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<div style="display: none; max-height: 0px; overflow: hidden;">Miura-Ko adapts the AV autonomy framework to AI adoption, sorting companies into six levels based on what AI can see, do, who can extend it </div>
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<h1><strong> TLDR Founders <span id="date">2026-05-04</span></strong></h1>
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The entire modern SaaS industry was built on the per-seat licensing model. However, Microsoft says that model is dying. In the company's new model, the seat remains, but it becomes a packaging mechanism for prepaid consumption. Beyond a certain level, users pay per token, per agent action, or per outcome.
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'AI-first' asks whether AI can do the work of the human pilot. 'AI-only' means extensive workflows in which no human sits inside the operating loop. Humans still set the goals, values, constraints, and conditions for escalation, but execution runs end-to-end on machines. This shifts humans from participating in workflows to being a steward of the system.
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Miura-Ko adapts the AV autonomy framework to AI adoption, sorting companies into six levels based on what AI can see, do, who can extend it, and how the org chart has changed. Most "AI-forward" companies still sit at L1 personal productivity or L2 functional silos, while L3 requires agents acting across CRMs, code, and tickets through MCP and shared skills authored by non-engineers. L4 introduces a compounding operating system where finance staff and AEs ship production internal tools and policy-driven agents fix issues with human review only at merge, while the still-hypothetical L5 has the system noticing problems, acting within delegated authority, and updating shared memory without a human initiating the loop.
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Buyers are showing up to your homepage with the comparison already done. They ask an assistant to shortlist vendors, explain tradeoffs, and rule out obvious mismatches before clicking anything. Your positioning got rebuilt from whatever the model could find: blog posts, support docs, comparison pages, YouTube clips, third-party reviews. One company doubled lead quality by editing pages LLMs already cited, not by chasing more citations. Another had so much old content that AI answers described the product wrong. Messaging drift used to be a brand problem. Now it shows up in shortlists.
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AI made competent content cheap. What's still scarce is a clear way of seeing the market that customers start repeating back to you. A blog, podcast, founder account, or event doesn't compound because it's "useful." Useful is everywhere. It compounds when it gives buyers a frame they didn't have, a way to name what they were already feeling. The Stripe and Notion versions of this look like content strategy, but they're really positioning. Name the customer's half-formed belief better than they can, and they'll start using your words to explain the problem.
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<strong>Releases (2 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Linear Releases integrates with CI/CD tools to precisely track the deployment environment, version, and status of every issue. It gives team members and agents full deployment context so they can see what's live to customers, not just what's been merged. Releases will automatically issue status updates when their associated code changes land in production. It supports both continuous deployment and scheduled release methodologies.
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<strong>Add Custom Agents to private Slack channels (1 minute read)</strong>
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Notion's Custom Agents can now read and reply in private Slack channels. They can only see the private channels they are invited to. The Slack API Connector allows users to find quick answers in Notion using information from Slack conversations. The feature is only available on the Business and Enterprise plans.
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<div style="text-align: center;"><strong><h1>Miscellaneous</h1></strong></div>
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<strong>If AI is so great, why isn't it working? (28 minute read)</strong>
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Models are already smart enough. Enterprises shouldn't be holding out for AGI. The companies that build the operational layer underneath the models, as opposed to waiting another five years for frontier AI to improve, will win the next decade.
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<strong>AI GTM Refactor: 5/3/2026 (6 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
AI models are now good and cheap enough. There are great tools that can give any company a competitive edge. It's easier than ever to build. Take an AI-pilled customer-facing engineer and give them a Vercel account and unlimited token spend. You'll be surprised what they can ship in a weekend.
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<strong>When Your VC Leaves, You Are Fundraising Again (9 minute read)</strong>
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A founder's responsibility to act in the best interest of their company and its shareholders doesn't change just because a partner has left.
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<strong>Why Does No One in AI Have Support? (9 minute read)</strong>
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Almost no non-enterprise AI apps have any real form of support.
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<strong>Most Companies Aren't Anywhere Near Ready for AI (5 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
AI is about execution, and it's quite powerless when it doesn't know what to execute.
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<strong>It's always about Velocity (9 minute read)</strong>
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<span style="font-family: "Helvetica Neue", Helvetica, Arial, Verdana, sans-serif;">
Speed only tells you how fast you are moving, whereas velocity tells you how fast you are moving and where you are going.
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