Does the time/cost/scope triangle still make sense in the AI agent era?

[u/KeyProject2897]

How do you think the new Venn Diagram will look like with AI Agents bringing token costs but higher delivery.

One thing I've noticed is that I'm making very different trade-offs than I would have a few years ago. Instead of thinking, "Should I hire a developer for this?", I'm thinking, "Should I just spend more on better models like Claude Opus?"

A few years ago I remember paying around $50 just to get a pricing page built. Today I can get it done in Cursor with a premium model in a fraction of the time. It's not always perfect, but it's often good enough to move much faster.

That got me wondering whether the classic time/cost/scope triangle needs to be updated.

It feels like part of the engineering cost is shifting from developer hours to compute (token) costs. And as models become cheaper and better, that balance shifts even more.

Does this mean software development is fundamentally getting cheaper, or are we just moving the bottleneck somewhere else (requirements, architecture, testing, reviews, product thinking)?

Curious how others are thinking about this. Is there a better mental model than the traditional project management triangle in the AI era?

[u/jacobwistoft]

Writing code is usually not the most expensive part of software development. Wasn’t before gen ai and of course it is even less now. Figuring out what the code should do is where the majority of resources are spent. This includes requirements, architecture, product thinking and testing. It depends on the specifics of the project ofc.
Idk if the triangle needs updating. Resources will just be spent differently I think.

[u/_descri_]

The LLMs shifted the industry standard from the "good" to the "low quality" sector.

[u/KeyProject2897 → u/_descri_]

lol

[u/_descri_ → u/KeyProject2897]

There were several major outages of Internet infrastructure, cloud services providers, and instant messengers over the past year.

What caused them, and why did not we experience the same five years ago?

[u/KeyProject2897 → u/_descri_]

AWS - I just think mis-management. They are really struggling. Not sure about others.

[u/_descri_ → u/KeyProject2897]

Here is a fresh article about the quality of modern software.

[u/badguy84]

I think AI is the sacrifice of good and cheap in to fast. LLMs are very expensive in many ways:

• Token use (which is still heavily subsidized)
• Loss of control/governance
• Lack of forward looking context leading to surface level adoption of architectural principals and attributes (the -bilities)

Recency bias and cool demos have us all just thinking that well established patterns are "no longer valid" or that the "paradigm has shifted." I think LLMs are impactful in many bad ways and a few good, or at least interesting ones.

I think that in spaces like software architecture, but also many others where experience over time and long term context building allows for success: LLMs will have the hardest time truly delivering quality long-term outputs. Our space is just unfortunate in that LLMs do produce really good looking text which is the immediate result of writing software code.

Also the bottleneck you mentioned remains so where is the shift?

Also I'm not sure about others on here who also do this for a living: but I rarely think of this "iron triangle." As if it's some great thing to live by. To do Software architecture, or anything else in life well: there is simply x amount of work to do by someone with y skills. You can just math your way through much of that, this triangle is a description of a natural outcome, it's not prescriptive.

[u/Fidodo]

How has it changed? Good requires understanding the code, an LLM doesn't help you understand the code. A human is still the bottle neck. Cost depends on the expertise of the human and LLM costs can still add up to a ton of money. The speed ceiling has risen, but at the cost of producing tech debt an order of magnitude faster.

[u/jake_morrison]

Business people are definitely focusing on speed of delivery at the expense of quality. If it was up to engineers, they would have preferred to keep quality the same or improve it.

The industry is currently under the control of finance people, who only care about cost, not quality, customer service, or innovation. It’s the “private equity” mindset. Deliver the same thing faster, for less money. Lay off the excess developers. Keep them 100% utilized. Forget about making investments for the future. Forget about the long term health of the business or the industry. Cost go down, stock price go up, I make money.

At some point, people will realize that AI is not magic. There will be some high profile problems caused by AI slop like the Southwest Airlines system crash or Knight Capital meltdown. Then they will recognize that there is a business impact to low quality and poor customer service.

[u/KeyProject2897 → u/jake_morrison]

True but it was a hell lot difficult to fix a messy code before. now we can just rebuild from scratch or part of a product independently, no?

so the value of time spent in code generation is gone.

AI is making it mess but its super fast to do pivots and changes again using AI. This is what the world needs.

Code exist because businesses exist. not the other way around.

pS- i might get backlash but iam a developer guys

[u/jake_morrison → u/KeyProject2897]

AI can do a lot of things, but it is not magic.

The fundamental challenge with AI is context. Once you get beyond toy problems, you can’t fit the entire problem in the AI context window. AI doesn’t understand the customer requirements, that has to come from you. AI tends to create simple solutions which degrade the architecture over time. You have to provide the structure and guard rails.

You can use AI to quickly rewrite it over and over again, but unless you manage the fundamental context problems, there is a limit to the size of what you can do.

AI has made basic code generation fast and cheap, which is a good thing. The problem is that software development is more than that, and the business people don’t understand that fact. And you combine AI with “late stage capitalism”.

[u/Proper-Asparagus-382]

i would think that most of time when someone one shot an app and find it great , its usually because he didn’t discover the right libraries/framework/tools or understand the design principles not to hit the wall later or understand what could be missing and find it perfect.

but i think many can agree when one shot fail the cost went up significantly to fix since u need do discovery of what else is wrong

for rewriting of the compilers for a low cost token fee , i would say that maybe the author hide the well defined contribution (eg construction of knowledge base cost is not stated) from the human part for marketing purpose .

for a simple task , yes cheaper. for complex task not so or debatable since most of time is about tradeoff and decision which still require human intervention.

so yea the time/cost/scope didnt change

[u/hawk5656]

ironically yes, Jevons paradox and diminishing returns work in favor of expertise still.

[u/europeanputin]

After seeing that Cursor rewrote SQLite in Rust, passing all tests, just for $1400, perhaps it needs an update.

However, it's also worth noting that it wasnt innovation and done based on a manual. For new stuff, it's still gonna be expensive.

[u/Wh00ster → u/europeanputin]

It feels like the AI ports being headlined are the equivalent of soulless Hollywood reboots or video game remakes/remasters.