필터 결과
24개정렬
18:34EN
Matthew Berman· 2026년 7월 7일Model Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.
0:52ENMatthew Berman· 2026년 6월 24일A 12-Day Codex Run to Build an Excel CloneMatthew Berman · Forward FutureMatthew Berman describes giving Codex a brief goal and manually stopping it after more than 12 days, then demonstrates the resulting spreadsheet.
16:11ENMatthew Berman· 2026년 6월 19일Seven AI Coding Agent Loops and When to Use ThemMatthew Berman · Forward FutureMatthew Berman explains how triggers, goals and repeatable checks can turn coding tasks into agent workflows, with examples for performance, documentation and product quality.
2:34:17ENMatthew Berman· 2026년 5월 28일Matthew Berman Tests Claude Opus 4.8 and Dynamic Workflows LiveMatthew Berman · Forward FutureA launch-day walkthrough compares Anthropic’s reported benchmarks with informal coding experiments and a multi-agent website redesign.
2:27:51ENMatthew Berman· 2026년 4월 17일Testing Claude Opus 4.7 and Building for an Agent-First InternetMatthew Berman · Forward FutureMatthew Berman tests Claude Design, examines early Opus 4.7 reactions and debugs an experimental agent chat live.
18:07ENMatthew Berman· 2026년 4월 16일Claude Opus 4.7: Benchmarks, Cyber Safeguards and Open QuestionsMatthew Berman · Forward FutureMatthew Berman compares Anthropic’s April 2026 Opus release with the limited Mythos Preview and examines its system card.
27:15ENMatthew Berman· 2026년 3월 31일Meta-Harness: Searching for Better AI Agent InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a paper on using a coding agent to iteratively improve model harnesses and discusses its experimental limits.
11:59ENMatthew Berman· 2026년 3월 11일How Claude Identified a Benchmark and Retrieved Its AnswersMatthew Berman · Forward FutureMatthew Berman examines Anthropic's report on BrowseComp contamination, evaluation-aware behavior, and the difficulty of keeping web-based tests reliable.
40:00ENMatthew Berman· 2026년 2월 24일How Matthew Berman Built an OpenClaw Workflow for His TeamMatthew Berman · Forward FutureA tour of sponsorship triage, CRM, meeting notes, security, scheduling, memory and backup after a month of heavy use.
0:58ENMatthew Berman· 2026년 2월 12일Matthew Berman’s OpenClaw Setup for Personal and Business WorkMatthew Berman · Forward FutureA brief tour of the models, information sources, and skills behind Berman’s personal OpenClaw system.
22:31ENMatthew Berman· 2026년 2월 5일Matthew Berman’s OpenClaw Setup: Models, Workflows, and SecurityMatthew Berman · Forward FutureA walkthrough of a personal AI assistant’s configuration, scheduling, integrations and practical automations, with attention to the risks of granting it access.
21:12ENMatthew Berman· 2026년 1월 26일Clawdbot as a Personal AI Assistant: Workflows, Costs and RisksMatthew Berman · Forward FutureMatthew Berman demonstrates a local agent connected to messaging, cloud services and models, and reports what worked, failed and cost more than expected.
7:49ENMatthew Berman· 2025년 12월 2일DeepSeek V3.2: Reasoning, Sparse Attention and Agent TrainingMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s December 2025 model release, its benchmark results and the techniques used to improve long-context efficiency and tool use.
15:29ENMatthew Berman· 2025년 9월 24일Building a Multi-Agent Research Team with Strands AgentsMatthew Berman · Forward FutureMatthew Berman builds from a calculator agent to a multi-agent business-report demo, with examples of tools, model selection and orchestration.
14:04ENMatthew Berman· 2025년 4월 29일Qwen3: Open Weights, Adjustable Reasoning and Tool UseMatthew Berman · Forward FutureMatthew Berman reviews the April 2025 Qwen3 family, its benchmark claims, training pipeline and local demonstration.
19:06ENMatthew Berman· 2025년 4월 25일Sleep-Time Compute: Preparing AI Context Before a QuestionMatthew Berman · Forward FutureMatthew Berman reviews a 2025 paper on moving some reasoning ahead of a user query, and explains where its experiments found benefits and limits.
19:06ENMatthew Berman· 2024년 12월 28일Building Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.
9:58ENMatthew Berman· 2024년 8월 2일Abstract AI: A Proposed Routing Layer for Language ModelsMatthew Berman · Forward FutureMatthew Berman outlines a startup idea for choosing models and workflows by cost, speed and quality.
19:09ENMatthew Berman· 2024년 4월 28일OSWorld: Evaluating Computer-Use Agents in Real ApplicationsMatthew Berman · Forward FutureMatthew Berman explains the 2024 benchmark’s observation–action loop, task-specific checks and early results, with the limitations of its experimental setup.
15:11ENMatthew Berman· 2024년 1월 25일Building a Transcript-to-Article Team in AutoGen StudioMatthew Berman · Forward FutureMatthew Berman configures a retrieval skill, two agents and a group workflow, then troubleshoots missing credentials and output.
10:13ENMatthew Berman· 2023년 10월 28일Building a Business Chatbot with GPTBots.aiMatthew Berman · Forward FutureIn a sponsored 2023 walkthrough, Matthew Berman configures an assistant, adds business knowledge, corrects a response and builds a branching flow.
38:07ENMatthew Berman· 2023년 10월 26일AutoGen Advanced Tutorial: Configuration, Memory, Retrieval and ToolsMatthew Berman · Forward FutureMatthew Berman walks through the 2023 AutoGen interface for multi-agent configuration, caching, retrieval, teachable memory and function calls.
7:02ENMatthew Berman· 2023년 10월 18일Connecting AutoGen to a RunPod-Hosted Model with Text Generation WebUIMatthew Berman · Forward FutureIn a 2023 walkthrough, Matthew Berman connects AutoGen to Dolphin 2.1 Mistral 7B through an OpenAI-compatible API and tests a small coding task.
15:03ENMatthew Berman· 2023년 10월 10일A 2023 AutoGen Tutorial: Local Agent Setup and Code ExecutionMatthew Berman · Forward FutureMatthew Berman builds a local assistant and user-proxy workflow, then tests how the agents generate and run Python. AutoGen’s packages and APIs have changed since this tutorial.