This content originally appeared on DEV Community and was authored by charlie s'
Hello developers! I'm Charlie. I've independently developed three AI tools: TransMonkey, Imgkits, and TeachAny. I'll be sharing my architecture, automation stack, and the real-world challenges I encountered while using these products.
1.Architecture for a solo developer Frontend
- I use Next.js, React, and Tailwind.
- I choose them for SEO, reuse, and fast themes. I use MDX for docs and demos.
Backend
- I run serverless functions for burst tasks like translate, generate, and export.
- I run a job queue and workers for long tasks like OCR, media, and large translations.
- I store assets and previews in object storage behind a CDN.
Data and documents
- I use Postgres for jobs, quotas, and audit logs.
- I parse document layout into blocks, lines, and tables to keep structure.
- I use small embeddings only when retrieval helps, like glossaries and terms.
AI and ML pipelines
- I do OCR. I build a layout graph. I translate by segment to keep order.
- I use LLMs for text. I use vision models with masks and seeds for control.
- I add guardrails after generation. I map font fallback. I apply RTL/LTR rules. I add safety filters.
Observability and reliability
- I send logs and traces to one place. I add per-job metrics.
- I track outcome metrics that users feel: table cell parity, subtitle drift, brand color delta, plan readability score.
- I use feature flags and staged rollouts.
Security and privacy
- I keep data for a short time by default.
- I provide delete endpoints. I collect minimal PII. I show clear controls.
2.Automation stack that helps me ship fast DevOps
- I use CI/CD with PR previews.
- I run tests for layout parity, subtitle timing, color deltas, and rubric checks.
- I use Infra as Code for repeat setups.
- I schedule cleanup jobs for previews and temp keys.
Workflow automation
- I orchestrate with queues. I retry with backoff. I send failed jobs to a dead-letter queue.
- I show early previews and honest progress bars.
- I send webhooks when tasks finish.
3.Problems I met that match my products, and how I fixed them
Let me first briefly introduce my three artificial intelligence tool websites.:“
TransMonkey: AI translation for 130+ languages that preserves original layout across PDFs, Word, Excel, images, video, and audio.
Imgkits: AI creative studio that turns prompts into high‑quality images/videos with strong control and built‑in editing.
TeachAny: AI teaching assistant that adapts materials to classroom context and diverse student needs.”
A.TransMonkey: translation with layout intact and real-world files Real problems:
- Many PDFs have mixed fonts. Some fonts miss glyphs after translation. Text shows as blocks.
- Many tables break after translation. Cell counts change. Merged cells split. Borders shift.
- Many files mix RTL and LTR. RTL in tables flips order. Numbers wrap wrong.
- Long SRT/VTT files drift after translation. Line length changes, so timings slip.
- Scans are low quality. Skew and noise cause wrong reading order.
Fixes:
- I run OCR with skew fix and denoise. I detect blocks, lines, and tables. I keep reading order.
- I build a layout graph for pages, headers, paragraphs, tables, and captions.
- I translate by region. I keep tokens per cell. I preserve cell count.
- I map font fallback per script. I test glyph coverage before render. I pick safe fonts automatically.
- I apply RTL/LTR rules per region. I keep number direction and punctuation rules.
- I retime subtitles after translation. I cap line length. I keep gaps. I check overlap and drift.
- I run post checks: page parity, table cell parity, caption timing, and font coverage.
B. Imgkits: on-brand image and video generation with stable framing
Real problems:
- Prompts change framing. Faces move. Key objects crop.
- Brand colors drift across batches. One variant is too dark. Another is too bright.
- Small text becomes blurry at social sizes. Upscaling breaks strokes.
- Background removal leaves halos on hair and glass.
- Users want 3–6 good options fast, not 100 random images.
Fixes:
- I use masks to lock composition. I set control points for subject and horizon lines.
- I fix seed and guidance per brand preset. I vary only one parameter per batch.
- I measure color delta to brand palette. I reject out-of-range shots. I adjust with LUTs.
- I render at target size or exact scale factors. I use vector text or SDF text layers when possible.
- I use matting models with hair detail. I add edge-aware feather and color decontaminate.
- I produce 3–6 controlled variants per job. I label differences. I let users pick fast.
C. TeachAny: lesson plans for mixed-ability classes that are practical
Real problems:
- One plan does not fit all levels. A single reading level loses many students.
- Many outputs are too long. Teachers have 40 minutes and one device per group.
- Some activities are not checkable. Teachers need quick checks for understanding.
- Accommodations are vague. Teachers need concrete supports they can use now.
- Standards mapping is weak. Plans miss the target objective.
Fixes:
- I collect standards and clear objectives first. I lock time and device limits.
- I define learner levels. I add supports like sentence frames, visuals, and adjustable text.
- I generate multi-level tasks for the same goal. I include an exit ticket or quick check.
- I keep outputs short. I add steps, timings, and materials. I make it editable.
- I add teacher notes with why this helps. I show alignment to the standard.
Conclusion
I independently developed three AI tool websites. I resolved issues such as missing layouts, brand drift, and one-size-fits-all approaches. I used a simple stack, clear checks, and robust security measures. Now, the products I deliver are trustworthy. I will continue to leverage user feedback to improve these products.
This content originally appeared on DEV Community and was authored by charlie s'
charlie s' | Sciencx (2025-11-03T04:13:15+00:00) I independently developed three AI tool websites: Architecture, Automation Stack, and Painful Lessons Learned.. Retrieved from https://www.scien.cx/2025/11/03/i-independently-developed-three-ai-tool-websites-architecture-automation-stack-and-painful-lessons-learned-2/
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