Codez (@0xCodez)

Anthropic just dropped 5 workshops, revealing the latest capabilities of Fable 5: • 00:00 - deep look into Fable 5 • 11:22 - Fable 5 and the capability curve • 30:54 - building managed agents with Fable 5 • 44:29 - real use cases of Fable 5 by teams • 57:43 - how to deploy agents with Fable 5 These 1-hour of sessions will replace 100 articles on how to actually use Fable 5. Watch them today, then read the best practices from the sessions in the article below.

Ex-Google engineer explains how to build memory for self-improving AI agents in 12 minutes. procedural (how to act / skills) + semantic (durable facts / profile) + episodic (dated events / chat history). Memory is an important part of an agentic loop. Memory + loops + harness + evals = self-improving agent system. This is better than $500 paid courses on the internet - in under 12 minutes. Watch it today, then save the detailed guide on building agent memory from scratch

Ex-Google engineer reveals how to build AI agent loops, harnesses, LLM ops, and evals in 19 minutes. Trace → evaluate → diagnose → fix → ship → repeat. That loop is how agents self-improve over time. Agentic loops + harness + memory + evals - that’s the senior engineer stack. This is better than $500 paid courses on the same topic, explained in under 20 minutes. Watch it, then save the framework below.

Anthropic Managed Agents Lead: "At Anthropic, >90% of our engineers are building with self-improving loops. In 4-6 months, it will be 100%. my agentic loops can run for hours without spending hundreds of dollars." in this 40-minute podcast, an Anthropic team lead reveals how to build effective agents from scratch. Agent → harness → loops → memory = modern agent This one video will replace 10 paid courses on vibe-coding. Watch it today, then explore the same setup in the article below.

A senior Anthropic engineer just dropped 11-page PDF on "Loop Engineering" for agentic systems. The shift: you stop prompting the agent. You build the system that prompts it instead. Schedule → Discover → Build → Verify → Repeat Every loop runs one turn, five moves: • Discovery: it finds its own work - failing CI, open issues, recent commits - instead of being handed a list. • Handoff: each task gets an isolated git worktree so parallel agents don't collide. • Verification: a second agent, told to assume the code is broken, reviews the first. The "thing that can say no." • Persistence: results get written to disk, never left in a context window that gets flushed. • Scheduling: an automation wakes it on a timer. That's what makes it a loop. The key insight: an agent grading its own work always praises it. This 11-page PDF changed how I'm building agentic systems today. Read it now, then explore the article below.

Сreator of Claude Code: "Since Opus 4.5, i uninstalled my IDE. I don't edit a single line of code by hand. 100% my code is written by Claude." in 1-hour Y-Combinator podcast, Boris Cherny breaks down his daily Claude Code setup. Claude + loops + dynamic workflow Worth more than a $500 vibe-coding course.

Andrej Karpathy (co-founder of OpenAI): "My agent will talk to your agent. Everything is going to be rewritten - agent-native sensors, actuators, infrastructure." In 30 minutes, he explained what the agent-first world actually looks like and how you can prepare for it. Most people are still using AI like it's 2023. Watch the interview, then read the article below.