New to this library, not necessarily new to the world.
Lex Fridman interviews Anthropic's Dario Amodei on scaling, computer use, and safety; Amanda Askell on prompting and constitutional AI; and Chris Olah on how neural networks compute. The episode combines technical explanations with Anthropic leaders' first-party accounts and dated forecasts; it is not an independent evaluation of Claude's capabilities or safety.
Lex Fridman · Source dated 11 Nov 2024
Tobi Lütke describes Shopify's shared Slack agent, agent-assisted coding, and his use of multiple agents to prepare decision material. He argues that people remain responsible for choices and warns that cheap generation can shift lazy work from too little output to unreviewed excess. His adoption figures, workflow outcomes, and forecasts are speaker-reported, not independently verified.
The Knowledge Project Podcast · Source dated 15 Sept 2026
Tobi Lütke explains how he retains failed tasks as model evaluations, supplies enough context to make work plausibly solvable, and codifies non-platitudinous product principles. Shopify uses AI critiques to find discussion points and refine those principles rather than as an automated approval gate. The practices and outcomes are Lütke's account.
Acquired · Source dated 18 Sept 2025
Tobi Lütke describes Shopify's AI mandate, why a token-usage leaderboard produced bad incentives, and how agent-summarized customer feedback supports smaller teams. He argues that experienced engineers still steer coding agents through problem understanding. Shopify's adoption, cost, and workflow outcomes are speaker-reported, not independently measured.
Uncapped with Jack Altman · Source dated 20 May 2026
Marc Brooker discusses testable specifications, learning from production incidents, enforceable agent policies, and shared team context. He forecasts increasing automation of implementation while emphasizing the human work of defining good outcomes. A practitioner interview with AWS product claims, not an independent evaluation; based on English YouTube captions.
AI Native Dev · Source dated 16 Sept 2026
From The Pragmatic Engineer — selected conversations
The Pragmatic Engineer · Source dated 17 Sept 2026
Philipp Schmid compares a Python tool loop, an agent framework, and a hosted agent on the same GitHub PR-review task. In the hosted version, the runtime handles the loop and the agent uses the GitHub CLI instead of custom wrappers; developers supply instructions and skills and retain responsibility for evaluations and outcomes. A Google DeepMind product demonstration, not an independent reliability or security assessment.
AI Engineer · Source dated 14 Sept 2026
Ryan Carson describes prioritizing concurrent Devin threads, using Watchdog to triage customer-account problems, and requiring video approval before his land PR playbook merges. He and the host discuss verification, design handoffs, and why customer learning matters more than code volume. Based on English auto-generated captions; workflow outcomes are speaker-reported, not independently verified. Carson discloses receiving monthly Devin credits from Cognition.
How I AI · Source dated 24 Aug 2026
Lada Kesseler describes refining agent output through focused write-read-revise loops, teaching TDD through reusable skills, and separating agent-facing tests from human-readable behavior checks. A practitioner interview covering review, exploratory prototypes, and her reservations about software factories; improvements are speaker-reported, not benchmark results.
AI Native Dev · Source dated 25 Aug 2026
Syntax discusses Pi Radius as a managed model gateway, remote agent sessions with Herder, and the trade-off between personal-agent access and prompt-injection risk. A concrete validation anecdote shows an agent accepting malformed metadata instead of rejecting it. This summary selects coding-agent material from a broader weekly roundup; product descriptions and workflow outcomes are host-reported, based on English auto-generated captions.
Syntax · Source dated 14 Sept 2026
An editorial selection from Syntax's channel uploads, combining the existing Zed/Delta interview with five videos on code review, remote coding agents, long-term memory, and MCP. The summaries distinguish demonstrations, practitioner reports, proposals, and product claims from independently measured outcomes. This is not an official Syntax course or a summary of the full uploads playlist.
Syntax
Source dated 13 Dec 2025
Source dated 8 Jul 2026
Source dated 16 Jul 2025
Source dated 1 Jul 2025
Source dated 16 Mar 2026
Andrew Qu explains how Vercel evolved D0 from a large prompt and a chain of agents into a sandbox-based data agent with company knowledge and reusable query skills, then packaged the approach in Eve. A transcript-backed practitioner account; evaluation gains and organizational outcomes are speaker-reported.
AI Engineer · Source dated 14 Sept 2026
A combined episode guide to Salvatore Sanfilippo and Enkk's Italian-language conversations across both channels: coding-model workflows, local inference, AI safety, interpretability, text watermarking, AGI labels, and evaluation through useful work. The guide records summary coverage because the hosts' separate YouTube playlists are incomplete. Opinions, proposals, and project anecdotes are not controlled evaluation results.
Salvatore Sanfilippo & Enkk
Source dated 11 Jul 2026
Source dated 23 Jul 2026
Source dated 2 Aug 2026
Source dated 24 Aug 2026