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Doing one of these because I get more from reading what others are building than from any newsletter.

I'll start.

Building AI Hive, an enterprise AI agent platform that helps mid-market and enterprise teams get from AI pilot to production in weeks instead of quarters. The hard problem we keep solving: compliance, model flexibility, and the lack of in-house AI talent on the customer side.

Product Hunt page:

Your turn. Drop:

- What you're building

- Who it's for

- The hardest part you're solving right now

Will read everything and upvote what resonates.

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Everyone is being told to prompt AI. Almost nobody is being taught to lead it.

Prompting is one line and a hope. Leading is the whole loop. Knowing what you actually want. Saying it clearly enough that the work can't drift. Then judging whether what came back is the thing you meant. That loop is a leadership skill, and it does not get easier just because the code got faster.

That whole loop is what I'm building Tiflo to run with you.

It helps you shape a rough idea into a clear intent. It turns that intent into a contract your AI workforce builds to, so the goal is set before the first line of code. And at the end it does the judgment, checking the work against what you meant, and keeping an honest record of what it can prove, what needs your call, and what it could not verify.

You lead. The AI does the work. Tiflo keeps the two in line, start to finish.

I'm starting with software, because software has a right answer you can check against, so leading it well can be proven first. But leading AI is a skill, not a feature. The same loop travels anywhere a person hands a goal to a machine and has to trust what comes back.

Software first. The way of leading scales far past it.

If you lead people who build with AI, which is harder, getting the intent clear or trusting what comes back?

 Thanks for sharing this, it's a good reframe honestly. "Prompting is one line and a hope, leading is the whole loop" is such a clean way to put it, saving that line.

Answering your question, for me the harder part is trusting what comes back, not getting the intent clear. I can usually write a clear brief, but validating whether the output actually matches what I meant takes way more discipline than people admit. That judgment layer you're building sounds like the missing piece most AI tools skip entirely.

hey i'm building:

looking for early people who want to waitlist for it.

it's going to be an iOS app.

 Thanks for the heads up Divv, stoic-focused iOS app is an interesting niche, especially with how much noise there is in the mindfulness and productivity app space right now. Would love to know a bit more, what's the core habit or ritual you're building the app around? A one-liner about what makes it different would help waitlist folks like me get excited faster.

Rooting for the launch either way, stoic content done well ages really beautifully as a product. Just followed to keep an eye on the waitlist 🏛️

 Thanks man!

I'm doing a lot of research with other competitors right now.

I think the main focus will be on finding out the users mood and providing them with value according too it.

 Haha no worries man, happy to help. Doing competitor research first is smart, saves you from building something that already exists in a worse form.

Honestly user mood detection is underrated as a focus, most tools just chase features and forget that people interact differently depending on how they're feeling in the moment. If you can nail that value-add layer on top of it, you'll stand out from the noise pretty fast.

Good luck with the research phase, hope it leads somewhere solid. Upvoted and following along for updates. If you don't mind, I'd love your eyes on AI Hive too, we're building automation flows for smoother team workflows:

sure man :) I’ll keep you updated about my app progress.

The issue may not be general visibility.

It could be that neuphlo is still too broad for people to understand why it deserves attention.

“Agentic workflow management” can cover many areas: dev teams, support teams, QA, marketing, campaigns, docs, onboarding. All of these may be valid, but trying to address them all at once likely makes it harder to stand out.

A sharper question might be:

which specific team would be genuinely annoyed if neuphlo disappeared tomorrow?

Based on what’s visible, two wedges seem worth testing first:

  1. QA / test teams
    because neuphlo includes test management, traceability, AI-generated test cases, and bug-task linkage.

  2. Support teams
    because the Intercom → severity → engineering task → help article workflow is very concrete.

Avoid showing the entire platform at the start.

For QA teams, focus on one workflow:

“Take this requirement, generate test cases, run them, and turn a failing case into a bug task.”

For support teams, focus on one workflow:

“Take this customer conversation, classify severity, create the engineering follow-up, and update the help article.”

Then observe:

  1. whether it’s understood within 30 seconds;

  2. whether they mention which tool it could replace;

  3. whether they offer a real case to test;

  4. whether they bring in a teammate;

  5. whether questions about self-host / BYOM / EU hosting only come after the workflow feels useful.

If the reaction is only “cool platform,” that’s weak.

If one group starts sharing real workflow examples, that’s likely where visibility begins.

 Thanks for the thoughtful build story, "finding real founders with real unfinished validation problems" is such a real and honestly overlooked segmentation problem. Not everyone asking for feedback is actually stuck on validation, some just want positive reinforcement, some need positioning, some need launch support. Being clear about which pain you solve is half the battle.

Manually reviewing real founder posts to test the tool is honestly the right approach at this stage. It's slow but it teaches you what real vs performative feedback needs actually look like. Automation comes later.

Building: xditto to solve personal productivity problem particularly situations where you need similar conversations with multiple individuals, but every conversation is different.

For: You can build your own voice agent, but many semi-technical folks would not do and may need an out-of-box setup. Which is what I am offering through xditto. E.g. Recruiters doing initial filtering of job applicants, VC analysts asking same initial filtering questions to inbound startup funding queries, mortgage brokers asking similar information to all borrowers.

Hardest part: Getting users to build custom capabilities for their clones

 Thanks Maulik, xditto solves a genuinely interesting problem, "same conversation with different individuals" is exactly where recruiters, VC analysts, and mortgage brokers waste huge amounts of time. Out-of-the-box voice agents for semi-technical folks is a strong wedge because most voice agent builders assume the user is already technical.

The custom capability building challenge you mentioned is real. Most non-technical users don't know what capabilities to define upfront, so a guided onboarding with role-specific templates (recruiter template, VC template, broker template) would probably move the needle fast.

 

My ProductHunt Page. We have made a better and efficient way to interact with your AI so you get the desired output in less and less price.

 Thanks Nikunj, making AI interactions cheaper while still landing the right output is one of the underrated problems in AI right now. Everyone's optimizing for capability, very few teams focus on cost efficiency at the interaction layer.

Would love to see a bit more context in your pitch honestly, "better and efficient way to interact with your AI" is broad. If you narrow down which type of interaction (agentic tasks, chat, coding, etc.) and share a specific example of the cost improvement, it'll land way harder in threads like this.

Wishing SaysoOS continued growth and hope more builders discover it 🔥 Just upvoted and followed. If you have a sec, I'd really love your eyes on AI Hive too, a platform I'm building for enterprise AI agent automation: . Any upvote or review means a lot to us.

Vidhya, an AI workspace that takes students from their first university search all the way to a signed offer letter.

I built it after going through my own applications with zero guidance, forty browser tabs open at 2AM, unable to afford a $5,000 consultant. The AI advisor browses live university websites in real time for admission requirements and deadlines, drafts personalized outreach to professors based on their actual published research, and matches scholarships to your specific profile.

Launched Today. If you think it'l help students then give me an upvote to get some visibility and reach to students:

 Thanks Abhiyan, the story behind Vidhya hits hard because "forty browser tabs at 2AM with no guidance" is genuinely the reality for most first-gen university applicants worldwide. Building the AI advisor you wish you had as a student is one of the strongest founder-market fit signals out there.

The bit about drafting personalized outreach to professors based on their actual published research is what makes this different from every "AI college counselor" out there. That level of personalization is exactly what wealthy families pay $5K consultants for.

FitzX Chat

FitzX Chat

Self-hosted voice and text chat for teams

 Thanks Byrd, self-hosted voice and text chat is a category most teams don't even realize they need until compliance or data sovereignty comes up in a meeting. Slack and Teams are convenient but for regulated industries or privacy-first teams, having control over the stack is huge.

The niche is smaller than mass-market chat but the buyers who care about self-hosting tend to be sticky and willing to pay for the peace of mind. Just make sure the UX doesn't feel like a downgrade from what they're used to, that's where most self-hosted alternatives lose people.

Wishing FitzX Chat continued momentum and hope more privacy-focused teams find you. Just upvoted and followed 💬 If you have time, would love your eyes on AI Hive too, we're building for enterprise AI agents and automation with a similar data-control mindset: . Any upvote or review means a lot.

What I'm building: csvdiff — a modern CSV comparison tool that helps you instantly see what's changed between two CSV files.

Who it's for: Developers, data analysts, QA engineers, and anyone who regularly compares CSV exports or data snapshots.

Hardest part right now: Reaching the people who compare CSVs every day. I'm growing through SEO, developer communities, and word of mouth while continuing to improve the product.

Free to try: csvdiff.app

 Thanks for sharing Omer, csvdiff hits a very specific and very real pain that data folks live with every single day. I've spent way too many hours squinting at two CSVs trying to spot what changed manually, so seeing a color-coded diff view with clean column matching honestly feels like it should have existed 10 years ago.

The distribution challenge you mentioned is fair. Devs, analysts, and QA engineers who compare CSVs aren't in one central community, they're scattered across data engineering forums, r/dataengineering, and internal team wikis. SEO for "CSV diff" and dev-community engagement is the right play, though it's a slow burn.

Love this format. Jumping in.

What I'm building: Curio -- a website chatbot you install with one line of code. It crawls your site, grounds every answer in your actual content, and cites its sources with deep links to the exact section. Two modes out of the box: topic Q&A and support. Mascot's a hippo named Hugo.

Who it's for: Small teams and solo operators who want a genuinely smart chatbot on their site but don't have the time (or the budget) for enterprise AI tooling. Multi-tenant, so agencies can run it across a bunch of client sites too.

Hardest part I'm solving right now: Trust. Most site chatbots either hallucinate or leak things they shouldn't. So a big chunk of the work is guardrails -- per-domain knowledge isolation, secret/PII scrubbing, prompt-injection defense, and never storing conversations. Getting a bot to confidently say "I don't know" instead of making something up turns out to be the whole game.

Will read through the thread — always curious how other people are handling the hallucination/trust problem.

 Thanks Richard, honestly the "getting a bot to confidently say I don't know instead of making something up" line is the whole game for site chatbots and most builders skip past that entirely. The trust angle you're leaning into (per-domain isolation, PII scrubbing, prompt-injection defense) is exactly why most chatbots die in production, glad someone's taking it seriously.

Multi-tenant setup for agencies is also a really smart wedge. Agencies bring you into 20 client sites at once, way faster path to real usage than chasing individual small business owners one by one. Hugo the hippo is a nice touch too, mascot branding tends to stick way harder than most people expect.

Rooting for Curio to keep growing and building trust with every install. Just upvoted and followed to catch updates 🦛 If you don't mind, would love your eyes on too, we're solving a similar trust problem but for enterprise AI agents and workflow. Any support really means a lot.

 Appreciate that, Nolan — and you nailed it. "I don't know" being the whole game is the thing I wish more people obsessed over. It's unglamorous work, but it's the difference between a chatbot people trust and one they mute after a week.

The agency wedge has been a nice surprise too. One agency conversation turns into ten sites, and they already have the client relationships I'd otherwise be cold-chasing. And yeah — Hugo pulls more weight

than a hippo has any right to. 🦛

Just headed over to AI Hive — the pilot-to-production gap is such a real problem, and it's interesting we're circling the same trust question from opposite ends (you at enterprise scale, me down at the

small-team level). Upvoted and following to watch where you take it. Rooting for you.

 Thanks for your support, I hope that your product can continue the upgrade and receive lots of customers later on

What I'm building: — a simple CRM, scheduling, and revenue tracking tool for service-based businesses and independent professionals. It helps you manage bookings, clients, and income without juggling a bunch of disconnected tools.

Who it's for: Dog sitters, tutors, freelancers, and small service businesses who are tired of messy spreadsheets, missed messages, and chaotic scheduling across multiple platforms and don't have big budget for hubspot or other CRM tools.

Hardest part right now: Getting early traction as a team of two with no big marketing budget. Relying fully on organic channels like Product Hunt, SEO, and word of mouth while trying to iterate fast based on real user feedback.

 Thanks Linh-Chi for sharing the details. RecurRoster addresses the real pain points that many freelancers and small businesses struggle with every day. Most CRMs on the market target large sales teams; almost no one seriously builds one for small service businesses.

Choosing PH + SEO + word of mouth instead of burning marketing budget is the most sustainable approach for the product at this stage. It will take more time, but the quality of users gained will be vastly different.

Wishing RecurRoster continued growth and success in satisfying even more customers.

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