📰 Dev.to · Daniel Romitelli

I rewrote the post around the real startup path in `app/yapper.py`: the dependency check, the import order, and the shared settings path in `app/co...

I built a depth segmentation path that treats shape as the signal and texture as noise. The interesting part is the sequence: depth arrives, gets v...

A deep dive into `lib/scene-compiler/text-detector.ts`, showing how I normalize fal.ai and Florence-2 OCR output, classify subtitle and watermark r...

I built the handoff so the web app never has to guess what a segment, bounding box, or measurement means. The trick is to normalize geometry before...

I added a voice-activity control to Yapper tray mode because the app was still handing Whisper recordings that contained no speech. This rewrite st...

A production assistant that can’t resume state can’t own a workflow. After watching real teams lose hours to “AI amnesia” across resets, I built a ...

Part 1 of my “How to Architect an Enterprise AI System (And Why the Engineer Still Matters)” series: why I rebuilt my email intake path around dete...

In Part 2 of my “How to Architect an Enterprise AI System (And Why the Engineer Still Matters)” series, I explain why my production extractor runs ...

I learned the hard way that “just call one enrichment API” turns into 30–40% missing fields in production—and worse, it quietly teaches your system...

I designed the Outlook Add-in so the AI never writes straight into the CRM. It streams a draft into a human-reviewed form—field by field, with conf...

In Part 5 of “How to Architect an Enterprise AI System (And Why the Engineer Still Matters)”, I explain why I treat feature flags as a safety contr...

A worker fleet that retries safely is mostly about being explicit: atomic claiming with FOR UPDATE SKIP LOCKED, leases that can go stale and be rec...

I built a sync engine against a CRM API that behaved differently in production than its documentation implied. The result is a pipeline that auto-g...

I hit the moment every enterprise AI system eventually hits: one query needed faceting and synonym maps, another needed raw vector similarity over ...

I learned the hard way that streaming a chatbot isn’t just “send tokens faster.” In my vault chatbot, I split the stream into two channels—THINKING...

I needed recruiters to search candidates live while sharing their screen on client calls—without leaking identities. The tempting answer was “build...

I watched my processing pipeline slow to a crawl the first time Redis blinked—and realized the real bug wasn’t downtime, it was my assumption that ...

In Part 1, I showed the shape of my company research chain: Firecrawl first, Bing second, and a tracer so the whole thing stays legible when the we...

I built a step-by-step extraction tracer so I can answer one question under pressure: “what exactly happened inside this run?” In this post I docum...

I replaced a ~3,500ms linear voice pipeline with a parallel, three‑phase orchestrator that targets <600ms P95 by treating “agents” like a compilati...

I built an embedding pipeline for our recruitment platform that represents each record as four typed vectors instead of one pooled blob: profile, e...

A practical pipeline for reconstructing deal timelines from messy webhook/API audit trails: normalize heterogeneous events, split them into deal-ce...

I built an Ops Intelligence Agent alongside a recruitment platform Operations Dashboard to turn a noisy real-time event stream into a small number ...

I built our Azure Maps integration as a cache-first geocoder because the first real failures weren’t “bad results” — they were wasted calls. In our...