> The pull request model on GitHub doesn’t carry enough information to review AI generated code properly — I wish I could see the prompts that led to changes. It’s not just GitHub, it’s also git that is lacking.

Yes! Who is building this?

Create a folder called "prompts". Create a new file for each prompt you make, name the time after timestamp. Or just append to prompts.txt

Either way, git will make it trivial to see which prompt belongs with which commit: it'll be in the same diff! You can write a pre-commit hook to always include the prompts in every commit, but I have a feeling most Vibe coders always commit with -a anyway

It's not just that. There's a lot of (maybe useful) info that's lost without the entire session. And even if you include a jsonl of the entire session, just seeing that is not enough. It would be nice to be able to "click" at some point and add notes / edit / re-run from there w/ changes, etc.

Basically we're at a point where the agents kinda caught up to our tooling, and we need better / different UX or paradigms of sharing sessions (including context, choices, etc)

>SaaS valuations are built on two key assumptions: fast customer growth and high NRR (often exceeding 100%).

They are also on the basis of high gross margins of 80-90%. What happens to margins when you start including token variable costs?

I often summarise HN comments (which are sometimes more insightful than the original article) using an LLM. Total game-changer.

Can you imagine the insights on human behaviour that she has had?

Yet, this applies for only three industries so far - coding, marketing and customer support.

I don't think applies for general human intelligence - yet.

What happens to Ben's aggregator theory in a world of LLMs where marginal distribution isn't zero any more but the cost of energy and inference?

The majority of these hidden truths are due to senior engineering management in their 40s and 50s who have not coded in decades, and yet pick up the latest trend or fashion and impose that on their teams.

The monolith to microservices trend was one great example of this.

Is SEO basically the same as GEO?

How is it that we always come back to coding in terms of model capabilities?