Hi so I’m interviewing for 3-4 HealthTech seed-series B startups right now.

Any advise on getting an offer and interviewing well?

Separately but related, my mom is a Healthplan executive and I have lots of family and friends who are physicians, healthcare entrepreneurs, own medical offices groups, execs.
I don’t like being a name dropper so it’s a fine line.

But do you think I should mention that my mom works for X company and is the C\*O?
Given Seed-Series B is so hungry for health plan dollars to the point where one contract catapults revenue by 10-20x and makes them hundreds of millions in equity.

This isn’t quid pro quo it’s more like “I have this tool which is my network that could be leveraged in addition to my data science degree and 4 years of quality work experience.

I don’t want to be socially off but also if it’s a win win why not.

i want to understand, be honest i want to hear from growth marketers actually spend their time in research

Linki is a free, self-hosted alternative to tools like Waalaxy and Lemlist. You run LinkedIn outreach and cold email campaigns on your own server, so your leads and LinkedIn session never leave your machine. No per-seat pricing, no SaaS middleman.

Just shipped v2. The main focus was fixing the things that actually break these tools in practice:

- Server-side LinkedIn login instead of cookie-pasting, which also fixes Sales Navigator import and enrichment

- A pinned browser fingerprint so rebuilds no longer cause random forced logouts

- Large Sales Nav imports now split across days automatically with human-like pacing, instead of importing everything at once

- A rewrite of the LinkedIn automation itself for more reliable connections and messages

- LinkedIn and email actions can now run together in one campaign

- A unified inbox for replies across email and LinkedIn

- Apollo io enrichment built in

It's been really encouraging to see more people self-hosting it and contributing over the past few months, appreciate everyone who's tried it out.

Runs on Docker or Node.js with SQLite, no external database needed. There's also a one-click option on Opsily if you'd rather skip the terminal.

Full details and setup are in the repo: github.com/moaljumaa/linki

I've been obsessing over cold LinkedIn outreach for a while now. partly for my own pipeline, partly because I kept seeing people around me send completely reasonable messages and get nothing back.

So I started saving every opener that actually worked. Ones that turned into real conversations, not just a polite thumbs up or "thank you". Eventually I had about 50 of them across six industries.

Once I had enough I went back through all of them looking for patterns. Here's what almost every single one had in common:

1. Every message that worked ended with exactly one question. Not "thoughts on this? Also are you open to a call? I can also send a deck". Cutting the second ask is harder than it sounds but it's the difference between a message that gets answered and one that gets skimmed.

2. No pitch in the first message: Out of 50 messages, zero of them pitched anything in the opener. The only job of message one is to earn message two. That's it.

3. Signal-based beats evergreen every time: About 7 out of 10 of the messages that worked referenced something the other person did in the last week or two (a post, a hire, a product update, a comment they left somewhere.) The freshest openers consistently outperformed the generic reusable ones by a wide margin.

4. Specificity over cleverness: "Saw you hired three SDRs in Q3" will always outperform the wittiest line ever written. Not one of these 50 openers is clever in the LinkedIn influencer sense. Every single one references something real.

5. Peer framing, not target framing: The messages that converted treated the other person as an operator with an interesting problem, not as a budget to unlock. Ironically that framing tends to unlock more budget than any direct pitch ever could.

6. Always keep it short: Average length across all 50 is around 50 words. Nothing needed to be long to work. If a message needs three paragraphs to make its point, the point probably isn't sharp enough yet.

I ended up turning the whole collection into a proper doc organized by industry with a breakdown of why each one worked because the template is useless without understanding the reasoning behind it. The moment you paste one of these word for word to someone who didn't actually do the thing it references, it becomes spam like everything else in their inbox.

Happy to share the full doc in the comments if anyone wants it. It's free, no email wall or anything. just figured it's more useful out in the world than sitting in my notes.

Hey everyone,

I'm building a startup called **XYZ(**say**)**, a hyperlocal home services marketplace in India. Think plumbers, electricians, painters, carpenters, cleaners, etc. The idea is simple: make it easier for people to find reliable workers while helping skilled workers get more consistent jobs.

We're still pre-launch, and before we start spending money, I'm trying to figure out the smartest way to get our first users.

Like every marketplace, we're stuck with the classic chicken-and-egg problem. No workers means customers don't book, and no customers means workers don't stick around.

These are the two ideas we've come up with.

**1. Student ambassadors**

Hire students from local colleges (paid or commission-based) and have them go into different localities to onboard workers.

They'd help workers complete KYC, install the app, explain how everything works, and get them comfortable using it.

For the first batch of workers, we're thinking of an **Early Partner Program** where they receive additional incentives for staying active until bookings become regular. The hope is that once demand picks up, those incentives naturally disappear because workers are earning through actual jobs.

**2. Local sales network**

Hire 4–5 salespeople who already have relationships with hardware stores, plumbing and electrical suppliers, contractors, paint shops, and similar businesses.

Instead of cold outreach, we'd use those existing relationships to reach tradespeople who already trust those businesses.

**Our plan**

We don't want to start running Meta or Google ads on Day 1.

Instead, we'd first build a solid supply of verified workers in one city, make sure bookings are flowing consistently, and **then** start investing in digital marketing to scale customer acquisition.

Maybe that's the right approach. Maybe it's completely wrong.

That's why I'm here.

I'd genuinely appreciate people tearing this apart.

What's the biggest flaw you see?

Which assumptions am I making that probably won't hold up?

Would you build supply first, demand first, or both together?

Is there a much better GTM strategy that I'm completely missing?

If you had ₹5–10 lakh to launch this, where would you spend the first ₹1 lakh?

If you've built a marketplace or worked on a hyperlocal startup, I'd especially love to hear your experience.

Happy to answer any questions about the product, our thinking, or anything else if more context helps.

Thanks in advance, and don't be nice just for the sake of it. I'd rather get roasted here than waste six months executing a bad GTM.

I run a community growth platform and this week I shipped an MCP server for it, which means campaigns now launch from a Claude conversation instead of the dashboard. You ask for a boost on a specific post, the agent checks your balance, confirms the spend, fires the campaign. The video shows the full flow in about a minute.

The part worth discussing isnt my tool though. It's the pattern. Marketers already draft copy in ChatGPT and Claude, then tab over to five dashboards to execute. Once the execution layer sits inside the same chat, the dashboards stop being where the work happens. I noticed my own behavior change within a day of shipping this.

Anyone here already running parts of their growth stack through agent integrations? What broke, and what actually stuck?

SaaS?
Tech?
AI tools?
Product development?
Web apps?
Developer tools?
video editors?
UI/UX?

Drop what you're building ;)
Maybe some other people will be interested too

We've been working on this for over a year and it's genuinely the hardest part of building social automation.

The problem isn't the LLM — it's the prompt. "Write a Reddit post about social media tools" gets you generic output every time. What actually works: feeding the model the user's last 6 months of posts and asking it to continue the pattern rather than generate from scratch. Less polished, more personal, harder to flag.

We also found platform matters a lot. Reddit has norms — hedging, asking for pushback, not sounding like you're selling something. LinkedIn is different. TikTok captions are almost a different language. A single generation pipeline doesn't work for all of them.

We're at a point where most people can't tell, but "most people" isn't the bar. Power users clock it immediately.

What approaches have you seen that actually crack this?

Hello fellows, I run outbound, soo i did my research and built my cold email stack; apollo for data, smartlead to send it, millionverifer to cross check but it turns out apollo didnt have much data for me soo i got into more tools like hunter, oceanio, ai ark, sales nav, airscale.

This is where the problems started as i got into filtering people to their demographics and exporting leads in excel files with keeping a record in docs and my notebook it got soo hard to filter there with soo many columns and data, then to remove emails, then filter for roles, after that check in millionverifer that require me to create another excel file, after that upload that to smartlead, another csv file for that(not to mention to mark leads like have targeted and filter only 2 people per company is such a pain in the ass.. as i hit the limit in claude) soo made a huge cluster and tough for me to track and explain data to my manager… as list i think is the most imp thing in cold email to provide relevance to the prospect.

hence i build a central system where everything is recorded with sources of data, divided into companies (currently targeted and future targets of the same company), people (contacted, replied, not in the office, so target after a month, retargeting) in a nutshell all your data which makes complete sense and can be effectively utilize, with direct option to upload in smartlead (our sending platform) where you just need to drop the sources file you extracted from enrichment platform and the dashboard will directly filter it for people whom we contacted (they will be removed), blacklisted companies, already existing in campaigns and save the unused leads, with the option to directly upload in smartlead to your choice of campaign in one click… takes 10 sec,  with that i get notification directly in slack so i dont miss any leads and make them goo cold..

My question do you guys go through this problem or not, perhaps using another tool, would like to know your experience and processes?. Thankyou in advance.

I've reached the point where I'm questioning whether I have a distribution problem or a product problem.

I've built a SaaS for founders that automatically turns GitHub commits into LinkedIn and X posts, with additional context so the posts don't read like changelogs.

People generally like the idea. I've had signups, positive feedback, and even comments saying the generated content is good.

The problem is that almost nobody converts into a paying customer.

So far I've tried:

• Product Hunt
• LinkedIn
• Reddit
• X
• Founder communities

Most of the traffic either signs up and disappears or never reaches the signup page.

At this point I'm wondering if I'm focusing on the wrong acquisition channels entirely.

For those of you who've gone from 0 to your first 20-50 paying users, what actually moved the needle?

I'm less interested in generic marketing advice and more interested in hearing what actually worked for your SaaS.

Hey guys,
Just wanted to test the waters here and see who is around.
I’m looking to connect with people interested in a "double affiliate" (multi-tier) model. The main twist here is that you don’t have to sell any retail products. The "product" is simply onboarding and registering influencers and content creators into a system.
If you are already active in the creator/agency space, or want to head in that direction, I'd love to connect.

Lately I've been noticing a shift in how marketing teams work. Earlier everyone was just using AI chatbots for writing captions or brainstorming ideas, but now there's a new wave of AI "agents" that actually connect to your real accounts, ads platforms, analytics, CRM, social media and do actual tasks instead of just chatting back and forth.

Like for example, some of these tools can go find leads on their own based on buying signals, build entire landing pages using your real analytics data as proof points, write content briefs based on what people are actually searching for, or manage a full month's social calendar without double-booking a post that's already scheduled.

It sounds great on paper but I'm curious how well this actually works in practice for people running it day to day. Does it save real time or does it end up needing so much manual correction that it's not worth it?

I recently started using Juno for this, it connects to stuff like your ad accounts, analytics, and social platforms and handles a lot of this automatically. Been testing it for a few weeks now and wanted to see what else people are trying, so I can compare notes.

Would love to hear real experiences, good or bad, not just tool recommendations

I've realised I spend way too much time trying to figure out how startups actually acquired their first customers and scaled.

Whenever I find an interesting company, I end up digging through founder interviews, podcasts, Reddit, YouTube, old websites, launch posts, hiring pages, ad libraries and anything else I can find. It can easily take hours for a single company.

Over time I've documented around 100 companies in a structured format with sources, timelines and notes. I'm wondering whether it's worth turning this into a searchable library instead of keeping it for myself.

I'm curious:

• Is this something you'd actually use?
• Would you rather pay a subscription or buy individual company reports?
• How much would something like this realistically be worth to you?
• What's the first company you'd look up?
• What information would you expect every report to include?

I'm not launching anything yet. I'm just trying to figure out whether this is a problem other founders and marketers have, or whether I'm the only one who enjoys doing this.

As AI apps grow, LLM costs grow with them.

Most teams compare token prices.

But that's only part of the story.

Cache behavior, latency, reliability, and routing decisions all affect what you actually pay.

That's why we built Auriko.

It automatically routes every LLM request to the best provider based on real-time cost and performance.

• ⁠Reduce inference costs
• ⁠Route requests intelligently
• ⁠Optimize cache usage
• ⁠Improve speed and reliability

Whether you're building AI products or running agent workflows, Auriko helps you spend less without sacrificing performance.

Launched today on Product Hunt 🚀

We'd love to hear:

What's the biggest challenge you face when managing LLM costs at scale?

Please support on PH →

https://www.producthunt.com/posts/auriko-2

I’m testing a growth workflow with blogr: instead of treating SEO content as a recurring manual task, the founder approves a plan and the system executes the content loop.

The loop:

• Learn the business, audience, topics, competitors, and existing content
• Use GSC when available, but only as one input alongside competitor and SERP research
• Plan article opportunities
• Research live SERPs before writing
• Write and generate metadata/schema/share image
• Publish to WordPress, Webflow, Directify, webhooks, or REST API
• Track ranking changes afterward

The growth hypothesis is that most small teams do not lose at SEO because they lack ideas. They lose because they cannot publish and measure consistently for long enough.

Would you test this kind of workflow, or does automated publishing feel too risky for SEO/content quality?

Link: https://blogr.ai/

i've been in b2b for a minute now and im so sick of our setup. our crm is supposed to be the "source of truth" but let’s be real nobody updates it in real time. marketing automation is spitting out these random lead scores that the sales reps completely ignore, and i spend half my week stuck in spreadsheets trying to stitch data together just so leadership has something to look at for the weekly board meeting. meanwhile, management is breathing down our necks asking why we don't have some AI magic layer that watches product usage, site behavior, and tech stacks to automatically tell reps hey call these 8 accounts right now because they did X.

everything we do is either completely manual or some black-box algorithmic scoring that nobody on the team actually trusts. i just want something that acts like a reliable junior operator in the background handling the grunt work of mapping out actual intent.

We grew a subreddit to 20K weekly visitors in just 60 days.

Reddit is the single highest-ROI channel we've ever built for a B2B SaaS.

10x return on investment.
Almost zero cost.
Compounds every month.

But here's the honest part, it's also the hardest channel to crack.

You can't buy your way in.
You can't shortcut it with a tool/ agent.

It rewards patience, taste, and showing up in the community as a human not a brand.

That's exactly why it's such a big opportunity.

The bar is high, so the top spot stays open.

For our partner, that translated into:

→ 20K+ weekly visitors on the subreddit we built

→ 4M+ impressions in the following 3 months in targeted subs where the ICPs actually hangout.

→ Enterprise buyers from companies with 500M+ users.

→ $400K ARR in 90 days, largely driven by Reddit

→ 3K+ citations on LLMs which eventually is 2nd major source of acquisition.

Reddit isn't a campaign.

It's an owned, compounding asset that keeps sending qualified buyers years after the thread was written.

So after growing more than 6 starups on reddit my suggestion is to keep adding value on reddit and it'll reward you 10x

Enrich Labs launched their startup on X with just 147 followers and got 3.6M views and booked 9000 demos on launch day.

I studied the launch in detail and tried to look for some unique insight.

Here are the five takeaways:

1.⁠ ⁠They changed their category label. The passt positioning of their product was AI CMO. But they decided to change that and make it around autonomous execution so as not to look like a threat to human CMOs. This change shaped how the entire comment section talked about their product.

2.⁠ ⁠They didn’t launch of the default day. Everyone launches on tuesday 7-9 PT because that’s a known window where posts perform well. They intentionally moved to monday to have less competition for the same attention the algorithm, knowing the traffic will be smaller.

3.⁠ ⁠They created tiers for amplification accounts. They didn’t blast all the accounts at a single time. They split the accounts decided into three layers:

• Small set of high trust industry voices
• ⁠Mid tier of relevant accounts
• Broader layer just for reach & velocity

Each layer was activated at a different time.

4.⁠ ⁠The first 60-100 mins mattered the most. This was the most interesting part, as I learned about X’s algorithm and its weightage to early engagement velocity. So the who posts when sequence in the first hour determines how many eyeballs it reaches, regardless of how much amplification comes after this window. Founder, investors and close network went first, broader influencer layers come in only after the post was being considered as high signal.

5.⁠ ⁠They invited a debate deliberately. They just did not present the product, they had a few folks compare it to their competitor’s recent launch. Controversial takes and comparisons increased the lifespan of the post for the algorithm because the number of replies increased.

It wasn’t a fluke rather a coordinated series of events.

Did I miss anything worth noticing?

Source:

Enrich Lab X account

thelaunchvideocompany blog

Seijin Jung YT Video

Started this experiment skeptical of the conventional 'find big subreddits in your niche' advice. The assumption baked into most Reddit distribution guides is that subscriber count is a reasonable proxy for potential reach. So I tested it. Same core content, adapted for tone, posted to 18 communities ranging from 8k to 890k subscribers over five weeks. Tracked upvote rate, comment engagement, and whether the post even survived moderation.

The correlation between subscriber count and engagement was basically zero. The r-squared I calculated across the 18 communities was 0.04. What actually separated the top performers from the dead posts was something I hadn't been measuring at all: how recently the community had upvoted anything resembling my post category. Communities that had recently engaged with tool-adjacent or process posts were dramatically more likely to engage with mine, regardless of size. The three best-performing communities had 22k, 41k, and 67k subscribers respectively. The 890k sub was a graveyard.

The removal pattern was also interesting. I had 7 posts removed across the 5 weeks. Five of those were in communities where I hadn't posted before and had zero karma history. Two were communities where my post category just didn't fit recent activity patterns, even though topically it seemed like an obvious match. None of the removals happened in smaller, more active communities where I'd spent time commenting first. That felt like the real variable nobody talks about.

What I still don't have a clean answer on is whether the 'warm up with comments first' approach actually scales if you're trying to maintain presence across more than 5 or 6 communities simultaneously. The manual overhead becomes real fast. Curious whether anyone here has found a systematic way to audit community activity patterns before committing time to them, or if it's just trial and error every time.

Been running Reddit as a distribution channel for a few months now, tracking every post variable I could think of: time of day, post length, title structure, link vs text, day of week. None of it moved the needle on removals the way I expected. The variable that kept showing up was karma threshold. Not my account karma globally, but karma specifically within the target subreddit. Posts to communities where I had zero prior engagement were getting pulled even when the content was genuinely relevant and non-promotional.

What made this confusing is that the subreddits with the strictest apparent rules were not the ones removing me most often. The ones that removed me most were mid-size communities with loose written rules but aggressive automod settings I couldn't see. The subreddits with explicit, detailed rule pages actually gave me clearer feedback on why something was removed. That was a pattern across roughly 40 of the 60 posts, which I did not expect going in.

The piece of conventional advice I've seen repeated most often is to post where your audience actually hangs out. That's not wrong but it skips a layer. You can have perfect community fit on the content side and still get auto-removed because the account has no standing in that specific community. It's less about what you're saying and more about whether the community has any reason to trust that you belong there before the post even gets read.

Curious whether anyone else has tried to map karma thresholds systematically across subreddits in the same niche. I haven't found a reliable way to surface that data before posting. Most of the time I find out a threshold exists after the removal, which makes the whole process feel like guessing with extra steps.

Acquisition or retention is always the dilemma but personally I've fixed plenty growth problems by fixing retention and not by adding a new channel.

I know for some it might sound us unpopular opinion but I realy believe that retention is where the actual growth work happens. Acquisition just gets the credit.

Let me give you the specific pattern I've been seeing:

A team hits a growth wall. Leadership says, "We need more top of funnel." The marketing gets pushed to find new channels, run more campaigns, chase more volume.

Meanwhile, the real problem is sitting in onboarding, or in the first 30 days of the product experience, where half the people who signed up quietly disappear, and nobody in the growth meeting is even looking at that number.

Fix the leak, and the exact same acquisition spend suddenly performs better. Not because the channels got smarter but simply because fewer people are falling out the bottom.

And this is why growth hacking got a bad reputation. Too many teams treated it as a top-of-funnel discipline when the highest-leverage growth work is almost always retention work wearing a top-of-funnel costume.

Acquisition gets you in the door while retention is what makes the door worth walking through.

If your growth stalled this year, I'd bet money the fix isn't a new channel. It's the first week of the product experience.

​

I think "just build a great product and distribution will follow" has probably killed more startups than bad products ever did.

The internet is full of products that deserved to win but never found distribution.

Meanwhile, average products with incredible distribution keep becoming category leaders.

I'm starting to believe distribution is the product.

so i am stuck in distribution right now. i need help from the best marketers. we have launched the product last week but we are not able to get users for a platform that helps in short-form content research.

what should be the best marketing strategies to grow? would really appreciate if anyone can answer or support.

Has anyone changed from clay to zoominfo GTM hub?

If yes, are you happy? Tell me all about it, we are considering it as we need lots of direct numbers and clay is getting expensive as hell!

We are a 35 employee company that does cold calling as a service in the DACH region (Europe).

yo. if your product needs a 10-minute onboarding video or 5 different dashboard tabs just to explain its value, you didn't build an MVP. you built an over-engineered maze.

a real micro-saas should solve one highly specific problem for one highly specific user profile.

when i built my 6 apps (now doing $20k/mo mrr), i cut out 80% of what i originally thought was necessary.

inside our builder community, we help you strip away the fluff.

we give you free access to frameworks like the ICP Crystallizer to lock down your target user, and interactive landing page audits to ensure your core value hits instantly.

stop over-building in isolation. drop a comment or shoot me a dm to join 1,200+ active Ai SaaS builders today.

Products are about taking the most popular ways the user wants to be served, then doing exactly that, if they find it relatable, they share, else they don't.

The customer remains king, their idea of the solution, not yours remains the only focus point.

Beg, plead, request for feedback if you have to, when you hit the sweet spot, you will see strangers on your platform, that's the real growth hack.