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Engineering & product playbooks
Hands-on playbooks, decision frameworks, and case studies from the team building AI-native products at CodeNicely.
Backfill Embeddings for 1M Rows Without Killing Postgres
Backfilling embeddings into a live Postgres table with a million rows isn't an ETL job — it's a queue problem. Here's a lease-based pattern that survives crashes, respects rate limits, and never holds a lock longer than one UPDATE.
Your AI Pilot Succeeded. That's Why It Never Shipped.
A pilot that hits every demo metric but never reaches production isn't an engineering failure. It's a scoping failure — and the cleaner the pilot looked, the worse the problem usually is.
Questions to Ask Before Hiring an AI Logistics Dev Partner
Vetting an AI logistics development partner after an internal build stalled? These are the 18 questions that separate real freight-platform builders from generic app studios pitching an ML demo.
GST Reconciliation Failures: A Dev-Side Cheatsheet
A dense reference for engineers whose GST reconciliation passes unit tests but bleeds ITC mismatch tickets in production. Covers GSTR-2B refresh cadence, RCM, QRMP, and GSTIN state transitions.
Kafka vs. SQS: Pick the Right Queue for Your AI Pipeline
Choosing between Kafka and SQS for an AI pipeline usually comes down to one question most benchmarks skip: do you need the message log to be a replayable asset for retraining and audit? Here's the honest tradeoff.
How to Hire an AI Development Partner in Australia
A practical buyer's guide for Australian COOs evaluating offshore AI development partners — the compliance questions, delivery signals, and time-zone realities that separate a studio that has shipped under Australian conditions from one that hasn't.
Build vs. Buy Your AI Matching Engine: A Decision Framework
Most build-vs-buy frameworks for AI matching engines treat this as a cost decision. It isn't. It's a data-density question — and the answer usually surprises the people asking it.
5 Mistakes Teams Make When Automating Pharmacy Operations
Most pharmacy automation projects fail not because the software is bad, but because it was configured against an idealized workflow no pharmacist on the floor actually follows. Here are the five mistakes we see most often, and how to recover from each.
Your Automation ROI Is Real. Your Headcount Math Is Wrong.
Hours saved on a slide are not dollars removed from a P&L. Here's the honest math behind automation ROI — and why most business cases quietly overpromise the board.
Stream LLM Responses to a React Frontend Without Melting
Your ChatGPT-style feature stalls for 6 seconds before rendering a single token. Here is how to stream LLM responses to React properly — with auth, aborts, and partial JSON that does not double-render on flaky networks.
How to Cut Over a Live Database Schema Without Downtime
A step-by-step playbook for renaming columns, dropping tables, and restructuring core models on a live production database — without a maintenance window. Written for CTOs whose deployment pipeline isn't clean enough to ship app and DB changes atomically.
What Is Idempotency? Stop Charging Customers Twice
A double-charge after a mobile timeout is almost always a retry bug, not a payment gateway bug. Here's how idempotency keys work, and why the fix lives in your client — not your server.