Hyperagent: A Sponsored Demonstration of a Multi-Agent Workflow

Matthew Berman shows a cloud-based workflow that turns a property listing into a real-estate video.

MBMatthew Berman연사 · Forward Future
채널
Matthew Berman
게시일
2026년 9월 10일
영상
1:04
읽기
1분
슬라이드
1
원문
영어
YouTube에서 열기
스크롤하면 영상이 오른쪽 아래로 작아져 계속 재생됩니다. 자막은 읽기 언어를 따릅니다.
읽기 언어2개 언어로 읽을 수 있음
이 글은 아직 한국어 번역이 없어 영어 원문으로 표시합니다.
요약

30초 요약

In this September 2026 short sponsored by Hyperagent, Matthew Berman describes the product’s specialist-agent approach and shows a real-estate video workflow. He says the task took about 30 minutes; the clip does not independently measure the output’s quality or reliability. The Airtable acquisition he references had closed before the video, with the Hyperagent business excluded from the deal.

  1. 1Airtable and HyperagentBerman links the product to Airtable’s history; the Hyperagent business was excluded from the completed Bending Spoons acquisition.
  2. 2Teams of agentsThe sponsored presentation describes coordinating specialist agents in a cloud-based workflow.
  3. 3A property-video exampleBerman shows a listing link used to gather property information and images, and says the process took about 30 minutes.

핵심 정리

  1. Hyperagent sponsored the video and is presented as a cloud-based product for coordinating teams of specialized AI agents.
  2. Berman shows a workflow starting with a property-listing link and says it gathers images and information for a video.
  3. The claimed 30-minute result is a single sponsored demonstration, not a controlled assessment of cost, accuracy or reliability.
  4. Bending Spoons completed its Airtable acquisition on September 4, 2026; the transaction excluded the Hyperagent business.
전문

챕터별로 다듬은 전문 읽기

원본 자막만 보기
01

Airtable and Hyperagent

Berman introduces Hyperagent in the context of the Airtable deal. The video is sponsored by Hyperagent.

In this short sponsored by Hyperagent, I introduce the product in the context of Airtable’s sale. Bending Spoons completed its acquisition of Airtable on September 4, 2026, at a reported enterprise value of $1.285 billion. The transaction excluded the Hyperagent business; the deal itself does not establish how well the product works.

Hyperagent is presented as a cloud service for coordinating teams of specialist AI agents rather than interacting with just one agent. I show a real-estate example in which a prompt and Zillow listing link lead the system to gather property information and images for a cinematic video.

02

A multi-agent demonstration

He describes specialist agents and demonstrates a real-estate video workflow. The short clip shows one example rather than a systematic test.

The property-listing workflow
슬라이드 1 / 1The property-listing workflowThe displayed interface shows the agent collecting image URLs from a listing during the sponsored demonstration.

I say the example took about 30 minutes and that I could review the result afterward from a computer through the cloud. This is one sponsored demonstration: the short clip does not independently establish accuracy, rights to the underlying images, repeatability or typical costs. I also mention a $100 promotional credit offer, whose terms and availability may change.

같은 채널의 다른 글

슬라이드 12장34:21EN
Matthew Berman· 2026년 10월 27일Matthew Berman Examines Anthropic’s IPO Filing, AI Growth and GovernanceMatthew Berman, Sam Altman · Forward FutureThe presenter reviews the S-1’s financial metrics, compute strategy and voting structure while questioning the tension between rapid AI development and safety.AnthropicAI Safety엔터프라이즈 AI+2
슬라이드 2장0:36EN
Matthew Berman· 2026년 10월 25일Kimi K3.1 and a Rubik’s Cube Solver DemonstrationMatthew Berman · Forward FutureMatthew Berman shows a scrambled virtual cube being solved and gives the Kimi K3.1 test a favorable assessment.평가(Evals)코딩 에이전트Open-weight models
슬라이드 6장25:50EN
Matthew Berman· 2026년 10월 24일Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.Open-weight modelsBenchmarksAI cost & performance+1
슬라이드 2장32:20EN
Matthew Berman· 2026년 10월 23일Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.Local inferenceOpen-weight modelsAI cost & performance+1
슬라이드 6장1:03:37EN
Matthew Berman· 2026년 10월 23일Matthew Berman’s Team Tests Kimi K3.1 on Animation, Games, and ChartsMatthew Berman, Alex, Brian · Forward FutureA live team AMA turns into an informal test of Kimi K3.1, from personal-agent workflows to motion graphics, a browser game, and a benchmark chart.코딩 에이전트Generative media평가(Evals)+2
0:53EN
Matthew Berman· 2026년 10월 22일Sam Altman on AI and the Discovery of New KnowledgeSam Altman · OpenAIAltman expects progress in mathematical discovery to extend to biology, materials and energy.AI for scienceMathematicsComputational Biology+1