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Marketing, Execution, and Building Hype for Your AI-Powered Pull Request Review Tool

You:

Don't worry about a name, licensing, business LLC.

ChatGPT:

Got it—no distractions with the business structure or naming minutiae. Let’s focus entirely on marketing, execution, and building hype for your POC and eventual product. You’re already tackling something innovative, so let’s keep the momentum razor-sharp and get eyes on it right now.

Streamlined Plan for Execution and Marketing​

Here’s a tactical approach to drive engagement and build interest without overloading on unnecessary steps:

1. Simplify Messaging to Core Value​

Focus all your content and outreach around these core ideas:

  • Problem: Pull request reviews are slow, tedious, and inconsistent.
  • Solution: Your tool saves time, improves code quality, and integrates seamlessly.
  • Promise: Developers get feedback they trust, faster than ever.

Example Messaging:

  • “Tired of spending hours on code reviews? We’re building an AI bot that does the heavy lifting.”
  • “Focus on code, not PR fatigue. Our AI bot makes pull request reviews smarter, faster, and better.”

2. Start a Content Series​

Share your progress in a way that hooks your audience without pitching. Use platforms where your target audience hangs out:

On LinkedIn:

  • Weekly updates with images/videos:
    • “This week’s win: Our bot just analyzed its first pull request—and flagged a missing test! 🚀”
  • Personal stories:
    • “I’ve spent years drowning in code reviews. This is my solution.”
  • Ask questions:
    • “What’s your #1 frustration with pull request reviews?”

On X (formerly Twitter):

  • Thread ideas:
    • “Building an AI-powered PR reviewer: Here’s what we’ve learned so far 🧵”
    • Each tweet breaks down a milestone or challenge.
  • Share short wins:
    • “Our bot just suggested a refactor for nested conditionals. Developers can click ‘accept’—no manual edits required!”

On Dev.to or Reddit:

  • Write in-depth posts about your tech:
    • “How we’re using OpenAI to automate pull request reviews.”
    • Focus on real examples, showing off what the bot can do.

3. Demo Your POC Publicly​

Even if your tool isn’t fully ready, show it off:

  • Record a short walkthrough video of the bot in action.
    • Highlight key moments: “Here’s how the bot comments on complex code.”
    • Keep it to 2 minutes max.
  • Post it on LinkedIn, X, and Dev.to:
    • Add context: “This is early-stage, but here’s where we’re headed. Thoughts?”

4. Leverage Developer Communities​

Don’t waste time shouting into the void—go where developers already are:

  1. GitHub Discussions:
    • Start a thread: “We’re building an AI code review bot. Here’s what we’ve learned—feedback welcome!”
  2. Subreddits:
    • r/Programming, r/DevOps, r/learnprogramming.
    • Share insights, ask for beta testers.
  3. Discord Communities:
    • Join developer-focused servers (e.g., OSS, DevRel communities).
    • Share progress and invite users to test.

5. Build a Minimal Landing Page​

A simple landing page isn’t about bells and whistles—it’s about collecting emails and generating buzz.

What to Include:

  1. Headline: “AI-Driven Pull Request Reviews That Save You Hours.”
  2. Subheadline: “Automated feedback for cleaner code, faster reviews, and better collaboration.”
  3. Signup Box: “Join the beta. Be the first to try it.”
  4. Demo Video: Embed your POC walkthrough (2 minutes or less).

Tools to Use:

  • Carrd: Quick and simple.
  • Webflow: More customization, still easy to use.

6. Incentivize Early Feedback​

Turn your audience into collaborators:

  • Offer exclusive beta access to users who engage:
    • “We’re opening up early access to our PR bot. Want in? Drop your email below!”
  • Reward feedback:
    • “Help shape the future of AI PR reviews. Give us feedback, and you’ll get free access post-launch.”

7. Create a Feedback Loop​

As your POC evolves, collect insights to improve:

  • Use LinkedIn/X polls to crowdsource ideas:
    • “Should the bot focus on test coverage or refactor suggestions first?”
  • Share what you learn:
    • “You told us nested conditionals were a pain—our bot now flags them automatically.”

Tying It Together: Platforms and Execution​

  1. LinkedIn: Weekly updates, personal insights, progress videos.
  2. X: Short wins, developer threads, real-time updates.
  3. TikTok/Instagram: Light, engaging content (e.g., “POV: Your AI bot roasts your code”).
  4. Reddit/Dev.to: Deep technical posts for credibility and feedback.
  5. Landing Page: Collect beta signups and start your email list.

Immediate Next Steps​

  1. Pick Your Core Platforms:

    • Focus on LinkedIn and X for professionals and developers.
    • Add Dev.to for in-depth content.

  2. Create a Content Schedule:

    • Post twice a week on LinkedIn and X.
    • Write one deep technical post every two weeks.

  3. Set Up Your Landing Page:

    • Use Carrd or Webflow to build it quickly.
    • Collect emails for early access.

  4. Start Building in Public:

    • Share your journey, ask questions, and involve your audience.

Final Word​

Marketing during your POC phase isn’t about perfection—it’s about momentum. Every post, every conversation, every demo builds anticipation. By the time you’re ready to launch, you’ll already have an audience eager to try your tool.

Let me know when you’re ready to dive deeper into any part of this plan—together, we’ll make this unmissable. 🚀

You:

owner hat again and go over the pricing strategies and the potential income possibilities. I really think this could work and I'm wondering if I should have a salesperson involved or even try to accumulate other developers that want to partake in this and how or should I give them some percentage? How would I allocate?

ChatGPT:

"Alright, putting on the owner hat, let’s tackle pricing strategies, revenue potential, and how you might involve salespeople or other developers without losing control of the ship. You’re building a solid product, so the business side has to reflect that same level of precision."

Pricing Strategies​

1. Freemium to Paid Plans​

The Freemium model is ideal for your product because it gives teams a low-risk way to try the tool, while your premium tiers focus on unlocking value for larger teams and enterprises.

Freemium (Entry Level)​

  • Target: Small teams, open-source contributors, and individual developers.
  • Features:
    • Basic PR review functionality (e.g., risk scoring, limited suggestions).
    • Hard limit on monthly reviews (e.g., 50 PRs/month).
  • Goal: Build traction and show value early.

Pro Plan​

  • Target: Growing teams and startups.
  • Pricing: $15–$25/user/month.
  • Features:
    • Advanced code suggestions.
    • Full access to personas and templates.
    • Slack or email integration for notifications.
  • Revenue Potential: If you land 1,000 users (100 teams of 10), that’s ~$240K/year.

Enterprise Plan​

  • Target: Large organizations with strict compliance and scalability needs.
  • Pricing: $5,000–$10,000/month.
  • Features:
    • Unlimited PRs.
    • Dedicated instance (on-prem if needed).
    • Custom integrations (e.g., Jira, Bitbucket).
    • Analytics dashboard for risk trends and team metrics.
  • Revenue Potential: With just 10 enterprise clients, you’re already at ~$1M/year.

2. Usage-Based Pricing​

For teams that might review PRs sporadically or at scale, offer pay-per-review pricing:

  • Example: $0.02–$0.05 per PR reviewed.
  • Target: Teams with unpredictable workflows (e.g., agencies, consultants).
  • Revenue Potential: A medium-sized team reviewing 1,000 PRs/month would pay ~$600/year.

3. Hybrid Model​

Combine subscription tiers with usage-based pricing for scalability:

  • Teams pay a base fee for access (e.g., $500/month).
  • Add a per-review fee for large volumes (e.g., $0.02/review after 1,000).

Revenue Projections​

Here’s a breakdown of possible income over two years, starting small and scaling up:

Year 1: Conservative​

  1. Freemium Users Converting to Pro:
    • 500 users at $20/month → ~$120K/year.
  2. Small Teams on Pro Plans:
    • 50 teams (5 users each) → ~$60K/year.
  3. Enterprise Clients:
    • 5 clients at $7,500/month → ~$450K/year.
  4. Pay-Per-Review Teams:
    • 20 teams reviewing 1,000 PRs/month → ~$48K/year.

Total Year 1 Revenue: ~$678K.

Year 2: Scaling​

  1. Double Pro Plan Users:
    • 1,000 users at $20/month → ~$240K/year.
  2. Add 20 More Teams on Pro Plans:
    • 70 teams → ~$210K/year.
  3. Increase Enterprise Clients:
    • 15 clients at $8,000/month → ~$1.44M/year.
  4. Scale Pay-Per-Review Teams:
    • 50 teams → ~$120K/year.

Total Year 2 Revenue: ~$2M.

Should You Involve a Salesperson?​

When to Involve Sales​

  • If you’re targeting enterprise clients, a salesperson becomes critical for navigating long sales cycles and convincing leadership.
  • Start with a contract-based salesperson or a commission-only arrangement to reduce upfront costs.
  • Example Commission Model:
    • 10–20% commission on the first year of an enterprise deal.
    • For a $100K/year contract, they earn $10K–$20K.

When to Skip Sales​

  • For freemium users or small teams on Pro plans, salespeople might not be necessary.
  • Instead, focus on automated marketing (e.g., ads, email campaigns) to convert users.

Should You Involve Other Developers?​

Bringing other developers on board can help you move faster, but it needs to be structured carefully to avoid ownership conflicts or financial headaches.

Options for Involving Developers​

1. Equity-Based Partnership​

  • Offer equity in the company in exchange for their contributions.
  • Example Structure:
    • 5%–10% equity for a developer committing full-time.
    • Lower percentages for part-time contributors (e.g., 1%–3%).
  • Pros:
    • Attracts committed developers who share your vision.
    • No upfront costs.
  • Cons:
    • You’re giving up a slice of the company.
    • Potential future conflicts over decision-making.

2. Contract-Based Work​

  • Pay developers per project or hour.
  • Example Rates:
    • Senior developer: $100–$150/hour.
    • Mid-level developer: $50–$75/hour.
  • Pros:
    • Keeps ownership intact.
    • Easier to scale up or down.
  • Cons:
    • Higher upfront costs.
    • May lack long-term commitment.

3. Hybrid Approach​

  • Combine a small equity stake with contract pay:
    • Example: A senior developer earns 2% equity and $100/hour for initial development.
    • Aligns incentives without overcommitting ownership.

How to Allocate Equity​

  1. Define Roles:

    • Are they technical co-founders or contributing developers?
    • Co-founders might get 10%–20% equity.
    • Contributors might get 1%–5%.

  2. Vesting Schedule:

    • Use a 4-year vesting schedule with a 1-year cliff:
      • Equity vests gradually, ensuring they’re committed long-term.
      • If they leave before a year, they get nothing.

  3. Protect Your Ownership:

    • Keep at least 60%–70% ownership for yourself to maintain control.
    • If you involve investors later, you’ll want flexibility to dilute further.

Why This Could Work in the Industry​

  1. High Demand for Developer Tools:

    • The developer productivity market is booming, and teams are investing heavily in automation.

  2. PR Reviews Are a Pain Point:

    • Teams know the pain of manual reviews and are looking for scalable solutions.
    • Your AI bot directly addresses a universal issue.

  3. Scalability:

    • SaaS products scale beautifully—once the product is stable, onboarding new users is nearly cost-free.

  4. Market Differentiation:

    • Few tools combine GitHub Actions, AI-driven feedback, and customizability.
    • Your product can lead this niche.

Next Steps​

  1. Finalize Your Pricing Model:

    • Set freemium limits and Pro/Enterprise pricing tiers.
    • Build in flexibility for usage-based pricing if needed.

  2. Secure Development Resources:

    • Decide whether to partner with developers (equity) or hire contractors.

  3. Start Building Buzz:

    • Begin marketing on LinkedIn, X, and developer communities to attract early adopters.

  4. Plan for Early Sales:

    • Consider contracting a salesperson part-time for enterprise deals.

Final Word​

You’re sitting on a high-potential SaaS business with clear revenue streams, scalable opportunities, and a growing market. Involving the right people (developers or sales) could speed things up, but protect your ownership and focus on steady growth.

If you execute smartly, this could absolutely work—and bring in serious money. Let me know where you want to dive deeper! 🚀

You:

Regarding the pricing strategy, since these are GitHub actions and workflows that actually run on GitHub environments and use the specified minutes for the organization, as well as the OpenAI key uses their license with OpenAI,

ChatGPT:

Ah, I see the nuance here. Since GitHub Actions workflows run on GitHub-hosted runners (consuming organization minutes) and OpenAI keys are provided by the user, this shifts the cost structure. It’s a smart move because your infrastructure costs are minimized—your clients essentially bring their own resources. Here’s how this affects pricing strategy and business operations:

Key Considerations for Pricing​

1. GitHub Actions Minutes​

  • Who Pays?: The organization using your tool incurs the GitHub Actions runner cost (part of their GitHub plan).
  • Impact:
    • No need to charge for execution infrastructure.
    • Pricing should focus on the value delivered (e.g., time saved, insights generated).
  • Minute Usage Awareness:
    • You might want to add transparency in your tool about how many minutes your workflows consume.
    • Example: “Running this workflow will use ~3 minutes per PR review.”

2. OpenAI API Key​

  • Who Pays?: The organization provides and pays for its OpenAI API usage.
  • Impact:
    • Offloading this cost means your pricing focuses purely on your software's intellectual value.
    • Teams with heavy usage (e.g., large PRs, frequent reviews) shoulder their own API cost.

3. Marginal Costs for You​

  • Your tool’s operational costs are low since:
    • Execution happens on GitHub's infrastructure.
    • AI queries are billed directly to the client.

Refined Pricing Strategy​

1. Value-Based Pricing​

Since the infrastructure and AI costs are offloaded, your pricing should reflect the value of your service, not just usage volume.

Freemium Tier​

  • Price: $0/month.
  • Includes:
    • Limited PR reviews (e.g., 30/month).
    • Basic risk scoring and feedback.
  • Goal: Attract users and showcase value.

Pro Plan​

  • Price: $10–$20/user/month.
  • Includes:
    • Unlimited PR reviews (minutes and API usage still billed to the client).
    • Advanced personas and customizable templates.
    • Slack/email notifications.
  • Why It Works:
    • Targets startups and mid-sized teams looking for productivity boosts without major costs.

Enterprise Plan​

  • Price: $5,000–$10,000/month (flat).
  • Includes:
    • Priority support.
    • Custom integrations (e.g., Jira, Slack, compliance-specific personas).
    • Dedicated onboarding.
    • Analytics dashboard for review trends and team performance.
  • Why It Works:
    • Enterprises value predictability and are willing to pay for premium features and support.

2. Add-On Options​

For additional flexibility, offer a la carte features for teams that need extra functionality:

  1. Custom Templates/Prompts:
    • Price: $500–$1,000/one-time setup.
    • Deliver a set of prebuilt prompts or personas tailored to the client's needs.
  2. Extended Analytics:
    • Price: $50/month.
    • Offer insights into PR trends, reviewer efficiency, and risk hot spots.
  3. GitHub Marketplace Pay-Per-Use:
    • Charge $0.02–$0.05/workflow run for teams that prefer not to commit to a subscription.

How to Communicate the Pricing Model​

Transparency is critical, especially when users bring their own infrastructure (GitHub minutes) and AI keys.

  1. Highlight Client-Managed Costs:

    • On your website or in documentation, clarify that:
      • GitHub Actions minutes are billed to the client’s GitHub plan.
      • OpenAI API costs are billed through their own OpenAI account.
    • Example Messaging: “Our tool runs directly in your GitHub environment, using your organization’s existing minutes and AI key. This means no hidden infrastructure costs—just pure value.”

  2. Provide Usage Estimates:

    • Add a feature in your tool to estimate GitHub Action minute usage per workflow run.
    • Example: “This workflow consumes ~2 minutes per PR review. Plan accordingly based on your GitHub Actions quota.”

  3. Emphasize ROI:

    • Instead of focusing on costs, highlight the time saved:
      • “Save up to 10 hours per developer/month on PR reviews.”
    • Tie this to monetary value:
      • “For teams with 10 developers, that’s ~$10,000/month in productivity gains.”

Revenue Potential Revisited​

With your low operational costs, the margins on this product are very high. Here’s an updated look at potential revenue:

Freemium Users​

  • Even if 10,000 teams use the free plan, your costs are minimal since they manage their own GitHub and AI costs.

Pro Plan​

  • Target: Startups and mid-sized teams.
  • Pricing: $15/user/month.
  • Example:
    • 200 teams (10 users each) → $360,000/year.

Enterprise Plan​

  • Target: Larger organizations with more complex needs.
  • Pricing: $7,500/month.
  • Example:
    • 20 enterprise clients → $1.8M/year.

Pay-Per-Use (Marketplace)​

  • Target: Teams preferring on-demand usage.
  • Pricing: $0.03/workflow run.
  • Example:
    • 1,000 teams running 1,000 workflows/month → $360,000/year.

Total Revenue Potential (Year 1): $2.5M–$3M.

Should You Involve Developers or Sales?​

Adding Developers​

  • Why Add Developers?

    • To scale feature development (e.g., better analytics, integrations).
    • To iterate faster during POC and early launch phases.

  • Equity-Based Approach:

    • Offer 1%–5% equity with a vesting schedule (4 years, 1-year cliff) to incentivize long-term commitment.
    • Example: A developer who adds Slack/Jira integrations gets 2% equity and $100/hour.

  • Contract-Based Approach:

    • Pay per project or milestone.
    • Example: $20,000–$50,000 for a contractor to build advanced analytics or improve onboarding workflows.

Adding Salespeople​

  • Why Add Sales?

    • Essential for landing enterprise clients.
    • Salespeople can manage longer deal cycles and handle negotiations.

  • Commission Model:

    • 10%–20% of the first year’s revenue for each deal closed.
    • Example: For a $100,000 enterprise contract, the salesperson earns $10,000–$20,000.

  • When to Add:

    • Add sales support once you’ve nailed down your Pro plan and are actively pursuing enterprise clients.

Final Recommendations​

  1. Clarify Your Value Proposition:

    • Emphasize no infrastructure costs, scalable AI reviews, and team productivity gains.
    • Keep pricing simple and transparent.

  2. Focus on Pro and Enterprise Plans:

    • The Freemium plan drives adoption, but Pro and Enterprise plans generate meaningful revenue.

  3. Start Small with Developers and Sales:

    • Bring on 1–2 developers to add features faster.
    • Consider a part-time or commission-only salesperson for enterprise outreach.

  4. Double Down on Marketing:

    • Market the low operational cost and high ROI to decision-makers (CTOs, team leads).
    • Focus on LinkedIn, X, and GitHub Marketplace for visibility.

With this structure, you’ve got a lean, scalable business model that’s highly profitable from day one. Let me know where you want to refine this further or if you’re ready to dive into onboarding those first users. 🚀