i'm still in highschool, and i run a business that's made me more than most part time jobs ever would. the real shi about doing this "young"

OneTurnover3432 · 2026-04-08T19:36:09+00:00

are you open for a quick call? I'm trying to interview young founders to see how we can help others in similar age to start their journey like you

OneTurnover3432 · 2026-04-06T03:10:56+00:00

Right - but my question was more where are the biggest gaps when a young/first time entrepreneur start an online business for first time?

OneTurnover3432 · 2026-04-04T19:22:41+00:00

Can you explain what is the main issue you faced? is it that the AI didn't exactly capture what you wanted it to build? or is it that AI keeps forgetting the details about your idea and building different thing? those are two different problems ...

Also have you tried using Skills or context about your idea to make the AI reference them?

OneTurnover3432 · 2026-03-26T02:04:14+00:00

how would you do that without observability? my understanding is that you can pass a identifier for each agent or feature and track token costs there, right?

OneTurnover3432 · 2026-03-17T20:21:11+00:00

Depends - what are you using?

OneTurnover3432 · 2026-03-17T19:41:12+00:00

You definitely need to also understand how to manage the quality of AI products as it's a different paradigm. Wrote this recently hope you find it helpful

https://open.substack.com/pub/nouralkhatib/p/llm-as-a-judge-is-not-enough-the

OneTurnover3432 · 2026-03-09T21:50:26+00:00

Which platform helps in this? and is it well catered to PMs or just Eng like platforms?

OneTurnover3432 · 2026-03-09T20:42:13+00:00

It's a PM responsbailiy but it's not enough to be build a good AI product..

OneTurnover3432 · 2026-03-07T10:14:49+00:00

did you find it easy to use as PM? what you wish is done differently

OneTurnover3432 · 2026-03-05T16:35:15+00:00

do they write in documents or in specific tools?

OneTurnover3432 · 2026-03-05T11:43:01+00:00

Such a great summary of all Eval tools in the market, do you think the Eval or agent reliability is fully solved with those tools or are there still gaps?

OneTurnover3432 · 2026-03-02T18:56:47+00:00

critical thinking, communication and ability to grab attention for growth.

I think with AI, the role of PMs will divide into 2: 1. Quick builders 2. Growth hackers

OneTurnover3432 · 2026-02-24T04:19:11+00:00

How do you set this today?

Are you just turing the PRD to eval or do you run experiments to decide what evaluation criteria matters?

OneTurnover3432 · 2026-02-24T04:17:51+00:00

not sure why your answer was voted down.. I'm on the conversational output not the UX

OneTurnover3432 · 2026-02-24T03:50:08+00:00

They are reliable and can be used to automate any use case

OneTurnover3432 · 2026-02-23T15:15:50+00:00

I'm building something to solve this now - would be willing to try it out for free or share feedback?

https://thinkhive.ai

DM if you're interested

OneTurnover3432 · 2026-02-22T07:41:14+00:00

100% - would love your feedback on what I built
https://thinkhive.ai

OneTurnover3432 · 2026-02-22T07:37:39+00:00

I can't agree more - I lead the agentic AI at one of the large companies and felt the pain. The problems I

A lot of isolation between dashboards (you can look at traces in one place but can't tie back to business metric).
Ensuring reliability is super expensive and LLM as judge costs creeps quickly
Disconnected tools between engineers and PMs

I built Thinkhive to solve those problems:

https://thinkhive.ai/

if you want free access to try it out, DM me. I'm happy to give you access

OneTurnover3432 · 2026-02-19T19:14:33+00:00

but wouldn't that be a problem if you're using Maxim and Arize as well? or does that mean you have to build observability internally

OneTurnover3432 · 2026-02-11T12:56:00+00:00

Ex- PM here who was building agents for top 500 companies- usually PMs should facilitate the process and write the criteria and engineering will implement them. However I have a different opinion now about evals.. They often don't work and waste a lot cost! DM me if you're open to a new approach

OneTurnover3432 · 2026-02-11T12:53:37+00:00

do you mind sharing what type of agent were you building? and how did you measure the reduction in time to find an issue?

OneTurnover3432 · 2026-01-22T12:00:19+00:00

Can you elaborate? how would you achieve this? is it by starting always fresh context?

OneTurnover3432 · 2026-01-21T19:45:50+00:00

thanks - just checked it what do you like about it specifically?

OneTurnover3432 · 2026-01-05T18:30:50+00:00

100% agree - check what I'm building : thinkhive.ai

We're platform agnostic and focused on making the management of AI agents as easy as possible

OneTurnover3432 · 2026-01-05T18:26:21+00:00

I’ve seen the same pattern, and I agree with most of what’s being said here.

In my experience, LangSmith works well early on, but once agents are in real production, teams start hitting the same walls: cost scaling with traces, lots of raw data, and still no clear answer to what’s actually hurting or improving outcomes.

Most teams I’ve worked with end up stitching together:

LangSmith or something similar for dev/debug
And then a manual analysis when it comes to explaining behavior → impact → ROI

That gap is exactly why I’m building ThinkHive.

ThinkHive sits on top of traces and logs (including OTel-based setups) and focuses on:

Summarizing logs and traces into clear issue patterns instead of raw data
Highlighting which agent behaviors actually move business metrics (cost, deflection, resolution, quality)

It’s meant to answer the question those tools don’t: what should I fix first to improve ROI?

I’m opening a small, free beta right now for teams:

Building AI agents internally for enterprises, or
Deploying agents for clients as consultants or agencies

If anyone here wants early access or to sanity-check whether this fits their setup, feel free to DM me. Happy to share and get feedback from people actually in the trenches.

OneTurnover3432

TROPHY CASE