Doesn t have to be a start up book (you know the usual suspects: blitzscaling, the lean start up .) it can be though. Can be anything that you feel enhanced your life in any way shape or form. Can even be fiction. I think there is a lot of real world insight to get from fiction as well.
The hardest bugs to spot in LLM-based apps are the ones where the output looks totally convincing at first glance. I had a bug where the model filled in missing fields ran a search and verified the result except it verified the result against its own generated text rather than the original input.
All my basic tests passed because the output data looked super clean and accurate on paper. It made me realize how dangerous it is to let LLMs modify source data instead of just using them for quick search suggestions.
What kind of checks or boundaries do you write in your code to catch these silent logic bugs?
There s a weird comfort in spending a whole afternoon adjusting padding, shadows, and color codes. At the end of the day, you look at a pretty screen and feel productive even though you didn't talk to a single potential customer or test an actual assumption.
We often build fancy wrappers around products because facing harsh feedback from real users is genuinely scary.
Have you ever launched a polished interface only to realize nobody cared about the design because the core problem wasn't even worth solving?
It feels nearly impossible to find a straight answer online when you're trying to buy a new SaaS tool. Most top-ranking review sites are just affiliate blogs pushing whatever pays the highest commission and if platforms start locking user discussions behind login walls finding real feedback is going to become even harder.
I've started relying more on niche community Discords and indie maker forums just to see what actual users are complaining about.
When you're about to pay for a new software tool what is your trusted spot to check if it's actually any good?
I used to be terrible at giving direct answers because I hated disappointing people or turning down feature requests. So I'd just say "let me look into it" and leave users hanging for weeks while I tried to figure it out. Looking back that silence was way more frustrating for them than a simple "we aren't building this right now" would have ever been. People can handle a rejection they just hate being ignored or strung along.
How do you usually handle feature requests you know you'll never actually work on?
A few years ago, AI at work meant smarter autocomplete or a chatbot on your website.
Now, I m seeing something different.
Companies are experimenting with AI agents as teammates - not just tools. They schedule meetings, file reports, analyze data, and even handle parts of customer support.
There s a lot of noise about AI taking jobs, so I want to share what we ve actually seen and hear what s happening at your companies. A few patterns keep showing up:
Nobody on our team lost their job, but focused on efficiency
Roles change shape to become more creative
Hiring changes quietly. Companies aren t always firing anyone. They re just not hiring the next support person they would have hired a year ago.
Anything involving judgment, an upset customer, or a decision with real money behind it has stayed with humans for us.
My honest take? I think this goes way beyond AI helps you work faster. These agents are actually doing the work now.
So I m curious: Has AI removed, changed, or created a role at your company? or If you re hiring less because of AI, which roles? and What task did you expect AI to handle that it still can t?
Simple question - as part of your marketing strategy, personal branding, or just maybe some thoughts on paper kind of deal. Would love to hear people who blog and the reasons why Also perhaps a bonus - maybe how you grew your blog if you managed to do so? For me personally, I managed to grow on Medium but it did take some time!
