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  1. Page 1: Today’s IndexTLDR InfoSec, TLDR Crypto, TLDR Fintech, TLDR IT, TLDR Data, TLDR Dev, TLDR Design, TLDR · 9 stories
  2. Page 2: TLDR InfoSecTLDR InfoSec · 13 stories
  3. Page 3: TLDR CryptoTLDR Crypto · 11 stories
  4. Page 4: TLDR FintechTLDR Fintech · 10 stories
  5. Page 5: TLDR FoundersTLDR Founders · 11 stories
  6. Page 6: TLDR ITTLDR IT · 12 stories
  7. Page 7: TLDR DataTLDR Data · 13 stories
  8. Page 8: TLDR DevTLDR Dev · 15 stories
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  10. Page 10: TLDRTLDR · 15 stories
  11. Page 11: TLDR AITLDR AI · 8 stories
  12. Page 12: TLDR AI — continuedTLDR AI · 8 stories
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Daily Edition · Page 5

THE DAILY INDEX

Technology, AI, software, security, crypto and business

HEADLINES & TRENDS

TLDR Founders

TLDR Founders

THE FUTURE OF THE FIRM

Managing people used to be something you earned after years of grunt work. In this post, two people at OpenAI who were running teams of agents at 24 walk through where AI could end up on a company's org chart. In the simplest version, nobody changes seats, so everyone just becomes a manager (an accountant still owns the accounting while agents do the spreadsheet work). The accounting team doesn't shrink either, because the rest of the company is getting more productive and needs more accounting than before.

links.tldrnewsletter.com · 22 min

TLDR Founders

DATABRICKS & THE FUTURE OF THE FIRM

Most companies don't need smarter AI models to unlock major productivity gains. The bigger bottleneck is context: models lack access to internal knowledge, unwritten processes, and the judgment sitting in employees' heads. Databricks is building a shared system of record that gives agents this context, alongside permissions and feedback on their work. This could reduce management layers devoted to moving information around, while shifting employees toward defining tasks, delegating execution, and judging results. The lasting competitive advantage would come from capturing what a company learns, so its AI systems improve even when it switches models.

a16z.com · 29 min

TLDR Founders

WHAT COMES AFTER SELLING WORK?

Companies spend about $6 on services for every $1 on software, so a lot of AI startups now want to be the law firm instead of selling it software. Selling the work itself might only be step one. Big firms are building their own AI (Kirkland & Ellis is putting $500M into its stack), so give the service away and make money on the deals and data that run through it. For example, Rockwell runs a free benefits concierge for employees at mid-market companies, so it sits right in front of their healthcare spending.

links.tldrnewsletter.com · 7 min

TLDR Founders

DESIGN THE DINNER FOR THE FOLLOW-UP

Most customer dinners are planned around the night itself, and the "great meeting you" email afterward gets ignored. One conference dinner turned into $4M in revenue for Recall.ai. The trick was to put a rep at every table whose only job was seating customers next to prospects, so prospects heard about the product from people who already trusted it. Reps then sent each prospect an intro to the customer they sat beside ("You two were talking about X at the dinner"). That email is much harder to ignore than a thank-you note.

links.tldrnewsletter.com · 2 min

TLDR Founders

HOW I BUILT THE MOST AI-PILLED COMPANY IN THE WORLD

Spawn is a company with 10 people that spends 30 times its payroll on AI tokens. The company ships almost as much as Anthropic, with 77,000 substantial changes in the last 30 days. Its work is done by a fleet of permanent AI agents that each own a part of the company. Each new model improvement has made the team faster and more coherent, and pointed the company's velocity more in the right direction.

links.tldrnewsletter.com · 20 min

TLDR IndexPage 5