@Gustavo Odone Yeah that makes a lot of sense I’ve been seeing the same thing. Getting attention isn’t really the issue anymore, it’s what happens after that where most people drop the ball. A lot of the time it’s not even a lead problem, it’s just no system to manage and follow up properly, so everything kind of fades out. On my end, it’s pretty similar once there’s a simple structure in place for replies and follow-ups, conversions usually improve without needing more traffic. Out of curiosity, have you been deep into digital marketing for a while now, or did that come more naturally as you started working with founders?

@Gustavo Odone Haha yeah exactly “pretty content doesn’t pay the bills” is something a lot of people learn the hard way. For me, I didn’t really start deep in tech. I was more on the side of trying to understand why people weren’t getting results or staying consistent, and that’s what led me into marketing and then automation. It just clicked that most people don’t have a traffic problem they have a system problem. Once you fix that, everything feels way more controlled. I like that you’ve got both sides though creative + backend is a strong combo. Curious, when you’re working with clients now, do you lean more into the strategy side or are you still heavily involved in the creative direction too?

@Nick Coppola This is a really sharp take especially the shift from “tools” to “workflows.” Most people are still stuck in that first phase, jumping between models and features, but what you’re describing is where the real leverage is: building something that compounds as the underlying tech improves. What stood out to me is how clearly you’ve defined your lane. When the inputs are consistent (like CRE tax strategy), the outputs become predictable and that’s exactly what makes a workflow valuable instead of just interesting. It also reframes AI from being a “capability” to being more like a multiplier on structured thinking. If the thinking is clear, the output scales. If not, it just creates faster noise. I’m curious in your workflow right now, which part actually took the most iteration to get right: the inputs you feed in, or how you structure the output for brokers/investors?

You can definitely automate your Instagram, but the best way is to break it into 3 simple parts: For content → use AI tools to generate captions, post ideas, and even carousel text For posting → use Meta Business Suite (free) or tools like Later to schedule everything in advance For engagement → tools like Many Chat can help automate replies to DMs and comments That setup keeps things efficient without risking your account, which is really important now. Most people try to fully automate everything, but the accounts that grow fastest still keep a bit of manual touch especially in conversations. What kind of content are you planning to post? That’ll help narrow down the exact tools and setup you should use.

@Frank van Bokhorst This is seriously thoughtful you’re not just tweaking UI, you’re shaping how people judge truth. That’s a different level. The “invitations to verify” idea stands out a lot. That flips uncertainty from a weakness into something actionable, which most products completely miss. And what you said about tone is spot on a confident wrong answer is way more damaging than a cautious right-ish one. Feels like you’re catching a really important nuance early. Now I’m curious have you heard much about MRR models or even how platforms like Shopify approached building trust early on? Not saying it’s the same space, but there might be some interesting parallels in how they balanced simplicity with reliability. Would be interesting to hear your take on that

@Frank van Bokhorst That’s such a sharp observation especially the point about sequencing complexity instead of hiding it. Most platforms either overwhelm professionals immediately or oversimplify to the point where trust disappears. What Shopify and Stripe understood early is that confidence compounds when users feel in control at every stage, even before they fully understand the system. What stood out to me in what you said is the idea that lawyers don’t want to “adopt AI,” they want to stay in flow while the product quietly proves itself. That framing feels incredibly important because it shifts the platform from being perceived as software to becoming infrastructure almost invisible until its absence would slow them down. And your point on trust being embedded into defaults, tone, and error states is probably the most overlooked advantage in AI products right now. A lot of founders talk about accuracy, but very few talk about emotional predictability. The feeling that the platform behaves the way a professional expects under pressure. That’s where long-term retention actually comes from. Out of curiosity, when you think about “depth on demand” for legal specifically, where do you think the boundary is between automation and professional control? Because it feels like the companies that win this category will be the ones that know exactly when to step forward and when to deliberately stay out of the way.