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Cognition's approach to scaling agent tasks, using Agentic MapReduce, enables parallel processing of security findings by sharding codebases, verifying vulnerabilities, and using Git for communication and fault tolerance.
The differences in how iPhones and Nothing Phones handle image rotation shows the importance of designing user interfaces that accommodate situational disabilities and improve usability by preventing unnecessary wait times for animations.
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.
Digital publishers are getting squeezed from both sides. Meta is prioritizing creator content over publisher links, cutting ad revenue, while Google's AI Overviews reduce search traffic by answering queries directly. Some publishers report CTR drops as high as 89%. Search traffic is projected to fall over 40% in three years, after steep declines from Facebook and X. A new UK ruling allows publishers to block Overviews without losing search rankings, adding leverage.
AI hype is sweeping advertising, expectations are overblown. Fully automated ad creation isn't realistic and risks hurting the ecosystem. Like programmatic before it, AI won't replace human judgment. Its real value is improving productivity and workflows. Meanwhile, creators are becoming full-stack businesses, blurring lines with agencies. The industry is shifting toward data-driven marketing, but AI alone won't deliver the transformation many expect.
Placing key customer proof in your website footer can influence how AI systems describe your product. In a test, Clay surfaced its case studies in the footer, and ChatGPT pulled listed customers directly from those links when asked which brands use the product. Companies that bury case studies deeper on their sites were cited far less.
Most loyalty programs fail because they're barely visible. Email flows should surface points, rewards, and status in welcome, post-purchase, and ongoing campaigns. Subscription flows should reinforce value with milestone updates and highlight what's lost during cancellation. Landing pages should surface perks upfront instead of burying them in footers. Retail experiences should connect online and in-store so that earning and redemption work both ways.
Use Google Ads audience targeting as a filter to reduce invalid clicks when click fraud is hurting your campaign performance. One account cut its invalid click rate by 50% after adding hundreds of Google predefined audiences and setting them to Targeting instead of Observation. The approach limits ads to users who match both keywords and Google's audience signals. It works best for accounts with unusually high invalid click rates because it can also exclude legitimate users who do not fit Google's predefined audiences.
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ContentGrapher provides website content recommendations for AI visibility. You give it a URL, and it maps weak or missing concepts, how well you've connected certain concepts, and if there's anything that belongs on its own page. It's free for the first 5 analyses, then starts at $29.
Success is framed as a function of what tradeoffs can be sustained, not just strengths or effort. Kristen Lowe introduces “success currencies”, highlighting costs like risk, rejection, and uncertainty as key drivers of achievement. The session includes a self-assessment to identify which costs drain or motivate, and whether current ambitions align with the prices required to reach them. It will take place on July 8 at 9 AM PT.
Google's new system targets coordinated AI content, not individual pages. It detects clusters of accounts producing templated content at scale using shared infrastructure, velocity, and semantic patterns, then removes the entire network. This shifts enforcement from optimizing single pages to avoiding detectable production patterns. High-volume, templated strategies are now a liability.
A 6-step framework to investigate and explain a metric drop.
MrBeast leads the ranking, followed by Dhar Mann and Steven Bartlett.
One test replacing all-caps headlines with standard capitalization increased conversions by 25%, highlighting the impact of readability.
Soccer wins on community, accessibility, and global identity over traditional violence-heavy sports.
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The Model Y Long Wheelbase is now available in the US and Puerto Rico. The 3-row, 6-seat configuration has ample headroom and legroom for all passengers. The trunk fits a 28" and a 20" suitcase each, and the frunk can hold an additional 20" suitcase. More details about the wheelbase, along with pictures and videos of the vehicle, are available in the post.
Mark Zuckerberg told staff during an internal town hall on Thursday that the pace of AI agent development was not accelerating in the way executives had previously expected it to. He has apparently commented that the job cuts earlier this year were not as clean as they should have been. The perceived upside of the company's new AI-focused structure has not come to fruition yet. Zuckerberg says that the company will begin to see improvements from its AI investments in the next three to six months.
The US Federal Aviation Administration has proposed a new rule that would allow commercial supersonic airliners as long as they can reduce the ground-level impacts of their sonic booms. The new rule would require any sonic boom overpressure at the surface to be kept below 0.11 pounds per square foot. Critics of the new rule say it doesn't actually consider loudness or annoyance. Legalization of quieter supersonic flights doesn't guarantee a successful comeback for commercial supersonic airliners - Concorde's massive fuel consumption made it difficult to sustain profitable operations.
Quants' assets under management in China have more than doubled in less than a year to over 2.6 trillion yuan. The trend is being fueled by the rapid adoption of artificial intelligence. Quants' breadth in covering thousands of stocks has made it mainstream. Funds are responding to the frenzy by creating new investment products.
It's still important to understand the code that agents write. Agent work needs to be understood to verify that it is correct. This understanding is required for humans to participate in the creative process. This presentation discusses techniques for building human understanding when working with AI and moving fast.
'Junior' is an AI intern in Slack. Users can give it information to work with, review the work, and steer the agent in the right direction. This article discusses the process of developing Junior, which took over four months. The full source for the project is available.
After years of trying to diversify, Meta is still almost entirely an ad business. The company's latest solution to that problem is AI. AI will be used to supercharge its ads business, but it will also ideally unlock other businesses. One of these businesses is Meta's newly announced cloud service.
The valuable work of the next decade is everything that can't be graded within the span of model training. Focus on resources that are truly limited and learn to find problems in addition to solving them. Work on the most ambitious form of a problem and learn to execute well in the last mile. Put yourself in the right position to see opportunities. The key to unlocking opportunity is to focus on finding interesting problems and delivering extraordinary results.
Intelligent routing is becoming table stakes.
The Microsoft Frontier Company will embed engineers inside customers to build and run AI systems.
Agents need domain knowledge, context, and carefully defined ways for humans to steer the result.
Anthropic has yet to decide what the chip will be used for, how it will fit into the server, or how powerful it will be.
AI crawlers have until September to separate bots that gather content for search from those that harvest it for training or be blocked on pages that carry ads.
The cap is a sign that even companies betting their future on AI are struggling to control their costs.
Meta's superintelligence chief, Alexandr Wang, says that the company's upcoming model has caught up with OpenAI's GPT-5.5 on closely followed AI benchmarks. Codenamed Watermelon, the model is still in training. The model reportedly uses an order of magnitude more compute than Muse Spark. Meta has not given a timeline for Watermelon.
Anthropic reportedly discussed a custom AI chip collaboration with Samsung as it looked to diversify its compute stack. The company said chips from Google, Amazon, and Nvidia remained central to its hardware strategy.
Many folks claim to be able to use AI to do the work of dozens of people. This researcher used autoresearch to work on a problem where the path from unknown to success is a clear, gradient optimization. The researcher found the auto-research/loop style of work makes sense for problems with a robust, measurable, and well-constrained metric to optimize. However, finding a problem with these factors is often tricky.