image (-1/4, 0, 0). Beyond the disproof itself, it would be value to know if a suitably refined conjecture is recoverable. Per @Acer, GPT5.6 has proposed: "A constant-Jacobian polynomial local biholomorphism with no loss of sheets at infinity—e.g. a proper Keller map—is an automorphism." I would be interested to know if any algebraists (e.g. @levent @littmath) have a reaction to this... A further twist to the story: Not only was the Jacobian conjecture one of the central open problems in algebraic geometry, it was (a special case of) Yitang Zhang's PhD problem! The catch was that Zhang's advisor had him solve it, assuming a lemma of his advisor. But that lemma turned out to be false! As a result, Zhang's thesis crumbled and he then struggled to get recommendation letters and a permanent academic position. Despite all this, Zhang went on to prove bounded gaps between primes! This is one of the most inspiring stories in modern mathematics, and was a motivation for me to work in the same area for my doctorate.

"you can outsource your thinking, but you can’t outsource your understanding" easy to forget in todays AI era, worth remembering everyday as we all wield more intelligence!

The more enterprises I talk to about AI agent transformation, the more it’s clear that there is going to be a new type of role in most enterprises going forward. The job is to be the agent deployer and manager in teams. Here’s the rough JD: This person will need to figure out what are the highest leverage set of workflows on a team are (either existing or new ones) where agents can actually drive significantly more value for the team and company. In general, it’s going to be in areas where if you threw compute (in the form of agents) at a task you could either execute it 100X faster or do it 100X more times than before. Examples would be processing orders of magnitude more leads to hand them off to reps with extra customer signal, automating a contracting review and intake process, streamlining a client onboarding process to reduce as many straps as possible, setting up knowledge bases than the whole company taps into, and so on. This person’s job is to figure out what the future state workflow needs to look like to drive this new form of automation, and how to connect up the various existing or new systems in such a way that this can be fulfilled. The gnarly part of the work is mapping structured and unstructured data flows, figuring out the ideal workflow, getting the agent the context it needs to do the work properly, figuring out where the human interfaces with the agent and at what steps, manages evals and reviews after any major model or data change, and runs and manages the agents on an ongoing basis tracking KPIs, and so on. The person must be good at mapping the process and understanding where the value could be unlocked and be relatively technical, and has full autonomy to connect up business systems and drive automation. This means they’re comfortable with skills, MCP, CLIs, and so on, and the company believes it’s safe for them to do so. But also great operationally and at business. It may be an existing person repositioned, or a totally net new person in the company. There will likely need to be one or more of these people on every team, so it’s not a centralized role per se. It may rile up into IT or an AI team, or live in the function and just have checkpoints with a central function. This would also be a fantastic job for next gen hires who are leaning into AI, and are technical, to be able to go into. And for anyone concerned about engineers in the future, this will be an obvious area for these skills as well.

Exclusive - Israeli security officials: The option of seizing islands in Iran (Kharg or others) or the Strait of Hormuz is “complex and fraught with danger,” and would likely trigger “massive Iranian attacks on energy infrastructure, the laying of mines, and, in any case, a severe escalation.” Their recommendation, as conveyed to decision-makers: if Iran refuses an agreement- and in any case escalates attacks on regional energy- the allies should threaten (and, if necessary, carry out) strikes causing extensive damage to Iran’s energy infrastructure, and not immediately execute a ground operation.