Great post, but two parts of your advice feel a bit stuck in 2025.
#1. Delegation Documentation can be written WITH the AI, not alone. E.g., Claude Code has a tool called AskUserQuestionTool that will interview you with multiple choice questions for as long as you want to build your Delegation Documentation for you.
#2. "Evaluate and review" should also be initially done by the AI, since effort is now free. You can prompt BOTH the task and its evaluation, and Claude Code can take on BOTH roles, going back and forth for you until the work product passes its OWN internal tests that it created as part of the task. When compute is free, AI iteration is free.
(Sample prompts of #1 and #2 are in the next comment.)
Asking humans to do these 2 steps outside of AI is just not necessary or efficient.
It's Sutton's Bitter Lesson. Don't be too clever; use more compute.
Yes, this is a mind shift. Imagine growing up in a 3rd world country where clean water and electricity are scarce, and then you move to the US and have unlimited clean water and power. It will take you a while to stop conserving both.
The same is true for Knowledge Work Effort (KWE). We all grew up in a world where KWE was scarce, and now it's plentiful, and we're still out here trying to conserve. It takes some unlearning!
Consider teaching your MBA students: Stop trying to conserve effort.
"Interview me in detail using the AskUserQuestionTool about literally anything: technical implementation, UI & UX, concerns, tradeoffs, etc. but make sure the questions are not obvious be very in-depth and continue interviewing me continually until it's complete, then write the spec to the file"
#2 - Sample prompt (h/t to @maxwellfinn on x.com):
"Before you return a version to me have 10 of the world's greatest advertorial experts on subjects like design, copywriting, psychology and CRO review the page, provide detailed feedback and rank it on a scale from 0-100. Each expert should include specific areas for improvement that are reflective of their ranking. If the average ranking isn't over a 90/100 then go back and improve it using the experts' specific recommendations and feedback until it is over a 90."
This also works for images. Want 5 matching slides? Have Claude go back and forth with Gemini Nano Banana (set it up as a Skill first) until Claude is happy with the final product.
"Stuck in 2025"? Today is only 1-27-2026. Time flies. ChatGPT 5.2 was a Bingo release. Now the hot button is Clawdbot. Today progress is not 10x. It's more like 100x. Or even 1000x. The biggest progress killer? Lack of imagination - given the constraints of the past, which would be early 2025. Thanks for your comment.
I'm not a massive doommonger over resource use, but that is an interesting analogy (unlimited water and electricity) you've picked to suggest that compute is 'free'.
But I find that the acts of delegation and evaluation are precious opportunities to challenge and refine my initial plans. Whether with human or AI agents, explaining my idea often inspires rethinking it, and evaluating results always does.
Your model treats iterative delegation as mere inefficiency, overlooking its value as strategic refinement.
Many of the software engineers I work with have trouble getting value from the agentic tools. But all of the engineering managers I know have found them to be very useful.
It’s very similar to working with junior software engineers - they are likely to do things a different way than you would do it, and if you give them a vague instruction, there’s a good chance you won’t get what you want. But you can generally move much faster with a team of ten junior engineers than you can when working by yourself.
This is a helpful article. I think you've presented a plausible hypothesis here about how AI might spin out in conventional business contexts.
Something we have already known is that AI is not automating core decision making, which is effectively a question of human ethics. The more you automate, the more morality and ethics you are necessarily handing over. There will be an obvious incentive to hand over more and more responsibility to try to 'get more done.' Which is just one concern here.
A more prosaic question: Will the economy, the broad, minimum wage economy, actually benefit from being able to create software this easily? It seems like the commercial software market is often pretty saturated. Most games on Steam don't sell, etc. I guess one possibility is this will unleash a wave of new entrepeneurship, but unless you're selling software that will be bought by a giant megacorporation, I'm not sure how you cash in on it. And aren't the megacorporations just automating all their own needs internally?
Here's a question: Just what is the value of an MBA given today's AI technology? Direction? No. Planning? That's instantly available. Marketing? Hardly. We are in the era of the one-man-band. If you can muster enough imagination then you can move forward faster than the money guys can say, "Wait, you forgot ... ". Spin up a VPS. Go into business tomorrow. Man, it's wonderful. (I'm 83).
Here in undergraduate world, I'm marking and reviewing assignments. Only a scattering of hallucinated references - either cheap AI tools are doing this less now, or the students are paying more, or they've got wiser to the problem - but so, so many that have a bit of an AI vibe to them. Mostly, I think students are prompting the AI tool with questions and paraphrasing the responses, plus some use of AI to create an outline structure. The basic summarising of reading and theory seems, on average, to be a lot better than a few years ago. The synthesis, analysis, and evaluation is often shallow. Marks similar. On the other hand, different cohorts and maybe a lot of this is just writing support like Grammarly getting a lot better, IDK ¯\_(ツ)_/¯. I'm bothered that our knowledge of how much learning activity is being delegated seems largely based on anecdotal evidence (like mine), we don't seem to know how much it affects expertise development, and - relevant to this, very interesting, post - are we going to end up with a generation that no longer has the kind of subject expertise you're saying is crucial for effective management of agentic AIs?
I think I intuitively know what you are talking about and that I could formally teach what you described because I do it everyday. Even tho I have zero experience last year I did commercial real estate feasibility studies, analyzed a $3B M & A deal etc
I was an early adopter of ChatGPT more than 3 years ago. The various versions 4 were disappointing compared to 3.5 but the 5.2 is absolutely amazing. People thinking that AI is for the future, useless for now couldn’t be more wrong. The people who should be very concerned are physicians: they started to use a medicine which is so fragmented that they have become more robotic than ChatGPT. I haven’t tested Claude as extensively as the other LLMs: I noticed on X, in 2024, that your method of testing was similar to mine. I have to write my first entry on substack and remove my alias.
Great post, but two parts of your advice feel a bit stuck in 2025.
#1. Delegation Documentation can be written WITH the AI, not alone. E.g., Claude Code has a tool called AskUserQuestionTool that will interview you with multiple choice questions for as long as you want to build your Delegation Documentation for you.
#2. "Evaluate and review" should also be initially done by the AI, since effort is now free. You can prompt BOTH the task and its evaluation, and Claude Code can take on BOTH roles, going back and forth for you until the work product passes its OWN internal tests that it created as part of the task. When compute is free, AI iteration is free.
(Sample prompts of #1 and #2 are in the next comment.)
Asking humans to do these 2 steps outside of AI is just not necessary or efficient.
It's Sutton's Bitter Lesson. Don't be too clever; use more compute.
http://www.incompleteideas.net/IncIdeas/BitterLesson.html
Yes, this is a mind shift. Imagine growing up in a 3rd world country where clean water and electricity are scarce, and then you move to the US and have unlimited clean water and power. It will take you a while to stop conserving both.
The same is true for Knowledge Work Effort (KWE). We all grew up in a world where KWE was scarce, and now it's plentiful, and we're still out here trying to conserve. It takes some unlearning!
Consider teaching your MBA students: Stop trying to conserve effort.
#1 - Sample prompt:
"Interview me in detail using the AskUserQuestionTool about literally anything: technical implementation, UI & UX, concerns, tradeoffs, etc. but make sure the questions are not obvious be very in-depth and continue interviewing me continually until it's complete, then write the spec to the file"
#2 - Sample prompt (h/t to @maxwellfinn on x.com):
"Before you return a version to me have 10 of the world's greatest advertorial experts on subjects like design, copywriting, psychology and CRO review the page, provide detailed feedback and rank it on a scale from 0-100. Each expert should include specific areas for improvement that are reflective of their ranking. If the average ranking isn't over a 90/100 then go back and improve it using the experts' specific recommendations and feedback until it is over a 90."
This also works for images. Want 5 matching slides? Have Claude go back and forth with Gemini Nano Banana (set it up as a Skill first) until Claude is happy with the final product.
Useful, thanks!
"Stuck in 2025"? Today is only 1-27-2026. Time flies. ChatGPT 5.2 was a Bingo release. Now the hot button is Clawdbot. Today progress is not 10x. It's more like 100x. Or even 1000x. The biggest progress killer? Lack of imagination - given the constraints of the past, which would be early 2025. Thanks for your comment.
I'm not a massive doommonger over resource use, but that is an interesting analogy (unlimited water and electricity) you've picked to suggest that compute is 'free'.
You assume that managers know what they want.
We think we know.
But I find that the acts of delegation and evaluation are precious opportunities to challenge and refine my initial plans. Whether with human or AI agents, explaining my idea often inspires rethinking it, and evaluating results always does.
Your model treats iterative delegation as mere inefficiency, overlooking its value as strategic refinement.
Dov, you make a great point. The burden of 1) setting goals and 2) providing context is easier said than done even with fancy AI tools.
Many of the software engineers I work with have trouble getting value from the agentic tools. But all of the engineering managers I know have found them to be very useful.
It’s very similar to working with junior software engineers - they are likely to do things a different way than you would do it, and if you give them a vague instruction, there’s a good chance you won’t get what you want. But you can generally move much faster with a team of ten junior engineers than you can when working by yourself.
This is a helpful article. I think you've presented a plausible hypothesis here about how AI might spin out in conventional business contexts.
Something we have already known is that AI is not automating core decision making, which is effectively a question of human ethics. The more you automate, the more morality and ethics you are necessarily handing over. There will be an obvious incentive to hand over more and more responsibility to try to 'get more done.' Which is just one concern here.
A more prosaic question: Will the economy, the broad, minimum wage economy, actually benefit from being able to create software this easily? It seems like the commercial software market is often pretty saturated. Most games on Steam don't sell, etc. I guess one possibility is this will unleash a wave of new entrepeneurship, but unless you're selling software that will be bought by a giant megacorporation, I'm not sure how you cash in on it. And aren't the megacorporations just automating all their own needs internally?
Here's a question: Just what is the value of an MBA given today's AI technology? Direction? No. Planning? That's instantly available. Marketing? Hardly. We are in the era of the one-man-band. If you can muster enough imagination then you can move forward faster than the money guys can say, "Wait, you forgot ... ". Spin up a VPS. Go into business tomorrow. Man, it's wonderful. (I'm 83).
I’d love to know what the assignment parameters were so I can try it out myself!
Here in undergraduate world, I'm marking and reviewing assignments. Only a scattering of hallucinated references - either cheap AI tools are doing this less now, or the students are paying more, or they've got wiser to the problem - but so, so many that have a bit of an AI vibe to them. Mostly, I think students are prompting the AI tool with questions and paraphrasing the responses, plus some use of AI to create an outline structure. The basic summarising of reading and theory seems, on average, to be a lot better than a few years ago. The synthesis, analysis, and evaluation is often shallow. Marks similar. On the other hand, different cohorts and maybe a lot of this is just writing support like Grammarly getting a lot better, IDK ¯\_(ツ)_/¯. I'm bothered that our knowledge of how much learning activity is being delegated seems largely based on anecdotal evidence (like mine), we don't seem to know how much it affects expertise development, and - relevant to this, very interesting, post - are we going to end up with a generation that no longer has the kind of subject expertise you're saying is crucial for effective management of agentic AIs?
Great article! Thanks so much for sharing these frameworks. It's insane the pace at which this is advancing and being democratized.
I think I intuitively know what you are talking about and that I could formally teach what you described because I do it everyday. Even tho I have zero experience last year I did commercial real estate feasibility studies, analyzed a $3B M & A deal etc
Interesting article! Nit: three broken images.
Not for me?
I was an early adopter of ChatGPT more than 3 years ago. The various versions 4 were disappointing compared to 3.5 but the 5.2 is absolutely amazing. People thinking that AI is for the future, useless for now couldn’t be more wrong. The people who should be very concerned are physicians: they started to use a medicine which is so fragmented that they have become more robotic than ChatGPT. I haven’t tested Claude as extensively as the other LLMs: I noticed on X, in 2024, that your method of testing was similar to mine. I have to write my first entry on substack and remove my alias.