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9:59ENOpen Interpreter: A 2023 Local Code-Execution WalkthroughMatthew Berman · Forward FutureMatthew Berman installs Open Interpreter, analyzes local files with GPT-4 and tries a local Code Llama setup, with mixed results.
4:35ENRunning WizardCoder on a Cloud GPU: A 2023 RunPod WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates downloading a quantized 13B coding model into a hosted text-generation interface, then explains how to stop the pod and avoid ongoing charges.
14:59ENAI News in September 2023: Tesla, Code Llama, Drone Racing and CopyrightMatthew Berman · Forward FutureMatthew Berman surveys a week of AI announcements, from Tesla's driving demonstration and ChatGPT Enterprise to model releases, generative media and a copyright inquiry.
6:11ENRunning WizardCoder Locally with Text Generation WebUIMatthew Berman · Forward FutureMatthew Berman walks through a 2023 setup for a quantized Code Llama-based coding model, from the Python environment to a simple test prompt.
10:20ENPhind Code Llama 34B vs GPT-4: A 2023 Python Coding TestMatthew Berman · Forward FutureMatthew Berman compares a quantized Phind fine-tune with GPT-4 on games, short functions and refactoring, with mixed results.
1:39:53ENUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer IntelligenceModeration: Nathan LabenzMichele Catasta, Replit's new VP of AI, lays out a generate-execute-learn loop he will not call AGI, a 2x-to-1000x productivity ladder, and a keystroke-level data advantage.
1:45:46ENReplit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring BotsModeration: Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.
11:07ENInstalling Llama 2 13B Chat and Testing Its ResponsesMatthew Berman · Forward FutureMatthew Berman demonstrates a 2023 local setup and tests a 13-billion-parameter chat model on coding, writing, arithmetic and reasoning. His small set of prompts illustrates both useful outputs and mistakes.
12:20ENTesting UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.
7:05ENAider’s Early Coding Assistant: Snake and an Existing Rails ProjectMatthew Berman · Forward FutureMatthew Berman demonstrates the terminal tool’s 2023 workflow, from generating and iterating on a game to proposing a dependency change in a repository.
6:26ENInstalling and Trying GPT-Engineer: A 2023 Snake Game WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates the early project-generation workflow, from a Conda environment and prompt to clarification questions and generated Python files.
7:37ENSmol Developer: Generating a Small Python Project From a PromptMatthew Berman · Forward FutureMatthew Berman walks through a 2023 project generator, from a simple Ruby example to a multi-file ChatGPT API program.
59:38ENRichard Eisenberg on Dependent Types, OCaml, and AI-Assisted ProgrammingYaron Minsky, Richard Eisenberg · Jane StreetHow type systems can express correctness and performance, and why precise, readable specifications still matter when AI writes code.
41:40ENEvery 10 Milliseconds Cost Copilot 1% of CompletionsModeration: Sarah Guo, Elad GilGitHub Copilot's chief architect, Alex Graveley, walks through how a leftover code model with a sub-10% test pass rate became a product developers would not quit — and what he is building next at Minion AI.
58:08ENAmjad Masad on Replit, Company Culture and AI-Assisted SoftwareGast: Amjad Masad · Moderation: Harry StebbingsThe Replit founder discusses hiring, developer productivity and the opportunities and risks he saw in AI in 2023.
32:48ENA Hundred Million to Train, a Penny to InferModeration: Nathan LabenzIn a February 2023 roundtable, two founders argue on mic over whether AGI ends humanity — and who actually captures the value if it does not.
2:51:33ENThe Self Is a GPT Prompt: Wojciech Zaremba on Consciousness, Codex, and Fermi's SilenceGast: Wojciech Zaremba · Moderation: Lex FridmanOpenAI co-founder Wojciech Zaremba tells Lex Fridman he thinks we might be alone in the universe — and that GPT-3, Codex, and a one-handed robot already hint at how intelligence is built.
1:25:13ENCodex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a TeammateModeration: Lenny RachitskyCodex product lead Alexander Embiricos explains the 20x growth, why every useful agent may need to write code, and why human review speed is the real bottleneck.
1:39:51ENAfter the Inflection Point: Simon Willison on Agentic Engineering, Dark Factories and the Coming AI Challenger DisasterModeration: Lenny RachitskyDjango co-creator Simon Willison explains what changed in November 2025, how he works with coding agents, and why prompt injection remains the field's biggest unsolved risk.
1:33:50ENEvals Are the New PRDs: Inside Anthropic's Research Product TeamModeration: Lenny RachitskyDianne Penn, Anthropic's head of product for research and Labs, explains how the company found its identity, how her team turns user feedback into evals, and why human judgment still matters.
1:11:06ENReplit's Amjad Masad on Building Your Own Model, Latency, and the Next Billion Software CreatorsModeration: Jacob EffronThe Replit founder explains why AI should be native to the product, why he trained a small in-house model, and why he thinks software engineering is about to split in two.
1:53:14ENWorth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute CapModeration: Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.
1:04:25ENInside GitHub's Copilot Bet: Agents, Open Source, and Why the Developer Job EnduresModeration: Jacob EffronGitHub CEO Thomas explains how Copilot went from a research bet to 1.3 million developers, and what agents, fine-tuning and a multi-model world mean for the next five years of software.
1:32:32ENDevin's Scott Wu on Building an AI Software Engineer and Turning Coders into ArchitectsGast: Scott Wu · Moderation: Lenny RachitskyThe Cognition co-founder explains how his 15-person team uses fleets of Devins to build Devin, what the product can and can't do, and why he expects more engineers, not fewer.
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