TLDR Founders 2026-05-06

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Making your company legible to AI could result in the commoditization of your own moat. Founders need to be building two versions of their company right now: the company that humans work inside and a digital twin that AI agents can navigate, query, and operate in. They need to consider what things should be deliberately kept out of the AI system to protect their advantages. The highest-value things to keep partially illegible are the things that make the company weird, specific, and hard to copy.

The gap between AI-enabled and AI-native companies will look like the gap between cloud-enabled and cloud-native, where the two paths look identical for a while and then diverge. AI-native means rebuilding product, workflow, and org from the floor up, not bolting an assistant onto yesterday's process. The work shows up as a sequence of bottlenecks you solve in order. Adoption comes first, where every engineering manager is required to use Claude Code at roughly the median of their direct reports. Once people are actually using the tools, engineering velocity opens up. One CTO reports his top decile is 5x more productive while the median engineer is up 20%. After that, the rate limit is product taste - whether anyone has the judgment to decide what to build next.

Slash recently raised a $100 million Series C at a $1.4 billion valuation. The company has raised over $160 million in venture capital across four rounds. This post details everything its founder knows about raising venture capital. Most of the lessons were learned through Y Combinator - while its advice is geared towards seed-stage companies, the concepts are still applicable at the growth stage.

Pricing is a surface because customers touch it more often than they touch most product features. Companies need to treat pricing as a hypothesis to test. They need to iterate on pricing as they learn what works. Being cemented in pricing will cause your business to bleed margin and cap growth, a dangerous combination.

The next trillion-dollar company will sell the work, not the tool. AI turns services budgets into something startups can actually attack. The head start belongs to the people who are willing to do the work by hand until the work tells them what to automate. Companies that look like services firms and earn like software firms are never accidents.

LaunchVideo coordinated Helena's launch to 3.6M views, 10x homepage traffic, and 70%+ positive sentiment, taking founder Seijin Jung from 147 followers to 3,000+ in a week. The team rejected the "AI CMO" frame to avoid threatening buyer CMOs, anchored Helena as the "first autonomous AI marketer," and shifted the launch from the standard Tuesday 7 am PT window to Monday to dodge a crowded feed where competing launches all stayed under 3M views.

AEO is the new SEO, and most sites aren't built for it. WordPress.com is. Everyone from enterprise clients to start-ups rely on it for server-rendered pages AI crawlers can read, auto-generated sitemaps, and clean URLs and semantic markup. Whether you're building with AI or trying to get found by AI, WordPress.com is ready

Shopify users can now manage their stores inside ChatGPT or Claude. Users can simply prompt their chosen assistant to add products to their store. The integration allows them to get insights, look up orders, and more without ever leaving the chat. A video demo is available in the thread.

OpenAI has launched a self-serve Ads Manager as well as new CPC bidding and expanded measurement tools. Advertisers can now create and manage campaigns directly through OpenAI instead of relying on managed partnerships and agency relationships. Advertisers in the US can now register for access. The rollout is currently limited and still in beta.

It has become a trend for engineers to turn themselves into agent wrappers. They interact with models to get them to generate their work, but they don't actually make decisions or do any reasoning. It is appealing to use tools that output work good enough that the failure modes don't bite right away. People need to consider what remains defensible when anyone with the same agent can get the same outputs.

Salesforce now estimates that copying context across Slack, Salesforce, Workspace, and ServiceNow costs the average employee two hours of productivity a day. Google Cloud says 75% of its customers use its AI products and 330 of them processed more than a trillion tokens last year. ServiceNow runs 95 billion workflows annually and is moving agents into a governed registry with audit trails. Coordination across systems, not model intelligence, is what's getting in the way.

The more people use AI, the better they will be at using it. Teams need experience in using AI to understand what the technology can do for them. Leaders need to give teams projects with tight deadlines to help teams learn how AI can benefit them. No amount of strategy can fix a lack of experience.

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Japanese startups have strong builders, launched products, and paying customers, but they lack access to capital.

The tradeoff at the heart of AI/labor ratio decisions is resiliency.

The standard in venture used to be having a thesis and a network.