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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The only reason why Instagram worked early on
Instagram turns 16 today. Before Instagram, there was Burbn. Systrom named it after his taste for bourbon. It let you check in somewhere, post your plans, earn points for hanging out with friends, and share a photo. He and Mike Krieger cut everything except photos, comments and likes, and rebuilt it in about eight weeks. Instant camera, telegram. Instagram. Source: Tim Ferriss
13 Businesses for the Age of AI
In this solo episode, I walk through the 13 businesses I think are left to build in the agentic era. I believe that in a world of agents and abundance, owning the right assets puts you in a better position. For each business, I explain what it is, why it holds up in a world of agents, and one or two examples, from Othership's sauna clubs to Osmo's window-cleaning robots. This episode gives you a map of where to build next, at any age. Timestamps 00:00 – Intro 01:15 – AI-Native Service Firms 02:57 – Offline Businesses 05:41 – Distribution and Organic Audiences 07:34 – Proprietary Data Sets 09:08 – Domain-Specific Harnesses 12:16 – Robotics and Physical AI 14:01 – Physical Products With a Fan Following 16:34 – Compute and Energy 17:31 – Health, Longevity, and Care 19:30 – Marketplaces and Social Networks 21:04 – Real Assets 21:46 – Vertical Agents 22:18 – Security 24:08 – Closing Thoughts Key Points • In an AI-native service firm, agents do most of the delivery and a human reviews the exceptions. • Ad clicks went from about five cents in 2009 to $1–5 today, so I start with organic audiences. • Proprietary data and domain-specific harnesses are the two gold rushes I see right now. • Offline businesses, niche hardware, and robotics sell rooms, objects, and labor that agents only support. • Compute, energy, and security are the scarce inputs every agent depends on. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/
The Biggest Shift in Cybersecurity in 30 Years
a16z General Partner David George sits down with Armadin founder and CEO Kevin Mandia to discuss what happens to cybersecurity when attackers can operate at machine speed. After 30 years in security and building Mandiant, Kevin says AI convinced him to get back on the field. He explains how AI changes the economics of cyberattacks, allowing attackers to probe thousands of paths simultaneously, and why that means defense will ultimately need to become autonomous too. They also unpack Armadin’s approach: continuously attacking customers’ systems with AI to find exploitable vulnerabilities before adversaries do, then building toward autonomous defenses that can respond in real time. Kevin shares what Armadin has learned from finding more than 90 zero-days in production environments this year, why humans can’t remain in the detect-and-respond loop, and how the entire security stack could change over the next few years. Timestamps: 00:00 - Intro 01:06 - Why Kevin came back to the field 04:19 - What AI attacks look like today 07:18 - Nation state vs AI drone swarms 14:34 - Why pen testing is dead 18:36 - Autonomous defense explained 21:22 - The future of the SOC 27:04 - Lessons from the Hugging Face incident 35:44 - Building a company at AI speed Resources: Learn more about Kevin Mandia and Armadin: https://www.armadin.com/team-members/kevin-mandia Follow David George on X: https://x.com/DavidGeorge83 Learn more about Armadin: https://www.armadin.com/ Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should
Google's AI Infrastructure Chief, Amin Vahdat, on the Physics & Economics of Frontier AI
At 100,000-accelerator scale, something fails multiple times an hour, which is why Google's Chief Technologist for AI Infrastructure Amin Vahdat thinks FLOPS is a vanity metric. The metric that matters is what he calls goodput: the useful work a workload actually delivers through real failures. Amin walks through the calculus that split the TPU line into 8i and 8t for the first time, why the TPU's core primitives haven't changed since v1, and how Google and DeepMind co-design in the same rooms, intercepting chip architectures mid-flight before tape-out. He explains why long-horizon agents are sending demand for CPUs and storage through the roof alongside accelerators, how optical circuit switches reroute light to a spare rack in milliseconds, and why Google would rather wait on a utility than build its own gigawatt. We also cover orbital data centers and the multi-megawatt rack of 2036. Hosted by Sonya Huang, Sequoia Capital 0:00 – Introduction 1:47 – What makes a data center an AI data center 5:30 – Goodput, not FLOPS: holding yourself accountable when something fails every hour 11:52 – Doubling token capacity every six months, and where the gains actually come from 15:32 – The TPU bet: from a contrarian call in 2013 to splitting 8i and 8t 23:30 – The case for and against co-design 26:11 – Shoulder to shoulder with DeepMind: intercepting chips mid-flight 34:16 – Long-horizon agents change the shape of the data center 37:50 – Optical circuit switching and the state of networking 42:35 – Power is the binding constraint: utilities, gigawatts, and sizing a data center 49:23 – Training vs. serving clusters, seven-year-old TPUs, and open standards 58:29 – Orbital data centers and the supercomputer of 2036
3 businesses we think are about to blow up
*Database of 140+ business ideas:* https://clickhubspot.com/2blw Episode 868: Shaan Puri ( https://x.com/ShaanVP ) and Sam Parr ( https://x.com/theSamParr ) talk about 3 business ideas. — Show Notes: (3:08) Idea: Oxytocin dosing (20:17) Idea: Loneliness solutions (27:30) Idea: Faith-based businesses (27:33) Angel Studios (34:36) What’s the reaction to the action? (42:03) The brutal business of making hit movies — Links: • Anduril - https://www.anduril.com/ • Oculus - https://www.meta.com/quest/ • BlueChew - https://bluechew.com/ • Hims - https://www.hims.com/ • Beckley Psytech - https://www.beckleypsytech.com/ • Knights of Columbus - https://www.kofc.org/ • Good Sam - https://www.goodsam.com/ • AARP - https://www.aarp.org/ • Angel Studios - https://www.angel.com/ • The Chosen - https://www.thechosen.tv/ • A24 - https://a24films.com/ • Brick - https://getbrick.app/ • Grindr - https://www.grindr.com/ — Check Out Sam's Stuff: • Hampton (joinhampton.com): My community for founders. Average member does $25m/year. Many of the guests are members. Get after it...apply: http://joinhampton.com/mfm — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Shaan uses Mercury across all of his companies. you can too: http://mercury.com/ Mercury is a fintech company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., Members FDIC • I run all my newsletters on Beehiiv and you should too + we're giving away $10k to our favorite newsletter, check it out: beehiiv.com/mfm-challenge My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano /
The Current State of Consumer AI
a16z Editorial Partner Elena Burger sits down with investing partners Olivia Moore and Josh Elman to unpack the seventh edition of a16z’s Top 100 Consumer AI Apps, including a new dimension this time: what consumers are actually paying for. The data reveals a striking power-user economy. Only a small share of consumers currently pay for AI, but among those who do, spending is heavily concentrated at the top. Olivia and Josh discuss why developers, creators, and other power users dominate spending today, and why subscriptions may not be the business model that ultimately brings consumer AI to everyone. They also dig into the rise of personal agents, the different trajectories of ChatGPT, Claude, and Gemini, how ads could reshape AI economics, and the enormous amount of consumer white space still left to build, from shopping and entertainment to social, dating, and marketplaces. Timestamps: 00:00 - Intro 00:56 - Inside the 7th edition 05:55 - Muse and Instinct's launch numbers 09:14 - The privacy wall for personal agents 14:39 - 4.5% pay, $903/month at the top 20:20 - Why subscription is the wrong model 23:51 - OpenAI's $1B ad run rate 29:21 - ChatGPT vs Claude vs Gemini 32:30 - Where creative tools still win 45:12 - The white space: dating, shopping, entertainment Resources: Read the Top 100 Consumer AI Apps, Seventh Edition: https://www.a16z.news/p/top-100-consumer-ai-apps-seventh Follow Olivia Moore: https://x.com/omooretweets Follow Josh Elman: https://x.com/joshelman Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for information
The Best AI Gets Out of the Way
Setting up and fiddling with agent loops isn't the future. Tibo Sottiaux, Head of ChatGPT & Codex, on a permanent, active intelligence that's available on any screen and gets out of the way when you don't need it.
This crazy simple app makes $50K/month
6 months ago, Lino had never built an app in his life. Then he stumbled upon the app community on X, made some connections, and started building. Just 6 months later, he's grown his first app to over $50K per month and changed his life forever. In this video, he will break down his unbelievable app idea and how he grew it so fast. *iOS App Ideas Database:* https://clickhubspot.com/a68v Say hi to Lino: https://x.com/LinoLeighton Check out AbMaxx: https://apps.apple.com/us/app/abmaxx-become-shredded/id6757769125 🔔 Follow the Second Channel: @StarterStoryBuild 🏁 We're hiring: starterstory.com/jobs Chapters: 0:00 - Can you change your life in 6 months? 1:08 - What’s your story? 1:34 - What’s the app? 2:15 - Finding the idea 2:49 - More iOS app ideas! 3:27 - an old idea, remixed 4:03 - Building process 5:22 - Tech stack 6:01 - Zero to $10K/month 7:24 - $10K to $60K/month 8:34 - Lino’s app playbook 12:05 - App demo 13:20 - Final advice 14:45 - Pat and Gus reflections This video is an educational case study of this founder’s experience. It is not financial advice and does not guarantee any income or results. Every business is different and your results may vary.
$13k MRR game app founder explains why gaming is a $100B industry
Meet Ken. He left a big tech job at Meta to build Harpagia, a text-based idle RPG, entirely by himself. A few hundred active users. Over $100K in revenue per year. ~$13K/month at peak $18K. Zero spent on ads. His take: the opportunity isn’t the next Flappy Bird or Clash of Clans. It’s building something you genuinely care about and finding the people who care about it too.
OpenAI’s Head of ChatGPT: We’re entering a new era of AI (again) | Tibo Sottiaux
Tibo Sottiaux leads ChatGPT and Codex at OpenAI. Under his stewardship, OpenAI has shipped some of its most consequential consumer launches: Codex, ChatGPT Work, and most recently, the new Dots personal agent platform. He joined me at DevDay, hours after his team launched more than 20 new products, to talk about where things are heading. *We discuss:* 1. Dots, OpenAI’s new personal AI assistant 2. Why most actions on the internet will soon be taken by agents 3. Why loops, graphs, and fine-tuning agent workflows are a passing phase 4. Which skills are trending up and down in the AI era 5. How Tibo’s Dot warned him about a production outage five minutes before the launch 6. OpenAI’s approach to AI safety *Brought to you by:* WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lenny DX—Engineering intelligence for the AI era: https://getdx.com/?utm_source=lenny&utm_medium=sponsorship&utm_campaign=q42026 *Episode transcript:* https://www.lennysnewsletter.com/p/openais-head-of-chatgpt-were-entering *Archive of all Lenny's Podcast transcripts:* https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0 *Highlights:* https://lennyspodcast.com/mostreplayedmoments *Where to find Tibo Sottiaux:* • X: https://x.com/thsottiaux • LinkedIn: https://www.linkedin.com/in/thibault-sottiaux-27195366 *Where to find Lenny:* • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ *In this episode, we cover:* (00:00) Introduction to Tibo Sottiaux (01:12) How Tibo uses AI in his daily work (03:10) The vision for always-on AI agents (06:15) How AI will continue to change work (07:32) Bringing Codex, ChatGPT, and Dots together (08:20) The sci-fi inspiration behind the technology (09:02) Building AI with the community (10:13) Understanding the Dots structure (11:34) OpenAI’s open ecosystem and plugin rev
$30k/month founder's advice: don't build a SaaS to do nothing
Bro’s advice: don’t build a SaaS to do nothing. Jack built Profit.ai (a Shopify app doing $30K MRR) with zero coding background. His one piece of advice for anyone trying to make the leap: Don’t aim for laziness If your goal is “make money while doing nothing,” you’ll get replaced fast Just ask Claude if it can do the thing, then stick at it
Why Specialized AI Could Beat The God Model
A16z’s Erik Torenberg sits down with OpenRouter’s Alex Atallah and Replit founder and CEO Amjad Masad to discuss why the future of AI may look less like one all-purpose model and more like an ecosystem of specialized models working together. Alex explains why OpenRouter is betting on “neurodiversity”: different models trained in different ways, routed and combined based on the job at hand. Amjad makes a similar case from inside the enterprise, where companies increasingly need to own their AI capabilities rather than depend entirely on a single model provider. They explore what happens when general-purpose agents give way to teams of specialized agents, why smaller models can sometimes be cheaper, safer, and easier to control, and how routing and model fusion could deliver frontier-level performance at lower cost. They also get into agent-to-agent communication, AI security, and why the next generation of companies may need an independence layer across models, clouds, and data. Timestamps: 00:00 - Intro 00:47 - Inside the Stripe acquisition 05:08 - Why OpenRouter needs more startups 08:53 - Enterprises are picking open-weight models 12:26 - Why owning your intelligence matters 19:52 - The case against the god-agent 23:36 - Specialization, Adam Smith style 31:13 - Models training their replacements 34:13 - Will smarter models deceive us? 45:12 - Fusion models at half the cost Resources: Follow Alex Atallah on X: https://x.com/alexatallah Follow Amjad Masad on X: https://x.com/amasad Learn more about OpenRouter: https://openrouter.ai Learn more about Replit: https://replit.com Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id84
What If We Stopped Using GPUs? | YC Paper Club
This week’s Paper Club is all about alternative compute. Modern AI has been shaped by a tight coupling between transformers, backpropagation, and GPUs. But as compute efficiency starts to plateau, there may be very different ways to build the machines that come next. We explore what AI compute could look like beyond conventional digital hardware through optical systems that use light to perform computation, neuromorphic architectures inspired by the brain, and experiments teaching living brain cells to play Doom. Sign up for the next Paper Club, where we'll discuss AI Safety: https://events.ycombinator.com/yc-paperclub-oct7 Chapters: 00:00 — Intro 00:07 — Francois Chaubard: Why Alternative Compute? 03:38 — Beyond Backpropagation 08:08 — Zero-Order Optimization and SOMA 15:06 — Ilker Oguz: Computing With Light 19:27 — Why Optical Computing Isn’t Everywhere Yet 22:23 — Building a Diffusion Model With Light 30:03 — Optical Computing Q&A 39:00 — Alok Vasudev: What Is Neuromorphic Computing? 45:23 — What the Brain Can Teach Us About Chips 49:35 — Where Neuromorphic Computing Stands Today 54:24 — Neuromorphic Computing Q&A 1:04:24 — Sean Cole: Teaching Brain Cells to Play Doom 1:07:48 — Training Biological Neurons With Reinforcement Learning 1:12:28 — How Brain Cells Learn From Feedback 1:15:40 — Biological Computing Q&A Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs
Masterclass: How FDEs make $1M/yr deploying AI agents
Google's most advanced audio models are LIVE, try them for yourself: Gemini 3.8 Live: https://startup-ideas-pod.link/gemini-3.8-live Gemini 3.5 Transcribe https://startup-ideas-pod.link/gemini-3.5-transcribe Gemini 3.5 Live Translate: https://startup-ideas-pod.link/gemini-3.5-live-translate In this episode, I talk with Vas from Varick about what it takes to put AI to work inside a real company. Vas makes the case that AI pays off through process reengineering, and he walks me through the exact method his forward deployed engineers (FDEs) use: interviews, process mining, step sorting, and agents built inside existing systems of record. We go through real engagements, including a $5B public software company and an accounts payable overhaul that cut the cost per invoice from $31 to $6. By the end, you get a clear picture of the FDE role, the business opportunity behind AI roll-ups, and a five-day plan to start on your own. Links Mentioned: FDE Presentation: https://startup-ideas-pod.link/FDE-slides Vas’s Article: https://startup-ideas-pod.link/vas-fde Timestamps 00:00 – Intro 01:31 – Sponsor: Google 03:58 – FDE Overview 05:02 – AI Roll-Ups and Process Reengineering 08:04 – The Personal Systems Analogy 09:55 – Understanding a company’s process (step-by-step) 14:11 – Case Study: $5B Software Company 18:11 – 4 Buckets for Every Step 19:04 – Build Inside Systems of Record 21:36 – Case Study: PE Portfolio 23:43 – Selling to C-Suite Executives 27:07 – Process of Mapping Five NetSuite Companies 28:39 – Example: Accounts Payable Process Map 32:54 – Case Study: 60-Person Accounting Firm 34:51 – When to Use Code, Agents, or Humans 36:00 – Choosing AI Models 38:16 – Sidekick vs Background Agents 40:29 – The 3 Skills of a Top FDE 42:25 – Why FDEs Earn So Much 45:26 – Five-Day Starter Plan 47:39 – On-Premise Hardware Demand 48:36 – OpenAI Private Intelligence 50:20 – The Full Playbook 52:01 – Closing Thoughts Key Points • AI pays off when you re-engineer the process first, th
Ben Horowitz on a Great Product
In The Hard Thing About Hard Things (2014), Ben Horowitz writes that the primary thing a technology startup must do is build a product at least ten times better at something than the prevailing way of doing it, and that two or three times better won’t get people to switch fast enough or in large enough numbers to matter. Video Source: lecture at UC Berkeley’s College of Engineering, 2009.
I Built a $30K/Month Business From a Remote Island (How I Work)
Milly built her $30K/month business from a tiny, remote island with just an internet connection and a team of two. In this video, we do a day-in-the-life dive into how she actually built it from the middle of nowhere: how she spends her time, how she picks what to work on, and how she's deliberately built the whole thing around living a calm, low-stress life rather than chasing scale. *Find your business idea with our free database (over 3k+ ideas):* https://clickhubspot.com/lryw Follow Milly: https://www.linkedin.com/in/milly-tamati/ Check out Generalist World: https://generalist.world/ 🔔 Follow the Second Channel: @StarterStoryBuild 🏁 We're hiring: starterstory.com/jobs Chapters: 0:00 - Meet Milly 1:20 - Morning routines 2:24 - The story behind the business 3:09 - Find ideas inside Starter Story 4:03 - A typical work day 4:43 - Building from a remote island 5:43 - Advice for finding business ideas 6:28 - What does success mean to Milly? 7:34 - Evening routine 8:39 - Advice for builders This video is an educational case study of this founder’s experience. It is not financial advice and does not guarantee any income or results. Every business is different and your results may vary.
Non-technical founder builds a $40K/month game in just a weekend 🥶
Non-technical founder builds a $40K/month game in just a weekend. Meet Frank. He’d never written code in his life. Then he drove home from a wedding, opened Claude, and shipped GeoSports in about 8 hours. Three months later: $40,000/month in revenue 700,000 monthly active users 1,800 pro subs on Stripe ~$30-35K/mo from programmatic ads 53% organic share rate
AI, Infrastructure, and the Next Investment Cycle
a16z’s David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez unpack 25 key charts from the latest State of Markets presentation, from the scale of the AI infrastructure buildout to what adoption looks like inside companies today. They examine why rising markets have so far been supported by earnings rather than multiple expansion, why hyperscaler CapEx is approaching $1 trillion annually, and why demand for compute continues to outrun supply. They also look at the downstream effects of that spending across chips, power, construction, and physical infrastructure. State of Markets Then they move up the stack: OpenAI and Anthropic’s revenue growth, the gap between AI deployment and measurable enterprise impact, the rise of agents, falling inference costs, and what all of this means for SaaS. They close with where the team is spending time next, including consumer agents, robotics, autonomy, AI and biology, personal health, defense, and the continued diffusion of AI across the enterprise. State of Markets Timestamps: 00:00 - Intro 00:59 - Is it a bubble? 06:28 - The $780B hyperscaler CapEx race 13:15 - The new age of atoms 18:21 - Only 2% of enterprise AI is truly tracked 20:28 - Power users spend 20x the median 31:34 - Amazon blocks Muse, Instacart opens up 36:14 - The SaaS bifurcation 42:23 - Stripe's Renaissance data 48:43 - Robotics, autonomy, bio: what's next Resources: Follow David George on X: https://x.com/DavidGeorge83 Follow Sarah Wang on X: https://x.com/sarahdingwang Follow Alex Immerman on X: https://x.com/aleximm Follow Santiago Rodriguez on X: https://x.com/santiago__rdz Read David’s piece ‘There are only two paths left for software’: https://a16z.com/there-are-only-two-paths-left-for-software/ Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://o
OpenAI DevDay: Dots, Agents & $100B Opportunities
I watched almost 60 minutes of Sam Altman on stage at OpenAI Dev Day 2026. Out of 20-plus launches, I pick the three or four that I think can make people billions of dollars in aggregate. I break down Dots, OpenAI's personal agent platform, plus the Decisions API, the Agents API with computer use, and Sign in with ChatGPT. I also share my four-step framework for building in this world and two business ideas I hope someone takes. If you want to build a business and make money around AI, this episode is for you. Timestamps 00:00 – Intro 01:48 – Dots, the Personal Agent Platform 03:29 – OpenAI Doubles Down on Plugins 05:02 – Decisions API 06:43 – Agents API With Computer Use 08:01 – Sign In With ChatGPT 12:36 – Where should you build? 13:46 – Idea: Real-World Work APIs 15:04 – Idea: Analytics for Agent Discovery 17:05 –Closing Thoughts Key Points • Dots gives plugin builders a front door to 1.2 billion weekly active users. • OpenAI is doubling down on plugins to make ChatGPT the app ecosystem for AI. • Sign in with ChatGPT lets users bring their current plan, so a free core app with paid upsells now works. • Workflows too niche for OpenAI to build become viable businesses. • The strongest businesses in this world own the trigger, the action, and the feedback. • Two open opportunities: real-world work APIs and an analytics layer for agent discovery Numbered Section Summaries 1. The Launches Worth Your Attention OpenAI shipped 20-plus features at Dev Day 2026, and I focus on four: Dots, the Decisions API, the Agents API, and Sign in with ChatGPT. I cover GPT 6.1 Soul, Ultrafast, Private Intelligence, and Spaces briefly at the end. 2. Dots and the Plugin Comeback Dots is OpenAI's answer to Muse by Meta and Instinct. A user asks for help, like fixing a permit or finding a restaurant, ChatGPT understands the job, and it selects a plugin, which is essentially a mini app. By my paraphrase, Sam admitted plugins got mixed reviews before, and now he plans to make them a
We Tested the New Wave of Personal AI Agents
a16z General Partner Anish Acharya sits down with Assistant Benchmark creator David Pawlan to unpack the sudden explosion of personal AI agents and what it will take for one to become part of everyday life. David has been testing dozens of assistants across real-world tasks, from managing email and booking travel to handling financial admin. They discuss why the most useful agents may become increasingly invisible, proactively checking you into flights, finding refunds, filing reimbursements, or simply handling the small tasks that pile up across everyday life. They also explore whether the winning interface is an app, text thread, voice, or wearable; how much autonomy consumers will actually give their agents; and what happens when agents start interacting with other agents. From commerce and restaurant reservations to entirely new agent-native services, Anish and David ask what the internet looks like when software starts acting on our behalf. Timestamps: 00:00 - Intro 00:54 - Poke, Instinct, Muse and the agent boom 03:41 - What Assistant Bench actually tests 09:14 - Cost savers beat time savers 14:53 - Muse charm as Meta's data play 20:03 - Silent agents in group chats 26:01 - Proactivity is the real moat 32:21 - Assistant vs agent, defined 40:22 - Amazon blocks Muse, Shopify opens the door 47:35 - The $20/day agent economics Resources: Follow David Pawlan on X: https://x.com/DavidPawlan Follow Anish Acharya on X: https://x.com/illscience Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT
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