Global

The Problem (Pain Level: 8/10) “Why is my AWS bill so high this month?” - A universal pain shared by every developer and startup using AWS. Current pain points: Dashboard fatigue: Constantly switching between AWS Console, CloudWatch, and Cost Explorer Cost black box: Hard to intuitively understand which resources consume how much Scattered health checks: Checking EC2, RDS, Lambda status individually Alert overload: Complex CloudWatch alarm setup with too much noise No CLI option: No quick way to get the full picture from the terminal Target Market Primary Target: AWS developers, DevOps engineers, startup CTOs ...

Problem (Pain Level: 8/10) “I want to use my API with Claude or Cursor, but I need to build an MCP server from scratch?” - A new barrier every API developer faces in the AI agent era. Current pain points: Manual Work: Even with OpenAPI specs, you must develop MCP servers separately Learning Curve: Time spent learning MCP protocol and SDK usage Deployment Complexity: Hosting and registry registration require separate steps Maintenance Burden: Manual sync when APIs change Fragmented Ecosystem: Tools like Specli (local CLI) and Mpak (package management) are disconnected Target Market Primary Target: API-owning companies, SaaS startups, AI agent developers ...

Problem (Pain Level: 7/10) “7 out of 10 PRs I get these days are AI-generated garbage” - The new pain for open-source maintainers. Current pain points: AI Spam Flood: Low-quality PRs mass-generated by LLMs flooding open source projects Time Waste: Maintainers missing real contributions while reviewing spam PRs Tool Installation Resistance: Security concerns about GitHub App permission requests Complex Setup: Most code review tools require excessive configuration New Contributor Identification: Hard to distinguish real beginners from AI spam accounts Target Market Primary Target: Open source project maintainers, enterprise GitHub administrators ...

The Problem (Pain Level: 7/10) “I didn’t know how many tokens my prompt was, and my API call failed” - A daily frustration for LLM developers. Current pain points: Token blindness: Can’t see real-time token count while writing prompts Unpredictable costs: Hard to estimate costs until API call is made Model confusion: GPT-4, Claude, Gemini all have different tokenizers No version control: Difficult to track prompt change history Team collaboration friction: Hard to share prompts and get feedback Target Market Primary Target: LLM app developers, AI engineers, prompt engineers ...

The Problem: Complexity of UX Testing Setup (Pain Level: 6/10) A developer shared on Reddit r/SideProject: “Solo developers - I built an app to test UX and site marketing with one click” UX testing challenges indie hackers face: Complex setup for Hotjar, FullStory, etc. A/B testing tool integration takes time Tools are overkill for small sites Free plan limits prevent sufficient data collection Interpreting results requires expert knowledge Core Pain: ...

The Problem (Pain Level: 8/10) “The AI agent sent emails, deleted files, and processed payments automatically… without any confirmation” - A new nightmare for companies adopting AI agents. Current pain points: Loss of control: AI agents executing critical operations without approval No audit trail: Can’t trace which tools an agent called and why No rollback: Can’t undo dangerous operations already executed Compliance violations: Automation without human review causes regulatory issues Trust barrier: Psychological reluctance to deploy agents in critical workflows Target Market Primary Target: Companies adopting AI agents, SaaS startups, enterprise IT teams ...

The Problem: “Stealing” Infrastructure Code from Old Projects (Pain Level: 8/10) A developer confessed on Reddit: “I got tired of stealing infrastructure code from my own old projects” Every developer relates to this: Copying Docker configs from previous projects when starting new ones Rewriting GitHub Actions workflows each time Copy-pasting Terraform/Pulumi settings between projects Debugging because copied code doesn’t match latest versions Constantly searching “how did I do this last year?” Core Pain: ...

The Problem: Analytics Dashboard Fatigue (Pain Level: 7/10) Developers and marketers face a common pain every day: Analytics dashboard fatigue. Tired of seeing the same numbers and graphs daily Depression and helplessness when KPIs drop Viewing data itself becomes stressful Even positive metrics feel meaningless On Reddit r/SaaS, one developer confessed: “I got so depressed looking at analytics dashboards that I converted it into a living garden game.” Target: Individual Developers & Small Teams - $112B Market The Gamification market is rapidly growing from $29B (2025) to $112B (2031) at CAGR 25.24%. ...

The Problem (Pain Level: 8/10) “I joined a new company and it took months to understand the million-line legacy codebase.” Large codebases are hard to grasp. Documentation is outdated, architecture is complex, and even finding “where this function is called from” takes time. Target Market - TAM $6.41B → $13.70B (2030) Developers working with legacy code Developers joining new teams Code reviewers and architects Open source contributors Software Development Tools Market is expected to grow from $6.41B (2025) to $13.70B (2030) at CAGR 16.4%. ...

The Problem (Pain Level: 7/10) “I wasted too much time creating invoices in Excel.” Freelancers and small business owners need to create invoices every month. They either use Excel templates, search for free tools, or sign up for expensive accounting software. Target Market - TAM $3.17B → $9.18B (2032) Freelancers (developers, designers, writers) Small business owners Consultants Solo entrepreneurs Invoice Processing Software Market is expected to grow from $3.17B (2024) to $9.18B (2032) at CAGR 14.2%. The SME segment holds 44.9% market share. ...