Simo Lemhandez

I’ve always dreamed of a self-updating CRM. You define the structure, and the CRM does the work. It captures data where it lives (from the web, your notes, your emails, your calendar, or any other source) and it updates smartly whenever is needed. Today, we’re making this real with AI Fields — fields that update themselves automatically. Watch the magic for yourself. And if interested to try it out, just comment “AI Fields” and we will reach out to provide 1000 free credits.

@HodaMehr @FolkHQ Thanks Hoda for the words - feel free to DM if you need support on anything.

Been testing CRMs for founders (talent, advisor, investor, and customer pipelines all in one place) and so far @FolkHQ is the best. The LinkedIn and X integration saves significant time, and the built-in enrichment is decent. Well done @LemhandezSimo and team 👏

Because people are switching to @FolkHQ. 3 times the product for way less money.

@anirudhnarayan @FolkHQ

I’d love to try an AI native CRM that is 10x better than Salesforce or Hubspot. Attio isn’t it - marginal at best

We’re closing 300+ accounts in January. Below is a breakdown of our funnel, from visitor to paid account. 1️⃣ Attracting visitors We had 80k unique website visitors last month. We run a combination of channels: - Chrome Store SEO - Affiliations via @partnerstack : partners share folk with their audience and receive 30% of the revenue - @LinkedIn posts from myself, the team, and our community - Cold outreach, but it’s not a major channel for us - SEO (and yes, it’s not dead) - Paid acquisition (when run properly, it can be very efficient and scalable) - @YouTube videos: we invest heavily in high-quality educational content and partner with creators. Direct revenue attribution is hard (no direct click), but many leads mention having watched our videos during demos - GEO on @ChatGPTapp, @MistralAI , @claudeai , @GeminiApp , and others: attribution is also difficult here, but we consistently hear about it from prospects - Review platforms like @g2 and @Capterra : direct attribution is hard to measure here as well, but strong ratings significantly help users during the discovery phase. Attribution is a hot topic for many teams. We don’t spend much time trying to build a perfect attribution model. We track first click and last click, and we ask users during onboarding where they heard about us. That’s sufficient to guide our decisions. We’re not trying to be on every channel. We strategically pick the channels that matter to our buyers. We focus on a small number of high-conviction bets. Then we commit to making them work over time. 2️⃣ Converting visitors into sign-ups We get thousands of sign-ups per week. Again, nothing fancy. We invest in a simple, well-designed website that clearly captures our ICP’s problem. No fluff. No expensive animations. We also invest in: - Retargeting visitors on LinkedIn and Meta. Retargeting is low-hanging fruit if the assets are strong and the implementation is clean - Translations into other languages (we recently started using @weglot) 3️⃣ Converting sign-ups into demos Once there’s a sign-up (or a demo request directly from the website), it’s all about qualification. Our team’s capacity is limited, so we want their calendars filled with the best leads. We then use multiple ways to bring these leads into demos: - Emails and product tours via @intercom - Phone calls via @ringoverapp Demo scheduling is managed through @Calendly. Since we can’t offer demos to everyone, we also run webinars on @livestormapp twice a week. 4️⃣ Converting demos into paid accounts Once a demo is booked, it’s added to our folk pipeline. We track every customer touchpoint, including: - Calls (@ringoverapp) - Emails - Calendar events - WhatsApp conversations - Video recordings via @GrainHQ - @SlackHQ After the initial demo, we send a proposal (with a vibecoded onboarding guide built using @Lovable), and the closing happens via @stripe. That’s it. We keep things simple. This funnel keeps evolving as we identify new opportunities/bets.

The Workflow Assistant — and the backstory I often send the same emails multiple times a day. I use the same few templates to save time. Some common use cases: - Greeting a new large client when they convert - Sending a quote during an active discussion - Reaching out personally to an new interesting lead I then try to tweak the template to make it personal, looking at: - The company website - Any notes I have on the person - The latest interactions — email, LinkedIn, or WhatsApp I keep repeating the same workflow again and again. Sending an email when a trigger happens. Personalizing the template as much as possible then. So we decided to build this natively in folk. ① Set a trigger — for example, when a person is added to your pipeline or moved to a specific stage ② Choose an email template, with variables like {firstName}, {companyName}, or {jobTitle} ③ Let AI further personalize the email using recent notes and past interactions (email, LinkedIn, WhatsApp), just like a human would ④ Preview the email before it’s sent ⑤ Analyze workflow results like open rate, click rate, reply rate We launched Assistants last week and received a lot of strong feedback. Today, we’re zooming in on the Workflow Assistant.

@Lovable has changed our ability to build internal tools, starting with a « Deal room » We never found a good solution for deal rooms. Deal rooms are shared with prospects and contain everything they need to move the deal forward. Our specs were simple: - Generate a deal room for every lead - Leads should be able to sign-up with the same @FolkHQ login - A list of onboarding and educational assets (articles, videos, etc.) included - A strong bonus if connected to our @segment account to display actions to take as a “checklist” showing what prospects have done and what remains dynamically - Dynamic assignment of the right Account Executive for the deal @FolkHQ folk data, including their details (embedded @Calendly, email address) - Last Call recording + extracted summary and next steps from @GrainHQ - An embedded @intercom bubble to chat with support We built this in a few hours with @Lovable, and it has fundamentally changed how we prioritize internal tooling projects If you want to see a version, comment “Dealroom” and I’ll share it

@Shreya_0707 thanks 🙏

@LemhandezSimo Congrats on the launch!

NEWS: We’re launching folk Assistants today. Your library of assistants, living inside folk. They research companies for you. They send personalized emails based on your interactions and notes, triggered by rules you define. They summarize your past interactions and notes for every deal or contact. They identify who you need to follow up with based on your WhatsApp and emails. It feels like a new era. Assistants are ready to use and easy to configure. No complex setup. No technical knowledge required. All the heavy lifting happens in the background. folk Assistants handle the repetitive work for you, so you can close more deals. We’re on Product Hunt today and would love your support. Go here: producthunt.com/products/folk-2

The AI era isn’t a battle for attention. It’s a battle for context. And if your outreach is generic, you’re getting ignored. Inboxes are noisy and oversollicited. So in 2026, the messages that win will be personalized and tailored to stand out. The way to engineer authenticity is to be specific about your recipient’s context: - mention a post they shared recently - refer to a launch or announcement their company made - include the name of one of their colleagues (the right one) - remind them of the last discussion you had (email, WhatsApp, call) Now it’s a competitive advantage to sound more human. Context = authenticity = attention. And attention is the bottleneck right now. Doing this consistently requires context + clean data. If your email bounces, or the number you call is dead, your “personalized” message never even gets a chance. That’s why working with the right data provider matters now more than ever. At folk, we’ve built waterfall enrichment and company research into the CRM. This way, context is easier to capture in the flow of work. And that’s also why we love working with Prospeo.io. - Database of 280M+ leads & companies we can enrich from - Emails are triple-verified (SMTP checks + real send-outcome data + the BounceBan engine) and re-checked continuously, so your message reaches a real inbox - 98% deliverability on verified emails (with a decent sending setup) - ~30% pickup rate on verified mobiles (in normal B2B conditions) - 7-day refresh cycle, so your lists don’t go stale mid-sequence

@romansventures Link to podcasts episodes open.spotify.com/show/57V2XYhek… podcasts.apple.com/us/podcast/fir…

Fireside with @romansventures Chatting with Andrew is always full of insights, anecdotes and unique views on tech & product. We go through the history of folk, our vision for the future, and many more. A preview here 👇🏻

GTM teams tend to follow trends 2023 → Website visitor identification 2024 → Signals 2025 → AI SDRs At the same time, you keep hearing: “Outbound is dead” “Cold calling is dead” “SEO is dead” I don’t believe following trends or rumors creates alpha. What works, in my view: - Identify where your buyers actually spend time - Select the channels that allow you to reach them — keep the number small - Treat those channels as high-conviction bets - Commit long enough and do whatever it takes to make them work Following hype is overhyped.

Epic businesses often capture a new trend in customer behavior, and turn it into a product Uber ➡ Adoption of Mobile Zoom ➡ Rise of Remote Work Shopify ➡ Rise of Independent Online Brands and many more examples... As a founder, I frequently ask myself what are the long-term trends I believe in and I built on top of. Earlier this week, I shared the list with my investors. I extracted a few of them: 1️⃣ Touchpoints are more multi-channel than ever: email, calendar, Zoom, LinkedIn, WhatsApp, SMS, Slack, IRL, and other social platforms. These touchpoints also happen across devices: mobile and desktop. 2️⃣ The cost of outbound has never been lower, making inboxes noisy. In a noisy world, personalization is the way to be heard. 3️⃣ Personalization requires context. Capturing full context around a relationship requires connecting to all the channels above. 4️⃣ A lot of context is currently lost: it stays in our heads, in live conversations, or even in elements we see in our browser/mobile but don't capture. Who owns the context owns the truth. 5️⃣ Across our tool stack, we are getting used to AI doing more for us. It’s not just about chatbots. AI is deeply embedded: auto-updating records, auto-deduping, generating intelligent summaries, providing smart nudges, and proactive suggestions. Proactive intelligence will progressively become the default expectation for work tools.

@HarryStebbings @neo @apartovi @southpkcommons @hf0 @jasonlk @apartovi is the best!

Fund of the Year @neo w/ @apartovi "First money into Cursor, Cognition and Kalshi. I also give it a vote because 12 months ago it seemed like YC had won the accelerator race but Neo, @southpkcommons @hf0. The rebirth of the accelerator model and Neo is impressive." @jasonlk Love to hear your thoughts on this @mntruell @mansourtarek_ @davefontenot @ScottWu46

Meet the Recap Assistant Great AI features take workflows users repeat every day and make them dead simple. Getting up to speed on a deal, a person, or a company is usually tedious. You have to scroll through notes and interactions across multiple channels — emails, LinkedIn, WhatsApp, calls. Even more when several teammates are involved. With the Recap Assistant, you get a short brief that summarizes interactions and notes, so you can get up to speed in seconds. See it in action

@nicolasosharp @keithpeiris you're all welcome!

@keithpeiris It's always flattering when a new competitor has been in your product for a year... 😉 Congrats on the launch!

It's always flattering when a new competitor wants to see your naked prompts...

@bhalligan @parkerharris @Rippling I think we’ve a winner (Mark Williams in the role of Arthur Weasley, in Harry Potter)

Who should play @parkerharris in a @Rippling movie/drama?:

@villi When there are many elements, often a good search works better than any artificial structure — think Google

@villi I believe one of the hard questions is the mental model Slack relies on channels which gives an artificial feeling of structure/order. But maybe a structure by topic/conv could work better. With good search / smart tagging.

I do think there is an opportunity to build an AI-native Slack. Ping me if you are working on it.