Data pipeline pricing: why bills spike and how to forecast
Data pipeline pricing comes in four flavors – active rows, event volume, credits and compute – and each one has a specific way of surprising you. This post explains how each model actually charges, why bills spike after backfills and schema changes, and how to forecast your own bill before you sign anything. Almost every […]
AI writeback: safe write access for AI agents in 5 steps
AI writeback is the ability of an AI agent to update your business systems – create an invoice, move a deal, send a reminder – instead of only reading from them. This post covers when to allow it, the five requirements for doing it safely, and the operations that should stay read-only no matter what […]
Context layer: why AI agents get 1 in 4 answers right
A context layer stores what your data means – metric definitions, relationships between systems, business rules – so an AI agent stops guessing. This post explains why agents fail without one, what Microsoft, Snowflake and Airbyte just shipped, and what to do if you don’t have a data platform team. In June, Snowflake published a […]
Agentic Data Pipelines: All you need to know
Agentic data pipelines use AI agents to autonomously ingest, transform, validate, and orchestrate data flows – replacing brittle, rule-based ETL with adaptive, self-healing workflows. This guide covers how they work, where adoption stands today, what they can and can’t do, and what changes for data teams. Data engineering teams spend a disproportionate amount of time […]
How to Build AI Agents
Building AI agents is no longer a futuristic concept – 79% of organizations are already using AI in at least one business function, and 93% of IT leaders plan to implement AI agents within two years. The challenge: 86% of enterprises need significant tech stack upgrades before they can deploy AI agents effectively. 42% of […]