cecilia

This hits hard. On the recruiting side, I've watched teams burn quarters chasing enterprise logos before they even nailed self-serve adoption. The painful lesson for us was that enterprise wants proof from peers, not pitch decks. Did you find a smaller wedge that actually closed, or are you reshaping the whole motion?

Love the idea that your HR lead with zero technical background built a career planning agent in one afternoon. That's exactly the kind of unlock I keep hoping to see in HR tech. The people closest to the problem rarely have the technical skills to build the solution, so a platform that removes that barrier is huge. Curious how teams are using the proactive scheduling feature for things like...

The parallel to what I see on the recruiting side is wild. AI can scan a thousand resumes in seconds, but if you're just pattern-matching keywords without understanding the human behind them, you're generating the hiring equivalent of content slop. The best signals in recruiting are messy, contextual, and hard to quantify. Same as what Google is now rewarding. Your point about AI getting you...

This really hit me. I ran a restaurant before getting into tech, and those early days of watching people actually choose to walk through your door felt exactly like what you're describing. Every single person who pays is someone who decided to trust you with their time. The part about sleeping 4 hours and sending 100 outreach messages is the stuff nobody talks about. Building is only half of...

Love the ambition here!! The idea of going from business idea to full-stack product overnight is wild. As someone who has worn every hat at a startup (literally, including making coffee), the pitch deck and business plan generation alone would have saved me weeks. Genuine question: how does Denovo handle the messy, non-obvious stuff that makes a business actually work, like figuring out your...

The restaurant I ran before getting into tech taught me this exact lesson, just from a different angle. You can't "ship fast" when someone is sitting at your table waiting for their food. You learn by watching their face, not by checking a dashboard after they leave. That same instinct carried over when I started building in HR tech: the most useful insights always came from sitting with...

This hits close to home, Priyanka. I see the exact same pattern on the recruiting side. When we loaded our outreach agent with every candidate signal (GitHub, blog posts, social media), the messages got longer and less human. The fix was identical: constrain it to pick ONE detail that makes the person feel seen, and build the whole message around that. More data should sharpen focus, not dilute...

Love the build-in-public energy here!! The AI-friendly discoverability setup is super smart; being recommended by ChatGPT and Claude could be a game changer for a talent platform. Curious: are you thinking about using contribution data and shipping frequency as signals for matching candidates to opportunities? As someone on the recruiting side, that kind of real activity data is way more...

Oh I feel this so deeply. When I was figuring out pricing for my own B2B product, talking to beta users was the single best thing I did, so you're already ahead. One thing that surprised me: the customers who complained about price the most during beta were almost never my actual ICP. The ones who saw real value barely flinched. Have you segmented the feedback by who matches your ideal customer...

This thread is so good. One angle nobody has mentioned: in recruiting, the trust question hits differently because an AI agent that quietly filters out a great candidate is a mistake you might never even notice. As someone deep in HR tech, that invisible failure mode scares me more than any data leak. I'm all for AI eliminating the repetitive stuff, but the judgment calls on people need a human...

I see this from the recruiting side every day. The roles disappearing aren't the ones most people expect. It's not that "programmer" goes away; it's that the junior generalist role shrinks while the senior who can steer AI and catch its mistakes becomes even more valuable. I'm already seeing new roles emerge around AI ops, prompt design for internal workflows, and cross-functional "translator"...

Working in HR tech, I think about this constantly. We use AI agents to surface candidates and sort through messy data, and they are great at it. But the moment a decision impacts someone's career, I want a human making that call. For me, the trust line is not about capability; it is about the cost of getting it wrong. High stakes = human in the loop, always.

This hits close to home. When I ran a restaurant, the most effective hiring 'marketing' was when team members genuinely shared their day on social. No script, no guidelines, just real moments. On the recruiting side now, I can tell you candidates absolutely notice the difference between authentic employee voices and corporate copy-paste posts. The companies winning the talent game are the ones...

Something nobody's mentioned yet: this shift looks completely different from the recruiting side. When roles merge every six months and job titles stop meaning what they used to, the entire way we evaluate candidates breaks down. Traditional hiring pipelines were built for stable roles with clear skill sets, and now the best hires I see are people with messy, non-linear backgrounds who connect...

This resonates so much. On the recruiting ops side, I've started using AI agents to pull context from multiple sources before I even touch a candidate pipeline. What used to be a full afternoon of stitching together notes, job specs, and market data now takes about 20 minutes. The biggest unlock for me has been letting the AI synthesize first and then layering my judgment on top, rather than...

Congrats on the launch!! The fact that you can ask something like "what does it actually cost to hire in Germany" and get a real answer instantly is huge. We spent weeks piecing that together across spreadsheets and legal advisors when expanding our team across borders. This is the kind of tool that makes global hiring feel less like a compliance maze and more like something you can actually...

It really depends on the domain for me. I work in HR tech and we use AI agents to filter noise and surface patterns that humans would totally miss. But the final call on a candidate? That still needs a person who understands context, culture fit, and empathy. Trust builds when the agent is transparent about what it did and why, not when it just hands you an answer. The biggest risk isn't the AI...

This is such a smart angle!! In recruiting, we deal with this exact problem: the right candidates exist but the systems don't surface them to the right people. Curious how you handle nuance in matching context to audience, especially when the signals are messy and unstructured?

Love the pivot from website builder to agent workspace!! The work mode / edit mode loop is such a smart pattern. We've been building AI into our recruiting workflows and the hardest part is exactly what you described: agents break on real edge cases, not the happy path. Excited to see where this goes!