Optimize prompts to cut DALL-E token costs by 60% automatically
Solo indie hackers building AI image tools lose 80% of revenue to skyrocketing OpenAI API costs, blocking profitability.
PromptPenny rewrites user prompts before sending to OpenAI, shortening them while preserving image quality via AI-trained compression. It A/B tests optimizations in your app and reports back savings. Solo devs plug it into their image tools to boost margins without changing UX.
Solo indie hackers developing AI image generation tools
AI-powered prompt compression trained specifically on DALL-E outputs for image gens
supportive
Auto-shortens prompts by 50-70% tokens
Compares original vs optimized image quality
Dashboard showing token reduction per request
Integrate as middleware for seamless use
CLIP-based similarity scoring for optimizations
User-defined optimization preferences
Optimize multiple prompts at once
Revert to original if quality drops
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| stripe_id | text | Yes |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| original_prompt | text | No |
| optimized_prompt | text | No |
| token_savings | int | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| similarity_score | float | No |
| approved | bool | No |
Relationships:
/api/optimizeOptimize a single prompt
/api/proxy/imageProxy with auto-optimization
/api/statsGet savings and test results
/api/testsRun A/B test
No A/B testing
50k tokens/mo
Unlimited
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 80 | 4% | $80 | $960 |
| Month 6 | 500 | 8% | $1,000 | $12,000 |
60% token savings via smart AI rewriting – perfect for your image SaaS.
Share Twitter thread 'How I cut DALL-E costs 60% – free access for first 3 indie hackers building image tools'. Follow up with DMs to engaged replies, validate with their prompts.
Logging
No optimization
Image-specific compression + quality checks
Dataset of optimized DALL-E prompts improves model over time with user feedback
Longer prompts in new DALL-E 3 driving up costs for complex indie tools
Optimization reduces quality
Mandatory A/B + fallback
Low adoption of proxies
Demo with user prompts
High OpenAI meta-costs
Use cheap GPT-mini
Success: 60% compressible
Success: Avg 50% savings
Success: 20% referral growth
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