AI
Artificial intelligence, machine learning, and everything LLM
#2483: Generating Synthetic Data Without PII Risk
How to generate realistic synthetic voice notes and calendar data with zero PII exposure risk.
#2482: When AI Chatbots Leak Your PDFs via Public S3 Buckets
A user uploaded a sensitive PDF to an AI chatbot. The chatbot stored it in a public S3 bucket with zero authentication.
#2478: MCP File Handling: Why Your Base64 Upload Breaks at 4MB
MCP has no standard file input. Base64 breaks at 4MB, presigned URLs need whitelisting, and MinIO workarounds aren't standardized.
#2472: AI Gateways: Where Guardrails Actually Break
PII detection at the gateway layer can block legitimate invoices. Here's how guardrails actually work and where they fail.
#2471: Creative Briefs for AI Agents: What Agencies Already Know
How agency best practices for briefing creatives map directly onto getting reliable output from AI agents like Claude Design.
#2470: Small Model vs Big Model for Prompt Enhancement
When should you fine-tune a tiny model for prompt enhancement instead of prompting a large one? The answer depends on latency, precision, and domain.
#2469: Embedding Model Deprecation: RAG's Silent Killer
When OpenAI retires an embedding model, your RAG pipeline breaks silently. Here’s how to fix it.
#2468: Tracking AI API Costs Across Providers
How to track AI spend across Open Router, Replicate, and more — without a unified dashboard.
#2467: OpenAI vs Anthropic: Tiered API Billing Deep Dive
How OpenAI and Anthropic structure API tiers, rate limits, and why your billing history matters more than you think.
#2466: The Hidden Trap of Embedding Model Lock-In
What happens when your vector database works great — until your embedding model gets deprecated and your vectors become useless.
#2465: JSON-L vs Parquet: When Each Format Wins
How far can JSON-L scale before it breaks? And why does Parquet dominate for millions of rows?
#2464: Batch APIs: The 50% Discount You're Probably Misusing
Batch inference APIs offer 50% off — but only for the right workloads. Here's when they actually make sense.
#2461: How Claude Code's Conversation Compaction Actually Works
The three-tier system, what survives, what dies, and why you shouldn't rely on auto-compact.
#2460: Building a Personal AI Shopping Agent for Israel
The real challenges of building an AI agent that navigates Hebrew e-commerce, geographic shipping quirks, and whitelist curation.
#2459: Drizzle vs Prisma: Which ORM Wins for AI-Native Backends?
Comparing Drizzle and Prisma for AI-native backends, MCP servers, and the future of agent-centric development.
#2458: Can Graph Databases Go Mainstream?
Graph databases are powerful but niche. Will they ever power mainstream CRMs and ERPs?
#2456: Choosing Between AI Cloud Providers
A practical guide to choosing between Modal, RunPod, Nebius, and Baseten for AI workloads.
#2453: Desire-Based Hiring: Fixing the Job Market
What if job matching was built on desire, not desperation? How one signal outperforms 100 applications.
#2449: Budgeting Without the Stick: Tools for Organization, Not Discipline
Can budgeting software feel like intelligence instead of judgment? A look at tools for people who hate being told what to do with their money.
#2445: How to Pick a Music Distributor Without Getting Trapped
Why can't you upload music directly to Spotify? And how to pick a distributor without losing your catalog.