Back when I was doing dropshipping, honestly the worst part was testing. You find a product, make the store, run ads... and a week later you find out nobody wants it. Money gone.

So how do you do it now?

• do you test before launch or just launch and pray lol

• what's the cheapest test that actually worked for you?

AI tools can now analyze years of employee performance reviews, retention metrics, and project outputs to generate hiring profiles and team structures: "hire for X trait," "keep teams under Y size."

I ve spent over a decade leading cross-functional teams, and I m skeptical. Not because the AI can t spot correlation, but because I ve seen how easily corporate data misrepresents human dynamics. A team can look high-performing on paper while burning out its best people behind closed doors. If the AI learns from that HR record, it standardizes burnout with total confidence.

Here s where I ve landed so far. I d need three things before acting on an AI-generated organizational lesson:

1. The qualitative feedback, visible. Skip-level notes, team sentiment, and anonymous feedback loops. Not just productivity charts.

2. The market context at the time. A hyper-aggressive growth playbook from a bull market will backfire in a retention-focused downturn. The lesson should state when it applies.

3. A leadership sign-off. A manager who navigated the human side confirms the nuance before it becomes an algorithmic hiring filter.

Our brain run on autopilot more often than we realise. One such behaviour is hearding, where we have the tendency to follow group or try to in a group. Imagine a few people suddenly started running. You don't know what's happening, but you might start running too, assuming they know something you don't?
Now, lets apply this into Cusomer behaviour, a D2C product goes viral and suddenly everyone wants to try it. A resturants has a queue outside it, we assume food must be good. A SaaS product gets #1 on product hunt and everyone wants to know what it does.
This i find really intriguing, becuase popularity can become a shortcut for credibility. (PS not shade to people who gets #1 on this platform a very big deal and hardwork) I'm just naturally curious on cusomer behaviour, read this paper recently in harvard business review about how fast consumer behaviour is changing in this decade.
Curious to hear what other makers think.

Got three outreach messages this week that all mentioned something specific about my product, referenced a post I made, sounded like someone had actually looked at what I do. Replied to one with a simple question. Took them over a day to answer something a real person would've typed back in a minute.

That's the weird part now. A bad cold email used to be easy to spot, generic greeting, no personalization, obviously copy pasted. Now the personalization itself is automated, so the one thing that used to signal someone actually cared doesn't mean anything anymore.

I wonder how people are handling this from both sides. If you send outreach, are you leaning into AI personalization or avoiding it because you think people can smell it now. And if you're on the receiving end, has anything actually worked to tell real interest apart from a well disguised template before you waste time replying.

I ran git log on my main project this morning instead of writing code.

First commit is 1 November 2023. Today is day 1,038. There are 550 commits in it, spread across 103 distinct days. 935 days have nothing at all.

When I first started designing, I focused a lot on making interfaces look polished. Over time, I realized usability and clarity usually matter more than visual effects.

One example for me was simplifying layouts instead of adding more components. Users completed tasks faster, even though the UI looked less "fancy."

I used it for a year or two, but eventually went back to iTerm because I found the UX to be over-complicated and slowed me down. (Also, I'm a dinosaur with too much muscle memory to overcome...) But the AI features were interesting, so I'm curious what ya'll see as alternatives, or if you think I should give it another shot.

One benefit I see is that it will usually produces something very politically correct that will usually go through the endless censorship that has taken over the internet (personally on the web since beginning of the 90's it was something else entirely, a mix of academic papers & free flowing ideas on clumsy graphics all over the place - oh boy that was so much decentralized and fun).

But then I only see problems: flatness, falseness, shallowness, lack of originality, creativity and most of all the dependency it slowly develops.