Technology
The people, products and decisions shaping technology.
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This reading list brings together items from the sources selected for Technology. Open each item at its original source for the complete article, episode or video. This is a selection of current coverage, not a complete archive.
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Why Claude can’t be your PM (yet) | Anthropic CPO Panel
What does product management look like when AI changes what teams can build every few months? At the Lenny and Friends Summit, Anthropic’s Ami Vora and Mike Krieger join Dan Shipper to discuss why understanding users, making good decisions, and adapting quickly remain essential to the PM role. They also explore software designed for agents, running experiments in parallel, and bringing the ideas that work into a product people can use. Recorded live at Lenny and Friends Summit on September 10, 2026, in San Francisco.
Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI)
How do you build AI products when the technology and users’ expectations are changing so quickly? At the Lenny and Friends Summit, OpenAI’s Tara Seshan and Nan Yu join Claire Vo to discuss shipping imperfect features, designing agents people can understand, and deciding how those agents should work with other tools. They explain why rapid testing, direct conversations with users, and completing the last mile of a task matter more than ever. Recorded live at Lenny and Friends Summit on September 10, 2026, in San Francisco.
$5T opportunity: AI Roll Ups
In this solo episode, I break down the $5 trillion wave of small businesses set to change hands as their owners retire, and why AI agents make this wave a real opening for solo founders. I walk through how Thrive Holdings and General Catalyst buy accounting firms, property managers, and support centers, then run AI agents inside them to lift margins. Then I show how I'd run a one-person holding company: the folder structure, the agent files, the human approval rule, and my average week. I close with the strongest arguments against AI roll-ups, including the one I take most seriously. Timestamps 00:00 – Intro 01:52 – Why the $5 Trillion Shift Is Happening Now 04:52 – Examples: Thrive Holdings& General Catalyst 08:38 – The Fund Playbook 10:07 – The Small-Deal Gap 10:51 – The One-Person Holdco 14:23 – The Folder Structure 16:47 – The Agent Pipeline 18:38 – Inside a Reviewer Agent File 19:41 – My Week Running the Holdco 21:49 – How to Land the First Business 22:24 – Arguments Against AI Roll-Ups 27:43 – Closing Thoughts Key Points • About a million small businesses, part of a $5 trillion shift, are set to sell by 2035 as owners retire (McKinsey). • AI agents now handle the work these firms run on: data entry, document chasing, status updates, and first drafts. • The big funds chase bigger deals, which leaves the small firms open for solo founders and small teams. • A one-person holdco runs on shared agents and rules, plus a GM with real upside at each business. • A person approves all agent work before it reaches a client. • The corrections log, turned into rules every week, becomes the most valuable asset in the holdco. Numbered Section Summaries 1. Why the $5 Trillion Shift Is Happening Now Three things line up at once. Owners who built accounting practices, insurance agencies, and property management companies in the 80s and 90s want to retire, and their kids and employees often want something else. AI agents can now do the typing, chasing, and status updates
Kākāpō Party
Tool: Kākāpō Party I gave presented a closing keynote for the WeAreDevelopers World Congress North America yesterday. As a STAR moment I decided to weave in references to the record breaking kākāpō breeding season we had in 2026. For my closing slide I wanted to celebrate, and I had seen some buzz around how good Claude Opus 5.5 was at creating pixel art animations. So I rounded up three Kakapo photos from Google image search and dropped them into Claude with this prompt:
Rocket cargo delivery anywhere on Earth in minutes
Hop Aero is building rockets that can deliver cargo anywhere on Earth in minutes. They’re starting with military logistics and other time-sensitive payloads, including temperature-controlled materials with short shelf lives, where getting something there much faster can materially change the outcome. They’ve already built and successfully hot-fired a new rocket engine, and signed $1.37B in commercial LOIs.
Autonomous construction on Earth and beyond
A lot of construction work is still done by hand simply because the machines to automate it don’t exist. That’s become a bottleneck for building things like solar farms, data centers, and other critical infrastructure. Cosmic Robotics is building those machines. Their robots have already installed 11,000 solar panels, and they just signed a major contract with the largest construction company in the country. They’re building the construction robots we’ll need on Earth today, and eventually on the Moon and Mars.
Meta Muse AI Connectors: The App Store for AI?
In this solo episode, I break down the huge business opportunity because Meta has opened Muse, its personal AI agent, to developers. You can now submit a connector, which lets Muse use your service when someone asks it for help, and I think this could be the app store moment for AI. I explain how a connector works, share four startup ideas you can build on one, and cover how to get customers beyond Meta's directory. I also show how I'd build a first version with a coding agent like Claude Code or Codex, and what I'd test before submitting it to Meta for review. Timestamps 00:00 – Intro 01:35 – The App Store Parallel 04:55 – How a Muse Connector Works 07:29 – Startup Idea 1: Lead Gen for Business Suppliers 09:28 – Startup Idea 2: Home Repair Dispatch 11:07 – Startup Idea 3: Paddle Match and Court Finder 12:47 – Startup Idea 4: Family Dinner Planning 14:10 – How to pick an idea? 14:56 – How People Find Your Connector 15:32 – Growth Idea 1: Partner With Creators 16:17 – Growth Idea 2: Product-Led Sharing 17:46 – Growth Idea 3: Connected Marketplaces and Directory Placement 19:34 – Building the First Version 21:38 – Custom Connectors and Meta Approval 23:56 – Where to Start This Week 25:31 – Closing thoughts Muse Connector Prompt: https://startup-ideas-pod.link/muse-connector-prompt Key Points • Meta has opened Muse to developers, and a connector lets Muse use your service when someone asks it for help. • I look closely at the step in a request where someone needs a business that can deliver and money changes hands. • With a small budget, I'd start with lead generation, because I can show a customer a sample before writing much software. • I plan distribution around channels I can reach, such as creators, product-led sharing, and connected marketplaces. • A coding agent can build the first version, and I still inspect the results and test the awkward requests myself. • To start this week, I'd talk to one type of customer about the last time they dealt with the task
Take Upwork jobs, let AI do them (Astra etc). It's absurd
Build your own AI native creative agency with Higgsfield : https://startup-ideas-pod.link/higgsfield In this solo episode, I explain why I expect a wave of one-person businesses built as AI-native service firms, and I show you how I built one. Three things matured at the same time: specialist creative models, Astra as an orchestrator that plans and repairs work, and the Higgsfield API, which puts 50+ creative models behind one key. I demo Studio Operator, the MVP I built to show you how I’d run an AI-native creative Agency, and I walk through the six prompts I used to build it. I finish with a model-by-model primer, three startup ideas, and four filters for choosing which firm to build. Timestamps 00:00 – Intro 01:46 – 3 Shifts, All at Once 03:35 – The AI-Native Service Firm 04:22 – Demand on Upwork and Fiverr 05:16 – Human Agency vs. AI-Native Firm 11:14 – Studio Operator Tour 20:08 – The Six Build Prompts 26:42 – Model Primer by Job Type 32:42 – Idea 1: Always-On Ad Studio 33:52 – Idea 2: Franchise Localization 41:00 – Idea 3: Industrial Catalog Sales Assets 43:15 – Four Filters for Picking an Idea 45:28 – The Self Improvement Loop 46:59 – How to Start 46:11 – Closing Thoughts Studio Operator 6 Prompts: https://startup-ideas-pod.link/Creative_prompt_pack Key Points - Creative models, Astra, and one production API matured together, and that makes one-person creative firms possible now. - Upwork, Fiverr, and Contra show what buyers purchase again and again, so I start from validated demand. - I estimate AI-native firms can reach 60%+ net margins, compared with 10–15% for a typical human agency. - I built Studio Operator with six prompts, one layer of the firm per prompt, in a deliberate order. - I match each job to a model: people, products, text, repairs, long scenes, speech, motion, or finishing. - The strongest ideas pair a creative surface with a repetitive, checkable operational core. Numbered Section Summaries 1. Three Shifts at Once Creative mode
Drone swarm defense
Attack drones are reshaping modern warfare, but many countries still lack an effective way to defend their airspace. Earendil Robotics is building autonomous interceptors, along with the software and training needed to stand up that capability from scratch. Their systems can take off, transit, and intercept targets on their own, reducing months of pilot training to a few clicks. The goal is air defense that’s affordable enough to deploy in large numbers and simple enough to operate at scale.
$30M Writer: Never write AI slop again
Get Your Complete Financial OS at https://startup-ideas-pod.link/brex_SIP In this episode I speak with Nicolas Cole about the real value of everything you write on the internet. Cole has 15 years of experience as a nonfiction writer and ghostwriter, and he runs the SaaS platform Typeshare. He gives me a simple model with three tiers of content: commodity, personality, and original. He also explains the digital brain, which he calls your personal language model, and he shows how AI repeats your approved language at scale. By the end, you know how to judge the short, medium, and long-term value of a piece before you write it. Make AI Sound like you: https://startup-ideas-pod.link/plm Start Writing Online In 30 Days: https://startup-ideas-pod.link/ship30 Timestamps 00:00:00 – Intro 00:03:36 – POV is the Moat 00:05:40 – Language As Open Source 00:11:24 – Value Is Relative To The Reader 00:14:26 – Approved Language 00:17:43 – The Value of AI in Writing 00:22:09 – Commodity Ideas 00:24:23 – How To Set Up The System 00:27:58 – Ownership IS Association 00:33:56 – Build your Personal Data Set 00:39:53 – Branded Content vs Founder-Led Content 00:45:17 – What is Original Content? 00:46:35 – Writing Versus Short-Form Video 00:48:58 – Three Types of Hooks 00:49:50 – Timely Content vs Timeless Content 00:53:27 – Voice is 3 dialed settings 00:56:32 – Finding your Voice 01:00:49 – The Company Brain As The Moat 01:07:30 – Closing Thoughts Key Points • A point of view creates the moat, because copycats must wait for your next idea. • Content sits in three tiers: commodity, personality, and original. Each tier adds different leverage. • Ownership equals association. Volume builds it, and personality details make it strong. • Your life story is the unmade data set, so AI learns it only from your own writing. • Every piece sits on a spectrum from timely to timeless, so match your expectations to the type. • Humans do the thinking and the writing. Robots do the repeating and the re
An ex-OpenAI researcher just deleted language from the LLM
Mux is the video API that translates audio and answers questions about your video. Get $50 in free credits: https://mux.com/fireship Ex-OpenAI researcher Diogo Almeida spent two years in stealth building Jev, a "System 1" AI model that can't talk or write code but claims to be 200x faster, 400x cheaper, and hallucination-free. Let's dive in. Want more Fireship? 🗞️ Newsletter: https://bytes.dev 🧠 Courses: https://fireship.dev
Jev is HERE. How to use it
In this episode, I talk with Ryan Vogel about Jev, a new type of AI built for classification. Ryan shows how Jev takes an input plus an output schema and returns a probability for each choice in about 200 milliseconds. He demos Jev sorting 1,700 emails for 18 cents total, then covers lead scoring, support routing, video clipping, and browser control. I push him on the startup angle: find a business with an expensive queue of incoming information and put Jev at the front of it. You leave with a clear mental model, real use cases, and a simple way to try it today. Links Mentioned: Jev/Typeface AI: https://typesafe.ai AI Gateway: https://vercel.com/ai-gateway Timestamps 00:00 – Intro 02:27 – What Jev Is and Why It Matters 04:32 – Email Triage Demo 07:19 – Jev as an AI Decision Maker 15:46 – How to Use Jev in a Business 20:48 – Startup Idea: Local Services Matching and Instant Quotes 22:51 – Use Case 1: Bitcoin Signal Test and Limits 24:03 – Use Case 2: Auto-Clipping Long Videos 25:27 – Use Case 3: Browser Control: Flight Pick in 7.1 Seconds 26:18 – How to Get Access 27:25 – Closing Thoughts Key Points • Jev is a classifier: an input and an output schema go in, and a probability for each choice comes out. • Ryan's demo scores 1,700 emails for 18 cents total. • Each Jev query takes about 200 milliseconds, whatever the input and output structure. • Use Jev at any point where a business makes fast, repeatable decisions on incoming data. • Keep Jev in an advisory role, and save frontier models for high-intelligence tasks like trading. • Instant access runs through the Vercel Gateway, and a waitlist covers direct access. Numbered Section Summaries 1. What Jev Actually Is Ryan explains Jev as a classifier. You define an input and an output schema, and Jev returns a probability for each option, for example 80% orange, 10% red, and 10% blue for the color of an iPhone. 2. The 18-Cent Email Demo Ryan runs Jev on 1,700 of his own emails and scores each one for category,
The Creative Spirit of Who Framed Roger Rabbit
The Creative Spirit of Who Framed Roger Rabbit I love Who Framed Roger Rabbit, the 1988 movie by Robert Zemeckis. I haven't watched it in quite a few years, and Cypress Frankenfeld just pointed out this sequence from early in the movie: It's a pelican riding a bicycle! Look closely and you'll note that the pelican is animated while the bicycle is a real bicycle. Apparently they filled the wheels with water to add stability, then set it running and guided it with a cable. Cypress gathered more details on the scene. What a delight.
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