with-agents

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New to this library, not necessarily new to the world.

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Collection additions CloudSecurity

Getting Started with Cloud Security Command Center

Five 2019 walkthroughs show how vulnerability scans, anomalous activity, sensitive-data findings, and configuration checks lead to investigation and remediation. A finding signals something to investigate, not proof of a breach.

Google Cloud Tech

2 summaries on this page
Collection additions Cloud

Serverless Expeditions — selected guide

Serverless design and operations through concrete examples: choosing a runtime, ordering events, managing relational state, undoing failed workflows, protecting secrets, and deploying changes safely. The selection also includes two AI-agent examples covering tools and database access.

Google Cloud Tech

14 summaries on this page

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video Coding

Think Harder: How I Prompt — Thorsten Ball

In this Laracon US 2026 talk, Thorsten Ball explains prompting as an information-design problem: show coding agents where authoritative context lives, externalize hidden constraints, use screenshots and diagnostic reports as compact evidence, and move recurring instructions into the codebase so shorter prompts can still work.

Laracon US · Source dated 30 Jul 2026

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video AI

Sam Altman on Building OpenAI & Betting on the Impossible

David Senra asks Sam Altman how AI adoption, context, product strategy, and research management shape OpenAI. Altman points to Tobi Lütke’s hands-on agent use, admits that habits and product gaps slow adoption, argues for iterative deployment and accident reporting, and proposes context-rich persistent agents. His capability, safety, and market claims are first-party reports or forecasts, and the privacy implications of broad context access go unaddressed.

David Senra · Source dated 23 Aug 2026

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video Coding

Pi Coding Agent - Deep Dive

0xSero gives a live source-level tour of Pi: provider normalization, the streamed agent loop, built-in tools, extensions, session storage, and the SDK. He then shows how those pieces can support local models, delegated agents, and long-running goal loops. The cache-hit, latency, cost, and benchmark comparisons are demonstrations without enough linked configuration or methodology to count as controlled evaluations.

0xSero · Source dated 21 Aug 2026

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video Coding

Coding Agents Don't Scale Themselves. Neither Do Your Teams.

Patrick Debois argues that coding-agent advantage will come less from individual prompting than from organizations improving the systems around agents. He recommends shifting retros from code failures to system failures, separating agent-ready work from decisions that need conversation, centralizing reusable context and tools behind a few paved roads, and tracking human interventions. His dark-factory forecast, hiring model, and metrics are practitioner guidance, not validated research.

AI Engineer · Source dated 22 Aug 2026

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