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LinkedIn. Crunchbase. CRM. Inbox. Last transcript. Fifteen minutes before every call, hundreds of times a year. "There should be an AI for this" - well, now there is.
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LinkedIn. Crunchbase. CRM. Inbox. Last transcript. Fifteen minutes before every call, hundreds of times a year. "There should be an AI for this" - well, now there is.
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Many AI startups are crushing revenue records because they are using a dishonest metric. Companies are reporting inflated ARR due to long-term enterprise deals they can report now but also opt out of after 12 months. On top of this, some companies are bundling full-time forward-deployed engineers into deals that massively reduce margins and sometimes produce negative margins. A wave of enterprise AI companies will collapse if customers start triggering their opt-out clauses or aggressively negotiate down long-term pricing.
The types of roles at startups are changing. Keeping up with the industry now requires adapting your skillset and evolving. This post puts together a list of some of the hottest roles in tech right now. They include internal automations and efficiency, founding salesperson, labs teams, forward-deployed engineering, creative direction/content, go-to-market engineering, and chief of staff.
Companies need to have a continuously updated, source-grounded, conflict-resolved understanding of who they are, what they're doing, and how they work. This should be delivered as files that any agent can read. This understanding will compound and create value that no amount of money can buy later. It will create a new moat that's proprietary and grows over time.
The hiring problem nobody talks about is that you can't evaluate domain expertise you don't have. You know you need someone sharper than you in a given area, and that's exactly why you can't tell which candidate actually is. The test that works is whether they generate ideas that reshape how you think about the company and whether you'd learn from them in meetings. The sharpest gut check is simpler, which is that if you feel it's easier to just do the work yourself, you hired the wrong person.
Vertical AI startups can compete with legacy incumbents by building customer-centric "systems of love," ensuring standalone product paths, and partnering strategically with non-dominant ERPs. Founders should avoid costly litigation and consider giving up margins if necessary to maintain growth momentum. Structural inertia and poor responsiveness of incumbents create opportunities for new platforms.
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Open-source video rendering framework that lets you create, preview, and render HTML-based video compositions.
Run a self-hosted AI assistant that autonomously plans and executes tasks on a local machine.
Evaluate an app idea by scoring it across key dimensions through an online assessment.
The 2% inflation target shapes the cost of capital for every founder raising a round, so it's worth knowing where the number came from. You'd assume rigorous economic research. Nope. A New Zealand finance minister pulled it out of the air during a 1980s TV interview to influence public expectations, and every central bank on earth just copied it. The broader argument is that good deflation (prices falling because entrepreneurs found cheaper ways to produce) is actually the definition of economic progress, and Moore's Law is the cleanest proof since nobody waited until 2024 to buy a computer despite knowing prices would halve every 18 months.
When software was expensive to build, commitment was cheap, and changing direction was the crisis that demanded a name. Now that building is cheap, the economics invert. Commitment becomes the expensive thing, and iteration is the default mode. The companies winning now look less like ships changing course and more like test kitchens running permanent R&D, which is why calling any given change a pivot has started to sound like a word from a different era.
Founders in the AI sector currently prioritize investors who offer specialized operational expertise and industry connections rather than simple capital deployment. Emerging professionals can bypass personal capital constraints by joining venture capital scout programs, which provide institutional funding allocations in exchange for a percentage of future returns. Successful angels build their portfolios by focusing exclusively on domains where they can provide unique strategic value and by restricting their investments to intimately known peers or exceptionally proven founders.
Open source has always licensed its code freely, but if you couldn't program, that freedom meant nothing.
Linear's CEO pushes back on the current wave of AI design tools, which all assume design is the act of producing an interface.
A new MCP tool integrates with Claude.ai or ChatGPT to streamline fundraising processes for founders.
The entire Salesforce, Agentforce, and Slack platforms are now exposed as APIs, MCP, and CLI.