Working Smarter with AI: How Founders Can Use AI with Intention with Joan Nguyen, Co-Founder and CEO of Bumo

At Female Founder Collective's The 10th House, we know that most founders are either paralyzed by AI overwhelm or throwing tools at problems without a real strategy. In our latest interactive workshop, Joan Nguyen, Co-Founder and CEO of Bumo, cut through the noise with a game-changing perspective: treat AI as your co-founder, not just another productivity hack.

Joan's track record speaks for itself. Her team of 13 operates like 50+ people, achieving 9x growth in 10 months. After raising $10M from Offline Ventures and True Ventures and landing on the cover of Entrepreneur Magazine, she's become known for one thing: using AI with intention to do the brave work while automation handles the busy work.

The Mindset Shift That Changed Everything

Here's what most founders miss: AI isn't about adopting every trending tool or replacing your team. It's about systematic experimentation with a clear ROI framework. Joan uses ChatGPT voice mode in her car for mock investor pitches, practicing message delivery, and reasoning through complex decisions. "Prompting equals prototyping," she explains. "Done is better than perfect."

The founder advantage? Small teams can adopt faster, and tools are affordable. Joan replaced workflows that would cost $1,700 per month with a $29 tool. Even her pricier tools save thousands compared to hiring additional headcount. But the real unlock is speed. While big companies move slowly, founders can prototype, test, and pivot within hours.

Building An AI-Powered Tech Stack

Joan's approach is ruthlessly practical. Write down your top 3 recurring productivity drains, then co-design automation plans with ChatGPT. Here's how she's built Bumo's stack across different business functions:

• Scheduling and communication. Howie ($29/month) acts as Joan's AI executive assistant, emailing like a human to propose meeting times, follow up persistently, and handle reschedules with empathy. Across 200+ meetings spanning multiple time zones (including investors in Korea), vendor calls, and even coordinating her kids' playdates, she's saved 41 hours and $1,800. For quick email replies, Fyxer AI scans inbox context and drafts responses in her voice, perfect for staying responsive on mobile.
• Internal knowledge management. Joan created "Bumo Buddy," a custom GPT trained on their handbook, SOPs, brand guides, and program definitions. It deflects repetitive team questions 24/7. She also built a "CFO GPT" that uploads financial models and Stripe data to instantly answer questions about burn rate, CAC, and burn multiple. No more hunting through spreadsheets or waiting for finance team availability.
• Rapid prototyping without engineering. Using Lovable (natural-language app building), Joan built functional prototypes in 1 to 4 hours each: a tour booking manager, password-protected investor dashboard, classroom coordination tool, and a product quiz linking to Shopify. Investors told her these looked like $2M seed-stage projects. "The pre-seed era is shifting," she notes. "You can build conviction with users before involving expensive engineering resources."
• Growth and marketing at scale. Nectar Social automates comment responses in brand voice, manages inbox categorization, suppresses spam and negative comments, and provides sentiment analysis. It's costly compared to interns but cheaper than full-time headcount, and it scales infinitely. Joan also uses Apollo for personalized outbound emails, Gamma for rapid deck creation, and Templify to turn raw footage into social content.
• Choosing the right model for the job. Joan doesn't default to one AI. ChatGPT handles building and doing. Claude provides deeper analytical reasoning for investor memos with more holistic, data-cited analysis. Perplexity tackles market research with up-to-date information. Gamma designs slides and visuals. Each model has its strength, and knowing when to use which one is part of working with intention.

Making AI Stick Inside Your Team

An important note from Joan’s workshop was the importance of team integration to AI tools. One tactic Joan uses is weekly 15-20 minute team standups to share what worked and didn’t work, with clear success metrics.

She also hires for AI fluency now. Her process includes a "vibe coding" project where candidates build something using AI prototyping. She prefers people already hungry for AI because converting skeptics takes too long. Every role at Bumo is augmented by AI, but humans make final decisions.

The Security and Risk Reality Check

That said, Joan maintains healthy skepticism about AI. She avoids uploading sensitive data to tools lacking SOC 2 compliance, expects hallucinations, and builds feedback loops to catch errors. She doesn't scale core operations on fragile prototyping platforms until they're hardened.

And here's what most founders overlook: fundraising diligence now includes questions about how you use AI and protect data. Have clear policies ready before you need them.

Joan's Bottom Line

The key is treating AI tools as replaceable while staying ruthlessly focused on what actually moves the needle. Share both wins and failures widely with your team, and don't be afraid to switch tools when better options emerge. Focus on automating real pain points rather than chasing vanity metrics, and always quantify your ROI in hours and dollars saved. Most importantly, lead the adoption yourself before expecting your team to follow.

AI is no longer just for technical founders with engineering backgrounds. The barrier to entry has dropped dramatically, but that doesn't mean you should adopt every tool you see. The real competitive advantage comes from using AI strategically to free up your time for the work that actually requires human judgment and creativity.

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