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For founders in markets where one sale hangs on permits, regulators, suppliers, or several companies agreeing on timing.
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For founders in markets where one sale hangs on permits, regulators, suppliers, or several companies agreeing on timing.
Teams experience "generated demand" when completing work reveals previously suppressed requests, leading them back to being overwhelmed despite progress.
AI agent work should live in private notes, drafts, and cheap experiments stay on the laptop, and once it's useful to someone else, work moves to shared docs, repos, or company memory.
Imagine an AI claims assistant watching every override an insurer makes. It does not just learn policy text. It learns when the company bends the rule for a broker, when a fraud pattern gets escalated, which underwriter gets trusted, and which ugly edge cases become paid claims. That is the enterprise AI value-capture problem here. The most sensitive company knowledge may live in exception logs and decision traces, not PDFs. For founders selling AI into serious workflows, customer-owned memory, audit trails, and training controls are not compliance garnish.
Brands used to brief a campaign, buy distribution, and control the message. This piece is about what happens when that center breaks. Creators are becoming the people who make the format, hold the audience habit, and decide how a product enters culture. That is different from an influencer post. An influencer rents attention for a launch. A creator can make the product part of a recurring world people already follow.
Emails need to be clear so readers can understand the point in seconds, decide quickly, and forward the message without extra explanation. A good email makes the reader understand the point fast without trying to sound smart, warm, or impressive. Don't use emails for long back-and-forths - call or chat when speed matters more than recordkeeping, then send a short email summary with the decision. Make the next step obvious, so the receiver knows what to do.
Preferential attachment shows that initial advantages can snowball into significant success, as seen in sports and social media. Early momentum and visibility are crucial to becoming a top contender, often outweighing pure quality. Focusing efforts on what's working can lead to outsized returns, reinforcing the importance of being number one.
Ship OS is a ready-to-use setup for running product development from end to end in Notion. It provides configurations for everything - developers just have to connect the custom agents that power the workflow. Ship OS makes Notion a shared workspace where all agents can work together. Examples of templates from companies building at scale are available.
ChatGPT Work brings together context from teams' tools to turn scattered notes, drafts, and ideas into finished work. It is available on all plans on desktop and is rolling out to Plus, Pro, Business, Enterprise, and Edu on web and mobile over the next few days. Powered by GPT-5.6, ChatGPT Work can help teams accomplish more. More information about the tool, along with examples of use cases, is available in the article.
Mercury has kept its company culture strong as it scaled by following four high-level ideas. Be weird: the core of a strong company culture is how authentic and real everyone is. Keep doing things that scale. Be very careful with hiring executives and leaders because culture is a very top-down phenomenon. Embed company culture into processes to organically help perpetuate the culture.
Gamma is at $100 million ARR, 50 million users, and 600,000 paying subscribers after five years. The team only has 50 people, and the company is profitable. This was achieved with zero sales or marketing spend. Growth came from word of mouth. This post details how the company did it.
Successful founder content follows six repeatable formats built from authentic company data, failures, and product-building progress.
If AI can make thirty versions by lunch, taste becomes the bottleneck.
Iconic companies emerge by relentlessly controlling the customer experience, building products people emotionally connect with, and thinking decades ahead.
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The Task Economy is the defining market for the future of AI. The barrier to automating every task with agents is covering the full distribution of all of the apps, all of the environments, and all of the tasks that correspond to everything in the economy. This will require a massive data build-out across every professional domain, academic discipline, and consumer use case. Labs, AI app companies, and enterprises will all fight to rapidly scale this data infrastructure across the full surface area of economically useful work. The ones that succeed will continue to improve frontier capabilities and gain market share.
AI companies have committed $9.75 billion in 12 months to forward-deployed engineering. The FDE role is now an industry default rather than a Palantir signature. FDE investment is a moat as retraining on a competitor's stack is friction no manager wants.
The founder who sold Vungle to Blackstone for $780M explains why his second-time playbook is a tax, after watching Blazel's token bill pass $70K in a single month and its AI-agency business race toward an easy but fatal $10M ARR. He kept the agency just long enough to harvest labeled human edits, fine-tuned a model on them, and pivoted to a platform before the cultural switching cost made the pivot impossible. The expensive lesson underneath it comes from Vungle serving two markets at once while AppLovin picked one, and today Vungle is worth $4B against AppLovin's $150-250B.
Agent AI adoption is changing how Uber builds. 99% of the company's engineers use AI tools. More than 70% of pull requests are attributed to agents. The biggest lesson that the company has learned is that the best AI opportunities are discovered by sitting next to the people doing the work, understanding every friction point, and building with them, not for them.
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Google is adding support for capabilities in Managed Agents in Gemini API like background execution for async interactions, easy connection to remote MCP servers, custom functions, and credential refresh. The new capabilities will enable developers to build autonomous agents with expanded capabilities. They turn managed agents into asynchronous workers that operate inside real development environments without blocking applications.
Claude Cowork is now available on web and mobile as well as desktop. Cowork runs sessions remotely so users can access their sessions and files wherever they are, on any device. It is still in beta on web and mobile. The feature will roll out over the next several weeks, starting with the Max plan.
Top AI companies are ramping up discounts in a desperate bid to win business. Founders across Silicon Valley are enjoying a wave of computing credits and are fielding competing offers from AI-model makers racing to land new enterprise customers. These offers have enabled some startup founders to raise later. Companies participating in Y Combinator are being especially targeted with offers.
Startups built around AI hire fewer entry-level workers than their peers. They are leaner, flatter, and heavily weighted towards senior technical talent. Their workers are especially likely to be graduates from elite institutions. AI seems to be concentrating rather than democratizing opportunity.
The world is short on people who can find the right problem, tell whether the machine solved it, and finish past where the machine stopped.
Google Search Console now supports a new property type that can track traffic from Search that goes to individual social accounts.
Software spend is accelerating. However, valuations are collapsing for many software leaders. The software market has split in two: one group is tapping AI budgets and accelerating, and the other is running the same playbook from 18 months ago. This post breaks down where the line between these two groups falls and what moves a company from one side to the other.
53% of finance-room executives name proving ROI as the main blocker to further AI spend, 62% expect measurable return within six months, and 17% already fund AI partly from money that would have gone to headcount. Founders in the same network price 50% on usage and 18% on outcomes against 25% on seats, but they still sell through CIOs and business units while the CEO signs and finance carries the proof burden, which is where deals stall. If your product needs eighteen months to show value, you're selling to a buyer who wants evidence in six.
Near-peers are people so good that the founder would be fine reporting to them if the roles were reversed. Their strengths perfectly complement the founder's strengths. Near-peers turn the founder's vision into daily operating decisions. This lets the founder focus on what only the founder can do, while the near-peer handles the rest.
Segmenting churn into categories allows founders to separate different churn problems and solve them individually. Keeping big customers happy is different to keeping small businesses from seeking a cheaper tool. Instead of excluding trials and POCs, segment them out and figure out how to convert better. Also, segment NPS and CSAT per segment - double down on the happiest segments and the segments growing the fastest.
Churn depends on your category. Not all churn is bad. However, some types can kill your business. Once you know your sticky ideal customer profile, the product job becomes to build for them ruthlessly. Free plans activate, and paywalls monetize. Negative churn is the Holy Grail.
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Claude Fable 5 can take on problems that were previously too complex, long-running, or ambiguous. It is particularly effective at end-to-end work that takes a person hours, days, or weeks to complete. Claude Fable 5 has several behavior differences from Claude Opus 4.8 that may require prompt or scaffolding updates. This guide covers promising and scaffolding patterns specific to Claude Fable 5 and Claude Mythos 5.
They Got Acquired's curated list of founders writing about their own exits on personal blogs.
Successful creator businesses often evolve from selling content to selling access to the creator's judgment and expertise. Structure access through content, workshops, communities, and premium advisory services rather than offering unlimited founder availability. Founders who want to build a sellable company must gradually shift trust from themselves to the team, brand, and systems.
Churn models ship with a default 0.5 threshold. This analysis prices that default at about $86 per customer in avoidable spend, $8.6M across a 100K-subscriber base. Missing a churner costs about 13x more than over-treating a loyal customer, so the profitable threshold sits well below 0.5 and the default is quietly setting your retention budget. Library defaults across an analytics stack are business decisions nobody consciously made.
Understanding human nature is the highest-leverage skill in an AI-driven world because attention, persuasion, trust, and value creation ultimately depend on people, not technology.
Entrepreneurs mistakenly believe a great product will sell itself without active sales and marketing efforts.
AI has shifted outbound from list-blasting to structured, multi-channel campaigns that combine agents for scale and humans for high-value relationships.
Token prices fell from $60 per million to $0.60 in three years, and AI bills still exploded. A four-person startup ran up a $113,000 monthly bill from a single provider. Uber torched its entire 2026 AI budget in four months. Consumption is the reason. An agent re-reads context and checks its own work, burning 60 to 140 times the tokens of one reply. Track cost per completed task, not per seat, and keep the model layer swappable, because cheaper tokens do not mean a cheaper bill.
Software architecture determines how software behaves. The engineering operating model determines how engineering behaves. Engineering organizations exist to create customer and business value through software. This means the job of engineering leadership is to maximize the value engineering teams create. Redesign the system around the work so that engineers' work matters more.
Salesforce shipped Agentforce, the fastest-growing product in its history, and scaled it to $1.2B in ARR. The stock hit a 52-week low anyway. That paradox is the whole shift. When anyone can rebuild your headline feature in a weekend, the software surface stops being a moat, and value rotates to what you can't clone, the proprietary data loops, the right to move money or push code, and being the tool an agent chooses to call. Outcome pricing seals it, turning vendors into insurers who underwrite every result instead of billing for seats. So what do you own that stays scarce once building is free?
Notion now lets users build interactive HTML right on their Notion pages. AI can turn content into interactive explainers, prototypes, or diagrams. The agent can take documents, sketch a flow, and build a lightweight prototype on the page. Video demos are available in the thread.
This GitHub gist contains a skill that transforms AI into the middle manager for an autonomous software factory. The agent doesn't write code or implement any issues. Instead, it reads the issue tracker, creates and manages Devin coding sessions, and informs the human operator only when it needs to.
All good communication is grounded in an understanding of the receiver's mind. Help is about people before it is about projects. Make it clear that you are someone who is worth helping by demonstrating that you are a serious person through personal connection or by having institutional credibility. Never lie.