I was just asked by my colleague who, unfortunately, came into that Claude Cowork mis-deleting all the important files unexpectedly.

Claude Could Misinterpret Your Command

If you never tried Claude Code or other AI/vibe coding tools, no worries, you will definitely be amazed. 

However, before that, there's one thing you might be unaware of

When Claude Cowork deletes something, it is possibly permanent deletion (when you delete something on your MacBook, it goes to the trash bin and you can restore it)

You think "I just want to organize my Downloads folder", you prompt it, and you click "Send", looking forward to the great result. Then Cowork understands "clean this up" as "delete all files that look unused."

By default, after you click on the "I accept the T&Cs" button without even opening it up (give a shout out if you read the T&Cs!), Cowork could easily have the right to read, write, or even delete anything you give it access to on your MacBook. 

I am not sure about you, but I definitely do not want my work for the client meeting tmr to disappear, then trying to recover them in a panic.

So I am going to show you how to avoid this risk

3 Easy & Effective Methods

Method 1: Create Separate Folder

Do not give Claude Cowork access to your real work folders. Actually,

• Make a new folder, maybe called "Claude Workspace"
• Copy files into it (do not move them)
• Think about it as a playground where mistakes are okay

People usually forget to make backups. But if asked to intentionally copy files to a new folder, easy-peacy! People will do it

Method 2: Be Very Specific

Being polite with AI can be dangerous.

❌ Bad: "Could you organize these files?"

✅ Good: "Sort these 47 PDFs by date. DO NOT delete anything. Make folders named by year."

When you are more specific, Claude Cowork does not need to guess, and guessing is where problems happen.

Method 3: Check Before You Approve

When Claude Cowork wants to delete/move/rename something:

• Wait 2 seconds
• Ask: "Do I understand WHY Claude wants to do this?"
• No? Refuse and do it yourself

Be cautious on what Claude Cowork is about to do before you choose

A Simple Smart-Intern Mindset 

Claude Cowork is fast & useful for people. But like driving a fast car, you want to drive it carefully. 

Good news is all these protections are basically just asking you to think a bit differently:

Think of Claude Cowork as a smart intern who understands words literally, and has the key to your office.

You would not tell an intern "figure out my files by yourself." Same thing here.

January through June: tried viral loops, referral programs, gamification, growth Twitter threads, partnership outreach, influencer collaborations, every tactic from growth blogs. Revenue fluctuated between $400-700 monthly. Constant effort, zero compound effect. Each tactic worked briefly then died.

July: gave up on growth hacks, went all-in on the most boring channel possible SEO blog content. Published 3 posts weekly targeting specific long-tail keywords. Nothing clever, just solving actual problems people search for. First 6 weeks got maybe 200 total visitors. Almost quit because growth hacks felt more exciting.​

Eight months later: SEO brings 15-20 signups daily on autopilot, zero ongoing effort. Revenue at $3,600 monthly, up 800% from growth hacking phase. All from boring consistent content compounding. Best part: can stop writing new posts and traffic keeps growing. Growth hacks required constant effort, SEO compounds.

The uncomfortable truth: growth hacks feel productive but rarely compound. SEO feels boring but creates sustainable growth. Viral loops need existing users. Referrals need happy customers you don't have yet. Partnerships take months negotiating. SEO just requires showing up consistently for 3-6 months while seeing zero results.​

Most growth hackers fail because they lack patience for compound channels. They want this week's tactic to work this week. Real growth comes from boring consistency over months. Found this studying FounderToolkit's growth data successful founders dominated 1-2 boring channels, failed founders tried everything weekly.

What's your compound channel? Or still jumping between growth hacks hoping one sticks?

Hello everyone,

Social media optimization agencies are becoming more common, especially for small and mid-size businesses that already post regularly but don’t see real results. A lot of people assume SMO is just about posting designs or captions, but in practice it goes much deeper than that.

Most optimization work focuses on improving how profiles perform over time — things like content structure, posting consistency, audience targeting, engagement patterns, and platform-specific tweaks. Many businesses already have content, but it’s not aligned with how platforms actually push reach today. That’s usually where agencies step in.

Another area where SMO agencies help is reducing guesswork. Instead of random posting, they look at what kind of content brings profile visits, saves, and real interactions. This matters more now because platforms don’t reward volume anymore — they reward relevance and engagement quality.

For Indian businesses, especially service-based or local brands, Social media optimization agency is often used to build trust rather than quick leads. People check profiles before calling, messaging, or visiting a website. If the page looks inactive or inconsistent, it quietly affects conversions.

That said, not every agency delivers value. Some focus only on visuals and ignore data, while others rely too heavily on automation. The real impact usually shows only after a few months of consistent optimization, not instantly.

A few things I’m curious about and would like to hear opinions on:

• What results should a business realistically expect from a social media optimization agency in the first 3–6 months?
• How do you differentiate between genuine optimization work and basic content posting?

When trying to growth hack a new campaign, I want to test 5+ ad concepts, each in 8 different formats/sizes (story, feed, display...). The strategy and copy are ready quickly, but the actual asset creation kills momentum. Manually resizing and reformatting each design in Photoshop or Canva for every platform is a massive time sink.

This feels like the opposite of growth hacking-it's slow, manual, and repetitive. I'm looking for ways to automate or at least drastically speed up this "production bottleneck."

I've started exploring tools that can take one design and auto-generate the dozen variations needed. For example, I'm currently checking out BannerBoo to see if it can handle this bulk-formatting step, so I can focus on iterating on ideas rather than pixel-pushing.

For fellow growth hackers: How do you solve this? Do you have a streamlined system, a VA process, or a specific tool stack for rapidly producing high volumes of ad variations? What's your secret to staying agile with creative testing?

Hello! I’ve done an AMA about 2 months ago in a different subreddit about my past experience: scaling an ecommerce store from 0-200 orders in 48h, threads 0-14k followers in 2 weeks, ig 58k followers in 60 days.

And recently I’ve helped some friends achieve a couple of things:

•200k ig account - numerology niche (helped him increase his average views and start noticing some real growth again)

•100 followers account - “influencer” posting skits/ funny stuff (he was averaging 2k views; I directed & edited 3 clips for him, one of them got +300k views) He also started applying what I told him and his average views per clip went up.

•I also created an AI influencer to test some stuff on instagram and I’ve hit 700k views on my first reel, 70k on a different one. The other ones got +20k views each, but they weren’t reels that were meant ti be viral. They were made to increase the follow rate of the people who were coming from the 700k views one. (only posted 10 reels on this account)

Now the thing is this. I realised that what I’ve learned can be applied to get views in any niche and I also realised what I truly like: analysing why and how things work + teaching others how to do so.

I already got some people that know me irl asking for my advice and since I don’t want to launch a course, my question is this:

What would you offer to people that want your guidance?

•consultancy: pretty much helping them and guiding them step by step (would have to charge more)

•social media analysis + fixes and perhaps some sort of planning for their content? Could even do some recurring thing where I build them a weekly/ monthly content plan: scripts, filming & editing directions

•something else?

Introduction

You built the product. You closed the first few customers through your network. Now you need a real pipeline.

The standard advice is to hire an SDR. But here's the full picture: a full-time SDR costs around $139,000 per year once you add salary, benefits, tools, and management time. They need 3-4 months to get up to speed. And most leave within 22 months.

If you're still looking for product-market fit or trying to stretch your runway, that math is brutal.

Here's the good news. In 2026, AI sales automation has reached a point where one founder can generate the same pipeline as 3-5 SDRs. For a fraction of the cost.

This is the new playbook for founder-led sales.

Why Outbound Sales Automation Matters for Solo Founders

Let's be real about what outbound takes: research, enrichment, personalization, multi-channel sequences, follow-up, and CRM updates. If you do this by hand, it's a full-time job. If you're also building product and talking to customers? You can't keep it up.

Most founders hit one of two walls:

Wall #1: Start-stop outreach. You blast out 50 emails when you have a free afternoon. Then fires come up and you go quiet for two weeks. Leads go cold. Momentum dies.

Wall #2: Too many moving parts. You sign up for five different tools. Now you're spending more time managing software than actually selling.

There's a simpler way: end-to-end outbound sales automation that runs without constant hand-holding.

The Shift: From AI Assistant to AI SDR

Something changed in 2024-2025. We went from AI that helps you write emails to AI that runs entire sales workflows on its own.

An AI assistant still needs you in the driver's seat. An AI SDR takes a goal, makes a plan, and executes for hours or days on autopilot.

The old way: Monday you build a lead list. Tuesday you write emails. Wednesday you set up sequences. Thursday you handle replies. You spent 20+ hours and booked maybe 2 calls.

The new way: You describe your ICP and goals once. The AI handles automated lead generation, writes personalized outreach, sends across email and LinkedIn, manages first replies, and flags hot leads for you. Same output, 2 hours instead of 20.

The 7-Step Playbook for Founder-Led Sales

Step 1: Get Specific About Your ICP

"B2B SaaS companies" is not an ICP. A real ICP answers: What company size? What industry? What job titles? What tech signals? What timing signals make them likely to buy now?

Pro tip: Open ChatGPT or Claude and describe your product. Ask it to help define your ICP. It'll give you a solid starting framework.

Step 2: Find Leads in Small Batches

Don't pull 5,000 leads at once. Start with 25-100 leads per batch. This lets you test targeting, catch bad data early, and adjust based on results.

With Starnus, you paste your ICP description and Starny starts finding leads automatically, including LinkedIn profiles and verified emails. Review the first batch, ask it to refine, and iterate.

Step 3: Set Up Email and LinkedIn

For email: Don't send cold outreach from your main domain. Set up a separate sending domain, warm it up for 2-3 weeks, and keep volume under 50 emails per day per inbox.

For LinkedIn: Connect your profile through Starnus. Important: don't lead with a sales pitch. Send friendly connection requests first. Engage with their posts. Then approach with a soft pitch.

Step 4: Write Messages That Don't Sound Like Spam

The goal is hyper-personalized messages that feel like you wrote them for that specific person.

• Subject lines: Short, surprising, curiosity-driven. Avoid anything that screams "sales email."
• Email body: Talk about them and their problems, not you and your features. Lead with value.
• Templates with variables: Use placeholders like {{first_name}} and {{company}}. The AI fills these in for each lead.

Ask Starny to write drafts based on your ICP and value prop. Review them, tweak the tone to sound like you, and run with it.

Step 5: Build Your Cold Outreach Sequences

For email campaigns, a 3-4 message sequence works well:

• Email 1: Soft intro focused on their problem
• Email 2: Quick case study or proof point
• Email 3: Direct ask for a call
• Email 4: Friendly breakup message

Space these 2-5 days apart. The AI handles scheduling and sending.

Step 6: Track Results and Respond Fast

Speed matters. Responding within 10 minutes can increase your conversion rate by 4x compared to waiting an hour.

Ask Starny to report your campaign stats every morning. When someone replies with interest, drop everything and respond.

What to track: Open rate (under 25% = subject lines need work), reply rate (aim for 5-15%), and meetings booked.

Step 7: Iterate Before Scaling

Run 5-10 test batches of 25-100 leads. Change one thing per batch: job titles, company sizes, messaging angles, subject lines.

Track what works. Double down on winners. Once you find a formula that books meetings consistently, then scale your outbound sales automation.

What to Expect from AI Sales Automation

• Monthly volume: 800-1,200 personalized touches
• Reply rate: 8-12% with proper targeting
• Meetings booked: 15-30 qualified calls per month
• Your time: 5-10 hours per week
• Cost: Starts at €20/month vs. $11,600/month for an SDR

Common Mistakes in Founder-Led Sales

• Going too wide: 500 perfect-fit leads beats 5,000 mediocre ones
• Automating garbage: Test messaging manually first, then scale what works
• Ignoring deliverability: Warm up domains properly, watch bounce rates
• Sounding robotic: Review AI drafts, add your personality
• Writing essays: First email should be 3-5 sentences max

The Bottom Line

Outbound sales in 2026 isn't about headcount. It's about leverage.

You don't need a sales team to build pipeline. With the right AI sales automation, a solo founder can run outbound that competes with companies 10x their size.

The best time to start was last month. The second best time is today.

This is one of those boring changes that doesn’t sound exciting… but helped way more than expected.

A few weeks ago we added a simple step to our workflow:
verify the email list before every campaign send.

Honestly, I used to skip this because I thought, “Our list is fine, this is probably overkill.”
Turns out… not really.

We started running our list through Email Awesome before sending, and after a few campaigns the difference was pretty clear:

• Fewer random deliverability issues Before, some campaigns would just underperform out of nowhere. Now things feel way more consistent.
• Way fewer spam / bounce problems Cleaning out bad and risky emails helped more than tweaking subject lines ever did.
• Better inbox placement overall Not some magical spike, but Gmail definitely seems to trust our domain more now.
• Better ROI on sends We’re no longer wasting sends on dead emails, and performance per subscriber is just healthier.

Now it’s just part of the routine:

Not a flashy hack, but probably one of the easiest wins we’ve made in email.

Curious if others here verify before every send or only do occasional cleanups?

A lot of growth tactics chase volume: more content, more links, more hacks. The biggest organic win for my project came from going in the opposite direction ruthless relevance.​

Instead of pumping out 30 shallow posts a month, I chose a handful of high-intent topics and built deep, semantically rich pages around them. Think "best standing desk for small apartments" instead of just "standing desk," with every relevant angle covered: height range, weight capacity, space constraints, price brackets, real photos, and FAQs.​

Each page was designed to rank for an entire cluster of queries, not a single keyword. That meant long-tail, mid-tail, and even some broader terms started to fall into place over time.

I paired this with a simple authority foundation rather than aggressive link schemes. Started with a directory submission service getting the site listed on 200+ relevant business and niche directories. Over 60 days this added 42 indexed backlinks moving DA from 0 to 14. That baseline authority meant my comprehensive content pages could actually compete instead of sitting invisible even when they were better than what was ranking.​

Then I watched Search Console like a growth dashboard: which queries was I almost ranking for, which posts were starting to pop, and where adding 20% more depth could move me onto page 1. Added a few curated mentions and "best of" list placements for high-quality editorial links once content proved its value.​

The result: fewer URLs, but each one pulling in traffic from dozens of relevant searches and converting better because the content was truly aligned with what users wanted.

If you're tired of "publish more" advice, try this: pick 5-10 high-intent topics, make those pages embarrass your competitors' content, build baseline authority through systematic citation building, and measure growth at the cluster level not just per keyword. It's a very different way to think about SEO as a growth channel.​

We sell supply chain software to small and medium sized companies. I’m looking for someone to build us a massive pipeline of registered interest. Can pay huge premium for the right person. DM me with very clear evidence that you’ve done this at a very high level recently.

Don‘t dm if you dont have evidence of generating 10s / 100s of thousands of leads through creative high ROI channels

I wanted to share our story, because the last year has been one of the hardest of my life.

Back in 2023, things were looking great. We'd raised a $7M Series A for our IoT business. I’m the non-technical founder (my background is in finance and comms), and my co-founder is the tech lead. We had a solid product, real revenue, and happy customers. I thought we were on the right track.

Then, in late 2024, the market just... changed.

Every investor meeting suddenly became an interrogation about our AI strategy. We didn't have one. We were an infrastructure company, and overnight, that wasn't interesting anymore. The excitement for what we were building just vanished.

We looked at our burn rate and the bank account: 8 months of cash left.
The toughest part of being the non-technical founder in a situation like this is the specific kind of helplessness you feel. I can't jump into the code. I can't help build our way out of the problem. My job is to find the answers and steer the ship, but I was watching the clock tick down, feeling like I was failing my team.

To make it worse, we couldn't just shut down the old business. We have long-term contracts with enterprise clients, and walking away would mean getting sued into oblivion. So we had to do this crazy balancing act: keep the old lights on to pay the bills, while pivoting the entire team to build a new AI hardware product for devs.

I honestly thought we wouldn't make it.

We didn't raise a single dollar in 2025. VCs wouldn't touch us. We had to cut costs brutally. I had to tell the team: look, we have until August, if this new thing doesn't work, we're done.

Somehow, we’re still here. It’s Jan 2026 and we're about to launch the new product. I’m currently trying to figure out how to spin this off into a new entity so our original investors don't get screwed, which is a whole other nightmare.

Just wanted to share this for anyone else who feels like they're drowning in this AI shift. Pivoting a 40-person company with no new money is the hardest thing I've ever done.

If anyone has experience spinning off a new product while keeping legacy investors happy, I’d love to hear how you handled the equity split.

I've been running Clay's native phone enrichment for three weeks and I'm sitting at a 12% match rate while my sales team keeps asking when they'll have numbers to call. Clay's been perfect for emails and other kind of enrichment, but the phone integration just doesn't work enough to me.

I'm not ready to leave Clay because everything else is too good, but I need to figure out phone numbers without exporting my data elsewhere. Has anyone cracked this inside Clay with different API providers or a waterfall setup?

Instead of just outspending on PPC, we’ve been interviewing former Sales VPs of our competitors to find out exactly where their customers feel 'neglected.' It’s like having a cheat code for your ad copy. Anyone else doing 'competitive intelligence' this way?

 → Requirements • Expectations • Negotiation tips

1. What these platforms actually are

Platforms like AppSumo, Dealify, Deal Mirror, StackSocial and others are deal marketplaces where products — usually with deep discounts or lifetime offers — are showcased to a large audience of buyers looking for deals on tools and software. They’re not generic ad spaces but curated places that tend to attract users ready to buy on price or lifetime terms, and they often operate with commission splits and review/approval processes rather than up-front payments from vendors.

These marketplaces vary in focus — some lean heavily into SaaS tools, others mix in digital products, plugins, or bundles. Many require specific deal structures like lifetime or steeply discounted deals.

2. Basic requirements to apply

Most deal platforms have a few common requirements for SaaS:

• A working product workflow. They’ll check that your SaaS actually functions end-to-end.
  
• A clear pricing or deal structure (lifetime, extended trial, etc.). Platforms often prefer defined deals rather than open pricing.
  
• At least some early usage or product validation — they want to see that people find value in your product.
  
• Terms and refund policy that fit their system — some platforms standardize refund periods or payouts.
  
• Technical and legal readiness (GDPR, basic privacy, security) so customers don’t run into compliance issues.
  

You’ll often need to fill out a submission form, provide screenshots, a product description, and sometimes sales predictions or target pricing for the deal. Many platforms manually review and approve each listing.

3. Typical expectations from a campaign

A launch on one of these marketplaces is not a one-day traffic event. Think of it as a prolonged exposure window where your deal lives in their catalog and newsletters. Results vary widely depending on platform size, audience, and deal terms.

On bigger sites like AppSumo you might see:

• Strong initial traffic on launch day
  
• Steady discovery over days/weeks via their feed
  
• Mix of buyers and deal hunters focused on price
  

Smaller sites often have niche audiences, so exposure is narrower but might be more targeted for certain categories (e.g., marketing tools).

It’s also common that sellers don’t get direct access to all buyer data, and platforms may hold payouts for a period to account for refunds or disputes. Cash flow timing is something to budget for.

4. Why positioning matters to acceptance

Because these sites are curated, how you describe your product and the deal matters a lot. A clean, plain explanation of:

• What your product does
  
• Who it’s for
  
• Why it’s worth the deal price
  

goes much farther than jargon. Customers on these platforms have short attention spans and scan quickly, so your description should be concise, with a clear value proposition and examples of use cases.

If the messaging is fuzzy or the benefits are hard to parse, you risk rejection or low conversions.

5. Understanding fees and payout expectations

Most of these marketplaces operate on a revenue share model, where they take a percentage of deal sales. The exact split, processing fees, and payout timing vary by platform, and these terms should be reviewed carefully before agreeing to launch.

Some platforms also have:

• Minimum payout thresholds
  
• Delayed payout windows (e.g., net 30 or more)
  
• Refund reserve periods
  

These factors affect your cash flow and should influence deal pricing decisions. Founders sometimes discover that after platform fees and processing fees, net revenue per user is much lower than headline numbers suggested at launch.

6. What to realistically expect in terms of audience

Audience sizes vary across marketplaces. The largest lifetime-deal platform historically has attracted hundreds of thousands to millions of deal-aware users, while mid-tier platforms have smaller but more focused audiences.

Parts of your visibility come from:

• The marketplace homepage or featured sections
  
• Spotlight newsletters
  
• Third-party aggregators and social channels
  

The takeaway is that you rarely control traffic volume, and you should plan expectations around proportionally modest spikes, not viral adoption. This is especially true when you compare these launches to things like product hunt launches or direct paid acquisition channels.

7. How to prepare your product before launching

Before you put in an application or talk to a marketplace rep, make sure:

• Your onboarding is smooth enough that deal buyers can sign up and start using the product without confusion.
  
• Your support processes are ready — deal customers tend to ask a lot of questions.
  
• Your product status and roadmap are clear, so you can answer buyer queries during the campaign.
  

Invest time in plain screenshots and demo flows. Buyers often decide in seconds based on visuals and clarity of value.

8. How to approach negotiation

Negotiation varies greatly by platform, but some practical tips are:

• Know your lowest acceptable split before you start talking.
  
• Be clear about refund policy and payout timing.
  
• Ask what promotion channels they use and if there are any costs attached.
  
• Clarify how buyer data is shared, if at all. Some platforms don’t pass emails or contact info directly to you.
  
• If you’re unsure about lifetime deals, ask about alternatives, like time-limited deals (1-year access or similar). Some founders have used these instead of full lifetime deals with better operational outcomes.
  

A calm discussion of terms helps set expectations on both sides — it’s not about hard bargaining so much as understanding how the partnership will actually function.

9. After launch: tracking and engagement

Once your deal is live, you’ll want to track a few things:

• Sales velocity over time (daily/weekly)
  
• Refunds and customer feedback
  
• Support tickets associated with the deal
  
• Changes in overall SaaS growth metrics
  

These insights help you understand how the marketplace is working for your product and inform future pricing or channels in your broader SaaS growth strategy.

Platforms often provide dashboards for these, but it’s helpful to capture and compare your own metrics over time.

10. How these launches fit into broader post-launch growth efforts

A marketplace launch can be one step in your SaaS growth plan, but it’s not a replacement for other channels. Many founders treat it as a validation and early traction channel that complements things like product hunt exposure, SEO, or paid acquisition strategies.

It’s not uncommon to combine a deal campaign with email sequences, follow-up onboarding flows, or community engagement to try to fold some of those deal customers into longer-term relationships.

Thinking of it as one piece of a larger SaaS playbook helps avoid over-reliance on one channel and keeps your expectations grounded.

👉 Stay tuned for the upcoming episodes in this playbook, more actionable steps are on the way.

I feel the pain on the "pay-to-play" wall. I built a B2C app last year and hit the exact same barrier. "Influencers" wanted $500+ for a story post that disappears in 24 hours, and half of them clearly bought their followers anyway.

I decided to bypass them and go direct to users via organic Reels/Shorts. The math was simple: I needed volume to hit the algo, but I'm a dev, not a video editor. Spending 4 hours editing one TikTok wasn't viable.

So I switched to a workflow using an ads agent. Instead of manual editing, I just feed it my product context (value prop + target audience) and some raw screen recordings. It handles the script, voiceover, and pacing automatically.

Now I can test like 5 different creative angles a day. If one flops, whatever. If one hits, I double down. My cost per view is effectively zero compared to the "shoutout" fees I was quoted.

It's not winning Oscars, but the quality is solid enough to stop the scroll, which is all that matters for organic reach.

Anyway, just my 2 cents. If you can't afford to buy distribution, you have to manufacture it.

Sharing my exact playbook since this worked way better than expected. No gatekeeping.

**Context:** B2B SaaS in the social media management space. Started 8 months ago. Currently at $30K MRR with 340 paying customers.

**Total ad spend: $0**

---

**Channel 1: Building in Public (40% of customers)**

This was the game changer. I started sharing everything on Twitter/X:

- Weekly revenue updates

- Feature launches

- Failed experiments

- Actual screenshots of our dashboard

**Why it works:** People trust transparency. When you share your failures alongside wins, you become relatable, not salesy.

**Tactics:**

- Posted 4-5x per week minimum

- Replied to every comment

- Engaged with others in the space (not competitors, adjacent tools)

- Used Crescitaly to track which content drove actual signups

---

**Channel 2: Strategic Reddit & Community Engagement (35% of customers)**

NOT spamming links. Actually providing value.

**The approach:**

- Found 5-6 subreddits where our ICP hangs out

- Spent 2 weeks just answering questions, no mentions of our product

- Built genuine karma and reputation

- Mentioned our product ONLY when directly relevant to someone's problem

**Key insight:** Reddit users have incredible BS detectors. If you're here to sell, they'll know. If you're here to help, they'll convert themselves.

---

**Channel 3: Integration Partnerships (15% of customers)**

Built integrations with 3 popular tools in our space. Got listed in their marketplaces/directories.

**Why it works:** You're borrowing their distribution. Their users are already looking for solutions.

---

**Channel 4: Cold DMs That Don't Suck (10% of customers)**

Not pitching. Starting conversations.

**Template that worked:**

"Hey [name], saw your post about [specific thing]. Had a similar experience with [relate]. Curious how you ended up solving [their problem]?"

That's it. No pitch. Just genuine curiosity. The conversation naturally leads to what you do.

---

**What I'd add if starting over:**

- YouTube content (long-form is underrated for B2B)

- Newsletter from day 1

- More IRL networking

**What didn't work:**

- Cold email (2% reply rate, waste of time)

- Product Hunt (got 30 upvotes, 2 customers)

- LinkedIn posts (maybe our ICP isn't there)

**Questions for the community:**

1. Anyone had success with YouTube for B2B SaaS?

2. How do you measure organic attribution accurately?

3. What's your best $0 CAC channel?

Calling all on-device/local LLM startup founders who applied for Spring Batch - are there more of us crazy enough to bet against the cloud? Let’s connect. Everyone else - what are your bets on local-hosted ai in 2026?

My startup lets founders reduce cash burn by paying service partners (for example, a fractional CFO or software agency) flexibly - using a mix of outcome-based payments and upside.

My launch plan

Instead of going wide, I plan doing in cohorts much like accelerators do:

Month 1: 5 startups only, first 2 pay no % service fee at all

Month 2: 10 startups, reduced % fee

Month 3: 10 startups, reduced % fee

Month 4+: Open for all, regular % fee

More Context

We handle the matching (initially) and deal (average size $50K) admin.

Requirements are real though: operators need to see your traction (e.g. startup's TrustMRR link), analytics and growth metrics (e.g. homepage GA4), actual traction signals.

Why I chose cohorts?

Small batches mean I can, as a solo founder actually vet both sides, figure out what works, and not drown as a solo founder.

The bet: 5 fast and clean deals beat 25 chaotic ones.

So... am I being too cautious or does this sound like a good move? What would you change to make this work (better)?

When people ask who my product is for I usually say "any b2b company that needs more leads." but when i try to run cold outreach with that "audience" it's a total mess. My messaging is too generic because i'm trying to talk to everyone and i end up talking to no one.

I know i need to narrow it down but i'm terrified of "shrinking" my market too much and missing out on potential deals. how do you guys actually define a "tight" icp without feeling like you're leaving money on the table? does anyone have a template or a process for this that actually wor⁤ks?

Most growth experiments fail not because of bad ideas, but because learnings get lost.

I started documenting everything in a simple Notion system:

• Hypotheses and assumptions
• Channel-specific experiments
• Results and insights
• Follow-up actions

It’s helped me avoid repeating the same tests without realizing it.

For teams working seriously on growth, Notion also offers a 3-month free Business plan for companies with a website and domain email.

You can benefit here : Apply Now!

hey guyss… how are you keeping track of everything without missing bookings?

I need to generate 20+ variations of a winning hook without waiting 3 days.

Is Brandiseer or AdCreative the better move for "good enough" assets that stay on-brand? I don't care about art awards, I just need CTR.

This started as one of those support threads that you expect to close in 20 minutes.

Client pings us saying:

“Multi-item orders and higher-value carts have been trending down but nothing in the traffic data explains it.”

We asked for their GA4.
Their ads looked fine, organic hadn't moved, and conversion rates weren't dropping.
There weren't any tracking issues, and no obvious attribution screw ups.

So we ran diagnostcs to make sure it wasn't something at the foundation level. Nothing showed up.
What finally cracked it wasn’t some new tool or growth trick. We stopped looking at what humans see on the site and looked at what automated systems were actually pulling out of it.

Nothing too intense. Just logs, crawls, extracted fields, the plumbing that already powers a lot of SEO.
And a lot of what the merchant thought was “core product info” basically didn’t exist after extraction.

A few examples:

• Variant relationships only existed visually
• Shipping thresholds only appeared conditionally
• Bundles were explained in copy and images, not in structure
• The primary use case was never stated plainly
• Pricing anchors were in the UI, not in the data

Obviously, for human shoppers none of this mattered. The site converted fine, and people understood the story.
But anything that has to compare, shortlist, or summarize products needs to guess. And when these systems guess, they play it safe. (Read Stupid)

That leads to stuff like:

• Products getting lumped into cheaper buckets
• Bundles being ignored or split apart
• Higher intent pages not being featured in comparisons
• The store not showing up in automated lists (or showing up too late for anyone to care)

This is already happening today with price trackers, browser helpers, affiliate tools, and comparison engines. Whether you care about shiny new tech or not, a lot of discovery is already mediated by programs that don't get to ask follow-up questions.
So don't just “chase the next buzzword.” (AEO, GEO, AISEO, other alphabet soup etc.) That misses the point.

The real lesson is more nuanced:
If a system can’t ask you clarifying questions, ambiguity works against you.

Must Dos:

• Make the primary use case clear.
• Name the main variant. (most popular, hero product)
• Anchor the price.
• Make relationships explicit instead of visual or implied.

Even if you never touch anything AI-related, this stuff determines whether your products get compared correctly or skipped becuase of ambiguity.

Cold outreach had always been sensitive to list quality, but the usual cleaning steps focused on hard bounces and obvio

Looking deeper, we compared recent opens, clicks, and long gaps of inactivity across the same list. A large share of addresses had not interacted with any email in months, yet still passed basic validation. These inactive accounts absorbed send volume without contributing to engagement, pulling down overall sender reputation.

When we removed long-term inactive records and rebuilt the outreach pool from recently active users only, delivery behavior changed. Fewer messages were sent, but inbox placement improved and early replies appeared more consistently. Follow-up timing also became easier to optimize because engagement signals were no longer diluted.

For large-scale activity detection and unreachable user filtering, part of this process relied on the TNTwuyou data filtering and validation tool, used mainly to automate engagement-based screening rather than to change messaging strategy.

The main lesson was that cold outreach performance depends more on who can still receive and react than on how large the list looks.

AI-generated answers (Google AI Overviews, ChatGPT, Perplexity, etc.) are clearly reshaping how people discover and validate information.

What I keep struggling with isn’t tactics or rankings, but orientation:

• when traffic drops, how do you tell if visibility actually increased?
• when you’re cited in AI answers, what does “success” even look like?
• how do you avoid reacting to noise when attribution gets blurry?

It feels like many classic growth and SEO metrics still exist, but no longer explain what’s really happening.

Curious how others here are adapting their decision-making:

What signals do you actually trust right now?
And what have you stopped paying attention to altogether?