Founder Log #9 – Prompt Engineering and Real Progress

- 3 minutes read - 521 words

🧠 Weekly Overview

This week was about deep work, learning, and getting unblocked.

After several frustrating weeks of slow or stalled progress, I finally broke through. Most of the week went into building the recipe ingestion pipeline and understanding Langchain4j’s structured output mode. The learning curve was steeper than expected, and that caused some stress. I felt like I wasn’t delivering — but the truth is, learning was the delivery.

Every prompt tuned, every bug traced, and every validation rule added was a brick laid for the long-term system. I’ve reached the point where the ingestion pipeline is finally moving. Real YAML recipes are flowing into the app, and I even got the UI preview working.

Mentally, I also got back on track. I fixed my sleep schedule, re-established good habits, and finally feel momentum again.

🗓️ Daily Execution Summary

Monday – May 19

  • Finalized and published last week’s Founder Log (#8)
  • Tested new recipe backend + UI integration
  • Implemented image resizing + watermark script in the evening

Tuesday – May 20

  • Finished responsive image component in frontend
  • UI now dynamically picks optimal image variant and loads lazily
  • Feels super fast — noticeable UX win

Wednesday – May 21

  • Started recipe ingestion pipeline implementation (step 1)
  • Folder watching + AI preprocessing integration done
  • Noted that social media drift hurts morning focus — made plan to fix that

Thursday – May 22

  • Keep on working on ingestion pipeline: AI to structured recipe JSON with prompt tuning
  • Added contextual logging and improved prompt versioning
  • Clarified new rules for social media usage to protect morning focus

Friday – May 23

  • Debugged concurrency bug in ingestion flow
  • Built and tested structured recipe object + metadata extractor
  • Evening: AI schema debugging in Langchain4j

Saturday – May 24

  • Finished prompt tuning + validation for structured output
  • First YAML recipes saved end-to-end
  • Deepened Langchain4j knowledge by reading source code

Sunday – May 25

  • Implemented UI preview for new YAML recipes
  • Refactored mapping logic to support multilingual recipes
  • Final tuning of dev preview mode and frontend mapping

🏆 Wins of the Week

  • ✅ Prepared scripts that convert base image into multiple sizes and formats and add watermarks
  • ✅ Built responsive image component that loads optimal size on the UI to reduce bandwidth and improve UX
  • ✅ Reached full ingestion pipeline from URL → YAML → UI preview
  • ✅ Mastered Langchain4j structured output tuning and schema control
  • ✅ Fixed concurrency bugs and added validation layers
  • ✅ Created responsive image component with lazy loading
  • ✅ Got back into flow-state morning deep work (no phone, no socials)

✍️ Lessons & Reflections

  • Estimation is fine — as long as you accept it might be 1000% off.
  • Learning is legitimate progress. Just not always visible right away.
  • Tuning prompts is a craft. Logging inputs/outputs helps immensely.
  • Flow state is real and repeatable with the right habits:
    • No phone
    • No social in the morning
    • One clear goal set the night before

🎯 Plan for the next week

  • Finish recipe ingestion pipeline and ingest 50+ recipes
  • Start meal planning functionality:
    • Support different schedules (3/4 meals, packed lunches, etc.)
    • Per-person meal schemas
    • Manual drag/drop or add-to-plan interface