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Salesforce's first perpetually free CRM helps companies ditch fragmented spreadsheets. Grow with the world's most trusted platform.
You don't have to take more risk, just structure your life to be exposed to the upside.
In 2025, seed funding surged with record-breaking rounds, particularly in AI, and US companies secured nearly half of the global seed investments.
Henry Ford's customers didn't want cars, they wanted to get from point A to point B - cars just fit that demand better than horses.
Leaders talk constantly - emails about deadlines, budget updates, workflow changes - but go months without mentioning vision or values.
Vibe coding is changing how value is communicated - people will still pay for edge cases, interrogations, and the accumulated wisdom from serving real customers with real problems.
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Seat-based, usage-based, or outcome-based: which pricing strategy is right? Most founders pick a model based on what competitors do, not what fits their product.
Seed funding is back to near-peak levels, but the money is significantly harder to touch. Investors are piling more cash into fewer rounds, essentially ignoring everything outside of SF and NY. The most telling stat is headcount: the average seed startup has slimmed down from 10 people to just 6, likely because AI is picking up the slack. However, don't let the tools fool you into going it alone: VCs still fund co-founders at double the rate of solo acts, despite the data showing that 25% of those partnerships end in a breakup by year four.
The feedback loop for physical products is speeding up. We used to assume that building hardware meant long timelines and high costs for every mistake. That dynamic is fading. Modern simulation tools and AI assistants now let engineers iterate on physical designs almost as fast as they write code. The barrier to entry is shifting from manufacturing logistics to pure design capability.
At your startup, it's important to recognize that a "messy yes" is often more dangerous than a hard "no." Teams tend to drift into "strategic ambiguity" - nodding along to avoid conflict without actually agreeing on the trade-offs. The fix is to force the friction upfront: make the team stack-rank priorities (no ties allowed) and write down exactly where you disagree.
Reinforcement learning (RL) has gone from being a promising path towards general intelligence to a taboo phrase over the past year. It has proved highly effective inside AI labs, but outside of the labs, its use cases remain surprisingly underdeveloped. Most efforts appear to be largely experimental and have yet to scratch the surface of the sophisticated techniques used within the frontier labs. This post looks at the intricacies of building effective RL approaches, assesses current use cases, and discusses what founders should consider when commercializing RL-based systems.
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Salesforce and HubSpot are for big enterprises with RevOps teams. Lightfield [9] — an AI-native CRM with an embedded call recorder — was made for startups. It automatically captures every customer communication so you never have to manually enter data. Never lose
Safebooks is an intelligent automation layer for quote-to-revenue finance operations.
Roark is a platform to test, monitor, and improve AI voice agents with simulations and call analytics.
doola is an AI assistant that automates back-office tasks for e-commerce entrepreneurs.
The venture capital industry is full of sheep. Funds blindly follow others without thinking for themselves. They lack all conviction. As a result, they don't blaze new trails - and blazing new trails is the only way to earn outsized returns in a hyper-competitive market as an investor or an operator.
Most startups eventually fail. This is rarely because of competition. Most of the time, their demise is self-inflicted by internal issues. The biggest threats usually come from within the company's own walls, not from the outside world.
Leadership can't fake that they care because people can feel it.
It turns out the real money in AI isn't going to chatbots or marketing copy - it's almost entirely still going to code.
AI adoption isn't a singular event - it's a staged progression.
SafetyCulture leverages AI agents to optimize marketing by achieving near-100% lead enrichment, doubling opportunity creation, and tripling meeting booking rates.
Stablecoins change the economics of building financial products and make specialization possible.
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Surprise parties can be fun. But surprisingly high internet bills? Not so much.
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Jason Freedman has read 8,000 YC applications. They went back and tested which questions actually predicted success by checking if they would have disqualified the biggest outcomes. What predicted success by a mile was determination. So predictive that YC took it and found five different ways to ask it.
Startups in 2026 will focus on transforming unstructured multimodal data into structured formats, automating cybersecurity tasks to close hiring gaps, and developing agent-native infrastructures for AI workloads. AI will also enhance creative tools for seamless storytelling across media, redefine data stacks with AI-native features, and push traditional systems of record into the background in favor of dynamic agent-led execution environments. Vertical AI will evolve into multi-party collaborations, agents will prioritize machine legibility over human interface design, and personalized experiences will become the norm, culminating in AI-native universities and interactive storytelling worlds.
You've got an idea, and you're convinced it's great. You want to start building right now. This is how founders waste months on things nobody wants. PostHog's founders pivoted five times, and most of those ideas never made it past a single conversation. The trap is asking people if they like your idea - they'll say yes just to make you go away. Instead, find out if they've actually had the problem and tried to solve it themselves. If they built some crappy internal system to deal with it, there's probably a business there. If it's not a hair-on-fire problem for them, move on.
Make help requests specific, finite, and actionable to increase the chances of receiving assistance. Requests should clearly define the commitment, showing preparation and ensuring the help will be impactful. Avoid open-ended asks and demonstrate you have taken steps on your own, and value the helper's input.
Why do brilliant teams often plateau at $20M ARR? It isn't a lack of effort—it's usually a lack of Single-Threaded Ownership. If two people own a goal, no one does. This guide details how to build performance infrastructure: hire for "capacity" (driving initiatives start-to-finish), define specific actions that violate your values (like saying "that's not my job"), and ensure every objective has exactly one owner so performance is always visible.
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Your startup needs every advantage it can get - and that means not paying $150K for roles you can offshore. Justworks is making global expansion easier than ever with this exclusive offer [11]: HIRE INTERNATIONAL CONTRACTORS AT NO EXTRA COST until 2027. Sign up with
Personalize your website to every visitor.
Make your existing CRM autonomous.
Atonomo finds one high-impact conversion optimization each week. They watch session replays, analyze funnels, and prioritize by KPI.
It's normal to feel lonely, scared, or overwhelmed when in the operator seat. You need to build infrastructure around yourself, not just the company. Start building a support structure, and everything will start to feel a little less heavy. Finding support and letting yourself use it is part of the job now.
AI has opened up the potential for real innovation, but founders are still building specialist AI products as if they were building the same subscription software tools of the last decade. Specialization will eventually lose out to simpler systems with more compute and more training data. The businesses that will define this era will be the companies that build what models need to get better, or companies that discover work that's only possible because of AI.
Using humans to ask basic questions that AI could answer in seconds isn't diligence in 2025.
The startup world has a sameness problem.
Stripe offered to acquire Airwallex for $1.2 billion when it had $2M in revenue, but the offer was rejected.
AI expands what is possible for companies and opens the door to categories that were previously out of reach.
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B2B lead gen tool providing contact info (emails, buy intent, etc.) for 1.3 billion decision makers.
Long-term relevance in an AI-dominated world comes from learning to make strong decisions under uncertainty rather than mastering any single technical field. Being right, which centers on ego and rigid beliefs, is different from getting it right, which requires curiosity, updating views, and detaching identity from ideas. Leaders who prioritize getting it right foster open debate, psychological safety, and faster progress. Ego-driven cultures slow teams and limit contribution.
Valuations have grown faster than fundamentals, and corporate balance sheets are unusually strong. Antitrust risk is about to rise, so selling before this shift is rational. Acquirers are overlooking unhealthy financials because they fear missing out on AI or automation. IPO markets may reopen, but most major private companies are still staying away from going public.
The most valuable asset in every organization is the hard-won, implicit knowledge inside the heads of its best people. Chatbots fail because they produce generic AI that averages out expertise into blandness. The only way to capture true expertise is to build an AI interviewer that earns the trust to be seen as a peer. This article discusses how 99ravens cleared this technical hurdle.
a16z General Partner Anish Acharya recently appeared on a podcast to discuss the speed/emergent properties of this product cycle, founder psychology in a period of intense competition, unbundling tasks from jobs, and AI native networks. a16z's core thesis is that founders make the best long-term CEOs. They have unique knowledge and networks - a16z builds its structure to provide these resources to founders indefinitely. A link to the full podcast, along with notes from the discussion, is available in the post.
The velocity of work changes instantly when we give agents the right tools. Businesses can now use agents to complete tasks, just like software engineers have been doing for the last several months. It is now possible to spin up multiple parallel workstreams, multiplying daily output without working longer hours. The agent inflection point is already here.