What I Learned Launching an AI SaaS (in 30 days)

The speaker shares their experience launching two AI SaaS products, aiming to build 20 in hopes that one will succeed, inspired by a fellow entrepreneur's advice to "ship more." Their first product launch, in October 2024, was met with several critical mistakes stemming from a lack of application development experience. These included maintaining separate codebases for development and production, poor code organization, and a less-than-ideal deployment process.

For their second SaaS product, significant improvements were made by addressing these issues. They unified the codebase, adopted a more structured project architecture, and streamlined deployment by integrating directly with GitHub. Furthermore, the speaker discovered powerful ways to leverage AI for coding, moving beyond simple prompt-and-edit to a more integrated workflow that fosters better understanding of code and reduces technical debt.

Beyond technical execution, the second build highlighted the crucial importance of go-to-market strategy. Recognizing their deficiency in sales and marketing, the speaker dedicated a substantial six weeks to customer acquisition, outlining a six-step checklist for developing an effective launch campaign. This process emphasizes understanding the target customer's needs and problems over focusing on the product itself.

• Launched a second AI SaaS product in 30 days, aiming to build 20 to find a successful one.
• Identified three major mistakes from the first SaaS build: separate codebases for dev/prod, poor code organization, and inefficient deployment.
• Learned to code 10x faster with AI, specifically using Claude Code's "plan" mode to understand proposed changes.
• Realized the critical importance of go-to-market strategy, dedicating 6 weeks to customer acquisition.
• Developed a 6-step checklist for launch campaigns focusing on customer needs and problems.

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First SaaS Build Mistakes [00:42]

• Mistake 1: Having two separate code bases for development and production, causing complexity in deployment.
  • This issue was resolved in the second SaaS by using a local .env file to automatically switch to dev mode.
• Mistake 2: Poor organization of the codebase, with most code living in just three Python files.
  • This became unmanageable after adding features like authentication, a user database, Stripe integration, and multiple web pages.
  • The speaker now spends more time architecting before coding.
• Mistake 3: Not deploying the app directly from GitHub, leading to friction in the shipping process.
  • Using GitHub for deployment streamlined initial setup and feature additions for the second SaaS.

These initial missteps in building the first SaaS product highlight critical areas for improvement in development workflow and deployment efficiency. The speaker learned the hard way about the importance of a unified codebase, structured architecture, and seamless integration with deployment tools.

"By far the biggest mistake I made was having two separate code bases for development and production."

Second SaaS Build Lessons [02:36]

• Lesson 1: Learning to code 10 times faster with AI.
  • Previously used AI by prompting and then editing, which sometimes led to hours of debugging.
  • Switched to using Claude Code, which lives in the terminal and overwrites changes.
  • Key benefit of Claude Code: "plan" mode, which outlines proposed changes without executing them.
  • "Plan" mode helps avoid generating code that needs rewriting and keeps the developer informed about codebase functionality, reducing technical debt.
  • Claude Code's interface also promoted the habit of making frequent Git commits, implementing one feature at a time.
• Lesson 2: Learning the importance of go-to-market.
  • Sales and marketing were identified as the speaker's biggest deficits due to a technical background.
  • Original plan was 3 weeks building, 1 week selling, which proved insufficient.
  • Dedicated the next 6 weeks to customer acquisition.
  • Developed a 6-step checklist for launch campaigns:
    1. Start with the avatar (who the product is for and where they are).
    2. Define the dream outcome (what the avatar needs or wants).
    3. Map out the customer's journey to achieve the dream outcome.
    4. Identify pain points and problems along the customer journey.
    5. Craft messaging (keywords, phrases, taglines) that speak to the avatar's pains.
    6. Write a launch summary (campaign title, length, goal, channels, volume).
  • Mindset shift: Forget about the app during the checklist process; focus on customer needs and problems.

The second product's development and launch planning revealed that efficient coding with AI and a robust go-to-market strategy are paramount for success. The adoption of advanced AI coding tools and a customer-centric marketing approach were key takeaways for accelerating progress and increasing the likelihood of market adoption.

"The truth is, people don't care about me or my product. They care about themselves and their problems."