Think Bigger: How Small Teams Win with ChatGPT
OpenAI 9 months ago 26
A practical guide explains how small teams use ChatGPT for tasks like analyzing data, creating marketing materials, managing budgets, running meetings, and making decisions.
334 summarised stories about ChatGPT, each linking back to the original source. Browse all topics →
OpenAI 9 months ago 26
A practical guide explains how small teams use ChatGPT for tasks like analyzing data, creating marketing materials, managing budgets, running meetings, and making decisions.
OpenAI 9 months ago 11
OpenAI scaled PostgreSQL to handle the database demands of supporting 800 million ChatGPT users through replicas, caching, rate limiting, and workload isolation techniques. The system processes millions of queries per second across their infrastructure. This approach allows OpenAI to maintain database performance without replacing PostgreSQL entirely, demonstrating how traditional relational databases can support massive-scale applications.
The daily briefing
TLDRocket reads all relevant sources, removes duplicate coverage, and summarises the day in two minutes. Follow companies and topics for alerts, or get the briefing in Slack. Free, no spam, unsubscribe anytime.
AI’s dominant theme today is accountability at scale: as agents get more autonomous, companies are doubling down on verification, sandboxing, and evidence—because “it worked once” is no longer good enough. Anthropic reports its merged code changes jumped from about 2,500 per day in May to over 30,000 by September as it rolled out agentic “software factory” workflows, but the growth depends on building a fast, high-fidelity verification “sensor” so agents don’t outrun what tests can actually validate. In parallel, Anthropic open-sourced its @anthropic-ai/sandbox-runtime, an OS-level sandbox (no containers) that reportedly cut internal Claude Code permission prompts by 84%—a practical nod to how real agent deployments are constrained by risk controls, not ambition.
Read the full briefing →