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YOU DON'T NEED MORE CONTENT
The internet is overrun with sloppy AI-generated copy. Piling on more is a losing strategy. But what if you could use AI to make your content better, rather than just churn out more of it?
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Sponsored
The internet is overrun with sloppy AI-generated copy. Piling on more is a losing strategy. But what if you could use AI to make your content better, rather than just churn out more of it?
The UK's planned under-16 social media ban could force millions of adults to verify their identity just to access major platforms, changing how the internet is used for everyone, not just kids. In Australia, where a similar ban took effect in December 2025, 7 in 10 under-16s who already had accounts still retain some access, raising doubts about how enforceable these rules are. The tradeoff is child protection versus increased data collection, since age verification gives more personal information to the same platforms it aims to restrict.
Selling AI as a replacement for people grabs attention but erodes trust with buyers and employees. The data doesn't support the narrative. In one month, 160 companies laid off 28.3K workers, and not a single one cited AI as the reason. Yale researchers also found no measurable job loss from AI across 33 months of labor data. Instead, AI works best as an augment. Top users complete 12.2% more tasks and work 25.1% faster when they know its limits. Companies pushing replacement messaging are already reversing course after quality drops and backlash.
There are two kinds of experimenters, one optimizing for scientific certainty and one optimizing for business speed. Strict significance rules like p < 0.05 are designed to avoid false positives, but large-scale studies show they can leave over a quarter of value on the table and sometimes underperform doing nothing. The real issue is decision-making, not testing, since teams stall debating results instead of acting. A better approach is to define intent upfront, either proving superiority or checking non-inferiority, and tune thresholds to the real cost of being wrong.
Most social reports stop at sentiment scores and miss the signal in the comments. Go deeper than positive or negative to see what people are actually reacting to. Look for repeated themes across threads, not one-off opinions. Turn those insights into clear stakeholder talking points backed by real comments. Feed audience language directly into campaign briefs so messaging matches how people already talk.
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Ads get ignored on social media but not in TLDR! Reach developers, PMs, marketers, founders and other tech leaders where they actually
HyperFrames is a free open-source tool that turns HTML into product launch videos. It includes a website-to-video skill for Codex or Claude Code, which takes a website address and outputs a 30-second promo video. The tool pulls from the site's screenshots, assets, copy, and brand look.
This webinar, on June 25 at 2 PM ET, will break down what makes email subject lines perform. It will move past guesswork and into data, showing what drives opens and how real campaigns compare against common instincts. It includes a live subject line showdown and practical fixes to improve results before hitting send.
New out-of-network reach tracking shows which posts actually grow audiences beyond followers. Search now supports natural language for faster ICP discovery. Video returns in a dedicated feed, signaling a stronger push for short-form content. Advice Sessions enables paid 1:1 calls, while Creator Marketplace connects brands with vetted creators for campaigns. Mobile boosting lets users promote posts directly from the app. AI-generated spam is being deprioritized in favor of original POV content. Comments now convert to follows instantly. Connected apps add verified tool usage to profiles as proof of real skills.
We're hiring a senior PMM to own product marketing at TLDR. You'll define our positioning, build out sales enablement, and lead every launch. Learn more [16].
LLMs are probabilistic systems that generate likely answers based on patterns, which makes them fluent but not always correct. They can confidently produce wrong outputs because they don't retrieve truth, they predict it. That works for writing, brainstorming, and conversation, but breaks in high-stakes use cases. Deterministic systems fix consistency but still need verification to ensure correctness. The emerging direction is hybrid models where LLMs generate and formal systems verify. As AI moves into areas like biotech and cyber, “probably right” is no longer enough.
B2B teams treat employee advocacy and influencer marketing as interchangeable, but they do different jobs and work best together. Advocacy builds trust through employee networks that are 10X larger than brand pages and drives 45% more opportunities and 51% higher quota attainment with minimal cost. Influencer marketing buys fast access to new audiences but requires ongoing spend and fades when campaigns stop. The strongest programs run both in parallel, using influencers for reach and employees for credibility, aligned to the same launch so buyers see consistent signals from inside and outside the company.
Confidence scoring in frameworks like RICE looks precise but breaks in practice. It assumes uncertainty can be modeled as probability, but most product work sits in true uncertainty where confidence is not measurable or reliably calibrated. This skews decisions toward safe, small work and away from high-upside bets. It's better to drop confidence and focus on real usage, strong customer pull, fast feedback, and observed behavior. Favor asymmetric bets and keep optionality as reality unfolds.
Mastercard cut 70% of its ad spend, moved budget into experiences, and still grew brand value and performance.
The NBA players' union launched Plyrs Untd, giving athletes direct ownership over how their names, images, and likenesses appear across content and partnerships.
Instacart is piloting a vertical video feed with 5-30 second recipe clips that lets users discover meals and shop ingredients instantly in-app.