Hey Everyone, Just curious about what do you do exactly after getting a client or a free trial, how do you smoothly onboard them? I’m now pitching 7 days free trial but I also think there should be an easy way to onboard these clients quickly and have them see the value. Interested in your approaches!

I've been teaching at this private school for a little bit over 4 months. In that time, I've had a lot of interesting takeaways that I thought to share, and I hope that if you're working with anyone born after 2000, you'll walk away with at least one new perspective. 1) 80% of classrooms are GPT-dependent and hate it. I've heard this to be true about public schools too, but with private schools where kids are believed to have an extra "edge", they're just prompting their way through oblivion and hating it. They know it's not their own thoughts. Management frowns upon any AI use, teachers are scared of inaccuracy, and students lean into it to offload the difficulty of thinking through problems. I posted about this revelation on Reddit, expressing that I was hoping to offer some middle-ground solution. The aversion and pitchforks were palpable, I had DMs, comments, all walks of teachers saying that I embody "the problem" with "tech bros coming into a space they know nothing about and trying to make a sale" I painted the post with "free" but I guess it still smelled like sales. I felt odd, rejected, I wondered if this was just a Reddit echo chamber. Went to a bunch of private teaching forums, attempted to walk down the same path of bridging free AI tools to help teachers and students navigate better. Felt incredibly uphill, I realized any mission in this direction of AI education would have to be tackled from the ground-up. I fundamentally believe, purely due to systemic bias, that we are under-equipping future generations and numbing them with media machines. Edu-informational content is meant to serve this gap, take the ones that are motivated and give them a path to trailblaze. Waiting for curriculum approval or middle management to greenlight doesn't make sense to me. I started building with this group in mind, the next generation of AI specialists. I've also found that this generation motivates and inspires a lot of the open source efforts, and if you have them on your team, you have a novel perspective on architecture, capability, and possibility. Regardless of age, people want to help people.

https://www.tomsguide.com/ai/chatgpt/chatgpt-now-offers-a-year-in-review-7-prompts-to-turn-it-into-a-wrapped This is slowly rolling out to users, found out I'm a top 1% user (which feels like fugazi but sure) What'd you get? 🤓

There's a number of repos like this. Now with Claude Code, Codex, Antigravity, cto.new , Cursor, and all these other Agentic IDE's on the market, I imagine the utility of these repos will only go up with time https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main You could create a full blown SaaS (with costs) out of any of these multi-agent builds, especially since it's open source and you only get charged for API + cloud use I've run a few Perplexity reports on these agents, they're remarkably competitive. There's people out there collecting arbitrage on these purely out of market ignorance. Heavy hitters all around A few highlights: (Junior) Real Estate Agent Team - Scrapes for properties, evaluates them based on scoring criteria, and creates a report for you. When I renew my real estate license in April, I'll be coming back to this AI Services Agency Team - 5 agents that would work in any services-based business. CEO (strategy) CTO (architecture mapping) Product manager (strategy + architecture, product market fit) Developer agent (implementation guide) Client success agent (GTM strategist) Built on top of CrewAI, IBM and NVIDIA's architecture of choice. They got over $18M in funding for this, and you could import it for free RAG-as-a-Service - Imagine you could point a laser and that laser just generates a memory lake for LLMs to feed from. That's the promise behind this one. There's over a hundred companies that have this as their core offering, and they EAT with a handful of a clients

I know this community is mainly about getting your first $ with AI and automation, but what's fascinating is the business model comes with an ocean of opportunity. Usually after your first handful of deals, you develop enough trust that the client opens the door for you to start pitching ideas for what would support their business. Automation and GTM (Go-To-Market) strategy carries a lot of affinity. Faster deals means revenue velocity. More data reporting automated means better decision making. It's a win-win, the thing is most businesses can't even conceptualize how they'd use your services. After you build and fix a few projects, the road gets wide. Caveat is most decision makers behind GTM strategy are often behind C-Suite, and the bigger the company, the harder it is to get automation systems in front of the right person, and the more craft is required to make it stupid simple. As an owner/operator yourself, you apply your consultative lens, crunch data, ideating on the theory of constraints to help drive revenue through their business. I came across this resource from LinkedIn sharing over 51 pitch decks that got funding. Was curious to hear from the minds of people making money with AI on their experience working with clients that either got funding recently or are in the midst of making GTM decisions. What's been your experience pitching ideas that drive revenue to your clients? Feel free to share successes and blunders https://www.figma.com/design/qT3c9M7TIs7Jo8mUXTpLMR/40---21-pitch-decks?node-id=98-2&p=f It also doesn't hurt to study what's working, especially when it comes to where money moves Happy holidays 🤓