This guide walks you through every step of creating an AI agent from scratch. It highlights tools and techniques that can shrink your build time from two weeks to a single day.

OpenAI’s data productivity team built Kepler, an AI agent that understands their data platform context and writes iterative SQL to answer complex data questions. It handles table discovery, query refinement, follow-up prompts and even visualizations, cutting analysis time and reducing errors.

Anthropic has turned Claude into a persistent Slack bot that watches channels, answers questions, suggests tasks and can trigger actions without prompting. It acts like an “agentic” AI coworker, raising questions about privacy, control and user consent in workplace chats.

GitHub built Qubot, an internal Copilot-powered analytics agent that lets employees query their data warehouse in plain English via Slack, VS Code, or the CLI. It pulls federated context from raw, conformed, and curated data layers, then runs queries on Kusto or Trino to deliver SQL-backed insights within seconds. A continuous evaluation framework and community contributions to the context layer keep responses accurate and fast.

Ponytail is an always-on ruleset and plugin for AI coding agents (Claude, Codex, Gemini, Copilot, etc.) that enforces a step-by-step “ladder” to include only necessary code. Benchmarks show 80–94% less code, 3–6× faster responses, and 42–75% lower cost by preferring built-ins and one-liner solutions before adding dependencies.

SkillSpector scans AI agent skills for vulnerabilities, malicious patterns, and CVEs before installation. It combines fast static checks with optional LLM analysis, covers 64 patterns across 16 categories, and outputs risk scores and detailed reports.

Ponytail is a plugin and ruleset for AI coding agents that enforces a six-step minimal-code ladder—skip unnecessary code, prefer stdlib or native features, then one-liners—to produce only what each task needs. Benchmarks on Claude models show 80–94% less code, 3–6× faster runs, and 42–75% lower cost. Installation covers Claude Code, Codex, OpenCode, Gemini/Antigravity CLI, Copilot, ClawHub, and more.

Sakana AI released Sakana Marlin, an autonomous research assistant that takes a topic and runs up to eight hours to produce summary slides and a detailed strategy report. It uses long-horizon reasoning and multi-model control to form hypotheses, gather data, and verify findings without human input. After a closed beta with about 300 professionals, it’s now available via pay-per-use and tiered subscription plans.

Two workshops demonstrate hands-on uses of Anthropic’s Claude model. In one, Andrej Karpathy breaks down his 14-minute tutorial on mastering Claude, claiming it takes about 10,000 hours to learn. In the other, Amazon quants show how they built a full AI agent in 25 minutes with just 44 lines of code, now open-sourced.