Day 8 of building StartupHQ: How would you visualize AI agents working in the background?
Day 8 of building StartupHQ.
A small milestone today: 6 founders have now tried the product. 🚀
Watching real people use it has been incredibly different from testing it myself. Every session uncovers something I never considered.
One thing I'm actively thinking about is how to make AI feel transparent instead of magical.
Instead of sending one giant prompt to an LLM, StartupHQ runs multiple specialized AI agents in parallel.
For example:
📈 Market Analyst
👥 Customer Researcher
🥊 Competitor Analyst
🎯 Positioning Strategist
💰 Pricing Expert
🚀 GTM Specialist
⚠️ Risk Analyst
...and more.
Each agent researches a different part of the startup, writes evidence, and eventually debates with other agents before producing recommendations.
The challenge is...
Most of this work happens in the background.
Right now I've built a live dashboard (screenshots attached) that shows:
which agents are working
completed milestones
research progress
evidence collected
current stage of the pipeline
But I'm not convinced this is the best UX.
I'm trying to avoid the typical AI experience of:
spinner... spinner... spinner... here's your answer.
Instead, I want founders to actually see the research happening and build trust in the process.
If you were using a product like this...
How would you want the AI's work to be visualized?
Would you rather see:
Every agent thinking in real time?
A timeline of discoveries?
Live evidence appearing as it's found?
Agent conversations/debates?
Something else entirely?
I'd genuinely love UI/UX feedback before I go too far down one direction.
The part that stood out to me was wanting founders to trust the process rather than just watch it.
One thought: transparency isn't necessarily about showing more activity. It's about making the reasoning behind the outcome easier to follow.
Watching ten agents work in parallel is interesting, but understanding why they collectively arrived at a recommendation is what would build my confidence. I'd probably optimize for explaining the path to the conclusion over exposing every internal step.
That's a great way to put it. I think I was leaning too much toward "showing the work" instead of helping people understand why the recommendation makes sense.
My goal isn't for users to watch 10 agents doing busy work. It's for them to feel confident enough to say, "Okay, I see why it came to this conclusion."
I'm thinking the live progress is useful while the research is running, but after that the focus should probably shift to the reasoning and the evidence behind the final recommendation.
Definitely something I'm still figuring out, so I appreciate the perspective. It gives me a lot to think about.
Live evidence appearing as it's found is the one I'd bet on — a timeline of "what was discovered and why it matters" builds way more trust than watching agents think in real time. Streaming raw agent chatter feels transparent but usually reads as noise to non-technical founders. Maybe progressive disclosure: a calm summary up front, with the agent debates one click away for those who want to dig in.
I think transparency is important, but I'd avoid showing every agent's reasoning. Most users (from my experience) care about why a recommendation was made, not every intermediate thought. A timeline of milestones with supporting evidence sounds like the best balance between trust and usability.