sequoia put out a blog post called 'services is the new software' -- look at this map of over $1T in services being replaced by AI agents
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Sequoia naming it makes it real for a lot of founders who were still hedging. The service layer is where the margin lives -- that's what AI is eating first.
This map is great, but most founders will read it, nod along, then keep building another SaaS dashboard. Execution gap is wider than the opportunity gap.
Right now, I have a few dozen tools to automate my life. Every single thing that I do more than once every week is now a tool... These agents are deterministic. They don't use an LLM to generate answers, so they will always return the same output given the same input.
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Deterministic agents are the underrated distinction nobody talks about. LLM for planning, deterministic execution for delivery -- that separation solves most reliability headaches.
Most 'AI automation' people are building one-shot scripts and calling them agents. Scheduled, deterministic, and actually reliable is an entirely different product category.
Business is actually simple. You don't need a website, a logo, or a rebrand. You need to talk to people. The more hands you shake, the more money you make.
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This lands harder because so many founders build for 18 months in silence then wonder why nobody buys. Distribution is built by talking, not by shipping.
The startup ecosystem has somehow turned 'talk to customers' into a controversial take. If your go-to-market strategy is a product launch, you've already lost.
Make your own App Store. [QT: AI coding agents can now deliver one-shot custom apps straight to your phone. It's the beginning of the end for the iPhone's dominance.]
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When distribution flattens, value moves back to the idea itself. AI-native app delivery changes who gets to participate in software -- not just who can build it.
Apple's 30% cut always looked like a tax on captive distribution. AI-native app delivery might be the first structurally credible threat to that model.
The hostile tax system gives you an incentive to never scale your business beyond €200k/year. So every business tries to stay small, and doesn't want more customers.
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Tax systems that punish growth literally build the culture they deserve. When the incentive is to stay small, everything does -- the businesses, the ambitions, the country.
Hot take: We're shipping AI agents that can book flights, write code, and manage money -- but nobody's built a framework for who's liable when they mess up. The 'move fast' crowd is building autonomous systems with zero accountability infrastructure. This won't age well.
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The liability gap in agentic AI is the biggest unaddressed risk in the space right now. Who pays when your autonomous agent double-charges someone or executes the wrong trade? That framework doesn't exist.
'Move fast' gave us a decade of social media abuse problems. Running the same playbook on systems that can autonomously move money is a different order of recklessness entirely.
Token issuance failure rates hit record highs due to low-float, high-FDV models. Urges 2026 projects to launch with >20% initial supply, proven PMF, real revenue.
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Low-float, high-FDV became the standard playbook because it transferred risk cleanly to retail. The market figuring that out is healthy, not a crisis.
If you need 20%+ circulating supply and real revenue to have any credibility at launch, most 2024 tokenomics were just structured exit liquidity with better branding.
Claude Code's source just leaked via an npm packaging mistake. Supply chain security in AI tooling is still an afterthought. And that's a problem when these tools have access to your codebase, your terminal, and your files.
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The architectural exposure is a useful reminder that supply chain trust in AI tooling hasn't caught up with how deep these tools are embedded in dev workflows.
You gave an AI tool access to your terminal, your codebase, and your files -- then were surprised the tool itself might have security gaps. Trust hierarchies matter.
Many crypto projects fail: because they launch a token first... Then spend months trying to figure out what it actually does. @ACIToken seems to be taking the opposite approach: Build the tools first. Make the token useful second.
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Projects that treat the token as a coordination mechanism rather than the product itself are the ones that survive the next cycle. Utility first is the only durable model.
Launching a token before you have a product isn't a growth strategy, it's a fundraise with better branding. The market's getting faster at spotting the difference.
People over complicate SaaS growth. Want more users? Show them the problem you solve. Want their trust? Show them the founder who built the solution. Put the right message in front of the right user on the right platform. Repeat daily.
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Clarity beats cleverness every time in early SaaS. Most growth problems are positioning problems in disguise -- and positioning is solved by talking, not by optimising.
Half the 'growth strategy' content on here is procrastination dressed up as planning. The founders winning are talking to customers, not reading threads about talking to customers.