Whoa, delisted Xbox 360 games just showed up on the Xbox Store β did Microsoft leak new Xbox Backwards Compatibility games?
Betvisors connects bettors with verified sports betting advisors and lets you tail their picks with one tap. You only tip when a pick wins; if it loses, you pay nothing. Advisors prove their track records with betslip screenshots, and a public leaderboard shows win rate, profit, and streaks. Gambly integration places bets at your sportsbook instantly, while Stripe handles secure payments. Advisors can monetize winning picks and grow a following on the platform.
Geysera helps ecommerce brands recover revenue by identifying returning anonymous visitors and syncing them to your ESP. It builds and manages cart, checkout, browse, and winback email flows inside Klaviyo, Mailchimp, or SendGrid, then optimizes continuously within your discount guardrails. Always-on holdout groups and RCTs prove incremental lift, and pricing ties to verified revenue. Brands and agencies get white-glove setup, real-time dashboards, and compliance-aware copy.
An Ipsos survey of U.S. adults found 63% say ads in AI search results would reduce trust. Early advertiser data offers limited, mixed signals.
The post Trust In AI Search Could Drop With Ads, Survey Shows appeared first on Search Engine Journal.

If you rank your own product #1 in βbest ofβ listicles, itβs not just a search-quality issue β it may violate FTC rules that took effect in October 2024.
Driving the news. As Lily Ray noted on LinkedIn, the FTCβs Consumer Review Rule (16 CFR Part 465) prohibits several deceptive practices tied to reviews and testimonials, including:
Penalties can reach up to $53,088 per violation, and each page may count separately. Ray also shared a reference table she generated with the help of Claude:

Why now. βBest Xβ and βTop 10 Yβ listicles have surged as a GEO tactic over the past couple of years. These pages often perform well in search and increasingly influence AI-generated answers.
The backstory. Before the rule was formalized, Ray said at least one company faced legal action for publishing hundreds of βbest ofβ pages that:
The Better Business Bureau later censured the company for unsubstantiated claims.
Whatβs happening. Many modern listicles follow a similar pattern:
These listicles may imply independence or firsthand evaluation when neither exists.
The nuance. You can publish comparison content that includes your own product. However, based on FTC guidance, risk increases when:
What Google is saying. Google is aware of the low-quality listicle trend. In a statement to The Verge, a Google spokesperson said the company applies protections against manipulation in Search and Gemini, and reiterated its guidance: create content for people and ensure itβs understandable to search systems.
Why we care. What has worked as a visibility tactic may carry risk on two fronts β regulators and a potential Google Search algorithm change. That means this popular GEO tactic could decline quickly as its effectiveness drops.
Caveat. Iβm not a lawyer. Consult your own legal counsel if youβre concerned about using this tactic.
Intel preps a huge socket for future CPUs with HUGE graphics chips Intel is reportedly working on a new CPU that aims to challenge AMDβs βStrix Haloβ and Apple Silicon. With its huge 4326 socket, Razor Lake AX aims to bring together strong CPU and GPU hardware to deliver a strong single-package computing solution for [β¦]
The post Intel Razor Lake-AX to challenge Apple Silicon appeared first on OC3D.

co-parenting.ai is the AI family app for separated parents β an assistant that communicates and coordinates the logistics, a place for family context, a village hub for grandparents, nannies, and schools, and a dedicated space for kids that shields them from adult conflict. It works whether your co-parent joins or not. We built this for the kids. Every conflict de-escalated means two present parents instead of two stressed ones. Every caregiver and extended family member who shows up knowing the schedule is a child who feels held by a bigger family.

Human-written content dominates Googleβs top rankings, appearing in the No. 1 position 80% of the time versus just 9% for purely AI-generated pages, based on a Semrush analysis of 42,000 blog posts.
The details. Semrush analyzed 20,000 keywords and their top 10 results, classifying content with an AI detector.
Yes, but. AI detection tools are widely known to be inconsistent and can misclassify human and AI-written content, creating some possible βfuzzinessβ in these classifications.
Why we care. AI-generated content works, until it doesnβt. Yes, AI can help you rank, but this data suggests human insight still drives the best performance. For competitive queries, originality, expertise, and editorial judgment remain your unfair advantages.
Perception vs. data. 72% of SEOs said AI content performs as well as or better than human content, yet ranking data showed a clear human advantage at the top.
How teams use AI. No surprise, AI is widely adopted and often used in a hybrid approach:
Whatβs driving adoption. AI accelerates output, but doesnβt reliably improve it.
About the data: The analysis examined 42,000 blog pages from 200,000 URLs tied to 20,000 keywords, using GPTZero to classify content. It also includes a survey of 224 SEO professionals working in content and search.
The study. Does AI content rank well in search? [Survey + Data study]

MetricSign monitors your Power BI datasets every five minutes and tells you when something breaks, such as a failed refresh, a missing column, or a changed schedule. Each alert includes the exact error, what caused it, and a direct link to fix it in Power BI. It works with ADF, Fabric Pipelines, and Databricks too, so you can see the full chain from source to dashboard. Setup takes two minutes: sign in with Microsoft, pick your workspaces, and you're done.
LLM Pulse helps companies understand how they appear in AI search and how to improve it. We track brand presence across leading LLMs like ChatGPT, Google AI Mode, Gemini, and Perplexity, analyzing prompts, responses, citations, and sentiment. Rather than relying on abstract scores, LLM Pulse shows the actual answers users see, making it easy to spot gaps, understand competitors, and take action through content and technical improvements. Designed for marketing, SEO, and growth teams, it turns AI visibility into something you can measure, understand, and act on.
AutoScaled generates personalized presentations directly from your CRM and spreadsheet data using a single prompt. Connect HubSpot, Salesforce, Attio, or your data sheet and specify which records to create tailored presentations for. Upload a template from Google Slides or PowerPoint to build sales decks in seconds.
The AI agent personalizes your content based on your data, maintains brand consistency, and saves you time. You can trigger presentations when CRM data changes, schedule recurring decks, and refresh existing ones with one click. Share content via branded pages, track engagement, and see who viewed what.

In this case study, we went deep instead of broad. We focused on one question: why wasnβt a brand present in a single ChatGPT prompt across ~70 iterations?
We chose one prompt: βWhat are the best hotels in New York City?βΒ
We analyzed mentions, citations, fanouts, and SERPs in Google and Bing. We also planned to analyze GPT memory, but it made no discernible difference to mentions, citations, or fanouts.
We chose NYC hotels because itβs a crowded, mature market with juggernauts and up-and-comers. We also have no connection to the NYC luxury hotel space β we intentionally picked an area where we could stay objective and learn from scratch.
After running the prompt βwhat are the best hotels in New York Cityβ 68 times, we identified which hotels appeared most consistently and which were nearly invisible.
We chose the Baccarat Hotel as our βclientβ because it appeared only once (1.5% of the time), despite strong reviews and clear alignment with the promptβs intent. We wanted to know why β and whether it could change that.
Key findings:
Note: A full methodology breakdown appears in the appendix.
The Baccarat Hotel appeared once in 68 trials (1.5%).
Top performers were large luxury hotels like the Four Seasons Hotel New York Downtown.
ChatGPT also identified boutique hotels as a subcategory, generating a secondary list in its answers. Boutique hotels like the Baccarat are typically smaller and not part of large chains.
Within this boutique subcategory, the Baccarat still underperformed. The Fifth Avenue Hotel, the top-performing boutique property, appeared 13 times, cited 20% of the time, versus the Baccaratβs 1.5%.
We first checked whether anything in the hotelβs history or reputation could explain the gap. As the chart below shows, nothing significant did:
| The BaccaratΒ | The Fifth Avenue | |
| Year Founded | 2015 | 2023 |
| Current Price | $930 | $563 |
| Number of Google Reviews | 1.3k | 213 |
| Google Reviews Rating | 4.6 | 4.6 |
| Number of Expedia Reviews | 531 | 201 |
| Expedia Reviews Rating | 9.4 | 9.6 |
Overall, the Baccarat has been around longer and has more reviews. On quality, the Fifth Avenue Hotel has no edge in Google reviews and only a slight edge in Expedia reviews. The only area where the Baccarat lags is price β but thatβs unlikely the issue when The Ritz-Carlton, a consistent non-boutique winner, is listed at $1,100.
Further reinforcing the Fifth Avenueβs underdog status: one of its most prominent Google results (rank 2) was a Wikipedia page for a different Fifth Avenue Hotel that closed in 1908, creating potential entity confusion similar to the two Danny Goodwins.
If the Fifth Avenue Hotel had been the one missing, it would suggest a less established brand with entity confusion. But the opposite happened β it prevailed in ChatGPT.
So what was the problem for the Baccarat Hotel?
When ChatGPT performs a web search, it sends a series of queries you can extract via Chrome DevTools. In this case study, examples included:
In total, we extracted 25 unique query fanouts.
If we only looked at the articles dominating fanout SERPs in Google, weβd expect the Baccarat to narrowly outperform the Fifth Avenue in ChatGPT. That didnβt happen.
In the table below, the Baccarat βwinsβ three of the top 10 most frequently appearing pages, while the Fifth Avenue Hotel βwinsβ two. The other five feature neither. A βwinβ means one of the following:
The data:
| URL | Who Wins? | Notes |
| https://www.forbestravelguide.com/destinations/new-york-city-new-york | The Baccarat | The Baccarat Hotel is #4 on the list, the Fifth Avenue Hotel is #13 and sits far below the fold |
| https://www.mrandmrssmith.com/destinations/new-york-state/new-york/hotels | Neither | Neither Hotel appears on this list |
| https://guide.michelin.com/us/en/article/travel/the-best-hotels-in-new-york-all-the-michelin-key-hotels-in-the-city | The Fifth Avenue | The Baccarat is listed as a βone keyβ hotel, placing it at the bottom of the list. The Fifth Avenue HotelΒ is listed as a βtwo keyβ hotel, placing it in the middle of the list. |
| https://youshouldgohere.com/2025/01/best-boutique-hotels-new-york-city/ | Neither | Neither Hotel appears on this list |
| https://travel.usnews.com/hotels/new_york_ny/ | The Baccarat | The Baccarat #11 on the list, the Fifth Avenue Hotel #16 |
| https://luxlifelondon.com/best-hotels-manhattan-new-york-city/ | Neither | Neither appears on this list |
| https://www.tripadvisor.com/Hotels-g60763-New_York_City_New_York-Hotels.html | Neither | Neither Hotel appears on this list |
| https://www.lartisien.com/hotels/united-states/new-york | The Baccarat | The Baccarat is #5, the Fifth Avenue is #15 |
| https://www.cntraveler.com/gallery/readers-choice-awards-new-york-city-hotels | Neither | Neither Hotel appears on this list |
| https://www.reddit.com/r/chubbytravel/comments/1n7jro1/which_luxe_hotels_are_people_loving_in_new_york/ | The Fifth Avenue | Both mentioned, but the Fifth Avenue much more positively |
By contrast, looking only at the articles dominating fanout SERPs in Bing, weβd expect the Fifth Avenue to outperform the Baccarat in ChatGPT β and it did.
In the table below, the Fifth Avenue βwinsβ five of the eight most frequently appearing URLs.
Note: The table includes two fewer URLs because Bing SERPs were slightly less diverse for these fanouts.
The data:
| URL | Who Wins? | Notes |
| https://www.forbes.com/sites/forbes-personal-shopper/article/best-hotels-in-new-york-city/ | Neither | Neither appears on this list |
| https://www.timeout.com/newyork/hotels/best-luxury-hotels-in-nyc | The Fifth Avenue | The Fifth Avenue is #1, The Baccarat is #16 |
| https://robbreport.com/travel/hotels/lists/best-luxury-hotels-new-york-city-1237348563/ | The Fifth Avenue | The Fifth Avenue is #5 (but also wins the hero image/caption), the Baccarat is #11 |
| https://www.cntraveler.com/story/best-boutique-hotels-nyc | The Fifth Avenue | The Fifth Avenue appears, the Baccarat does not |
| https://www.travelandleisure.com/best-hotels-in-new-york-city-8612778 | The Baccarat | The Baccarat appears, the Fifth Avenue does not |
| https://www.tripadvisor.com/Hotels-g60763-zff12-New_York_City_New_York-Hotels.html | The Fifth Avenue | The Fifth Avenue appears, the Baccarat does not |
| https://www.cntraveler.com/gallery/best-hotels-in-new-york-city | The Fifth Avenue | Both are listed, but the Fifth Avenue is listed under βOur Top Picksβ |
| https://travel.usnews.com/hotels/new_york_ny/ | The Baccarat | The Baccarat is #11 on the list, the Fifth Avenue is #16 |
Bing rank strongly predicts ChatGPT citations β 87% align with Bingβs top results, Seer Interactive found. Our case study supports this and extends it.
We examined the relationship between fanouts (Seer focused on prompts) and brand mentions.
Example mention: βFor a luxury boutique feel: listings like The Fifth Avenue Hotel or Crosby Street Hotel consistently make βtop NYCβ lists from travel editors.β
Mentions are often more valuable than citations. Most people wonβt follow citations but will remember the top recommendation.
Thereβs ongoing debate about whether fanouts shape ChatGPTβs answers and mentions, or simply support answers generated from training data. For example, Leigh McKenzie argued on LinkedIn:
By contrast, our data aligns with Beehiivβs research, which suggests citations do shape mentions.
Training data doesnβt appear to be the issue for the Baccarat. Compared to the Fifth Avenue, itβs older, has more reviews, and holds similarly high ratings across major platforms. What it lacks is strong presence in Bing results for fanouts and citations, which appears to lead to fewer mentions.
A simple flow might look like this:
In this vertical, third parties like Forbes and CondΓ© Nast control the space. Visibility depends on who mentions you, so you need a strong outreach strategy β not just updates to your own content.
Our data shows that βtargeting Forbesβ isnβt specific enough.
The top result surfaced in both Bing and ChatGPT was the same Forbes article. In Google, the most frequent fanout result was also a Forbes article β but a different one.
As weβve seen, getting into Googleβs Forbes article likely wouldnβt provide a meaningful boost. The Baccarat βwonβ in that piece.
Getting into Bingβs Forbes article, where the Baccarat wasnβt mentioned, could make all the difference. This requires a highly surgical approach grounded in Bing data.
Generalities wonβt work; detail reigns supreme.
Model: We prompted GPT-5.2 Instant and manually extracted results. We didnβt use APIs within ChatGPT.
Number of iterations: We ran the same prompt 68 times.
Prompt: βWhat are the best hotels in New York City?β
Settings: We tested three memory states:
For all trials, we turned off βreference chat historyβ to avoid interference across iterations.
We expected differences based on memory settings but found none, so we treated all trials as a single dataset.
What we extracted:

Is it possible to get an accurate view of the current state of SEO?
There have been multiple attempts to reach consensus on what works, predict what might be coming, and identify the factors that may play a role in βgoodβ (or βbadβ) SEO.
As useful and productive as some of this may be, none of it offers the same grounded data as the Web Almanac, a project I was honored to be a part of. With the publication of the 2025 SEO chapter, we can now review the data and spot the emerging trends from 2025 and what that could mean for SEO in 2026.
2025 has been another year of increasingly higher SEO standards β which can only be a good thing:
Not all of these statistics represent rapid change, but they do show steady and consistent change, at the very least. The 2025 Web Almanac data presents the web as a more secure and easier-to-crawl place, which is certainly a positive.Β
So, can SEOs take a victory lap right now? No, as there is more to do in 2026, even if the basics do feel like theyβre stable or steadily improving.
Content management systems (CMSs) and SEO plugins play a huge role in developing SEO best practices and cementing the βdefaultβ or de facto standards.
As the CMS chapter in the 2025 Web Almanac shows, more and more websites are now powered by a CMS:

Of these, the top five most popular systems over the last four years likely arenβt surprising.

Frequently underpinning many SEO defaults are SEO tools typically utilized by WordPress sites:

Thatβs not to say that using these platforms or tools ensures a perfect website setup. That said, key elements or functions of these tools can become industry standard due to their ubiquity:
Not all of these are on by default. Sometimes they require inputting basic details or simple implementation. Regardless, their ease of access increases the likelihood that they will become an SEO best practice.
This is happening, and itβs proving effective. What this means for 2026 and beyond is that:
Defaults and best practices help, but they donβt finish the job. While attention often shifts to new features, old or forgotten standards still see widespread use.
There have been many different cases where deprecated settings or standards have prominently appeared in the data.
Web changes β no matter how small β are often neither quick nor easy to get done, and weβll likely see traces of deprecated features and settings in the data for years to come.
The improvement in SEO standards doesnβt apply to all features and sites. There are some that arenβt moving in the same direction:
While CMS default settings or configurations can take credit for some of the larger changes, they also bear some of the responsibility for the issues above. For example, median Lighthouse scores for some of the major CMS platforms are still lagging, especially on mobile (while seeing increases over last year).

The long tail of the web is still messy, and this will probably always be the case. The Web Almanac dataset doesnβt exclude websites that are no longer relevant or abandoned.
Site metrics that meet the βtopβ standards from an SEO best practices point of view can likely be achieved with an out-of-the-box site built on any major CMS with a modern theme and 30 mins of carefully considered configuration. This is one of the most significant opportunities in technical SEO.
In 2026, weβll likely:
One of the more eagerly awaited elements of the Web Almanac data was whether we can chart the increasing presence and impact of AI search and crawlers in the decisions of SEOs and developers.
Within the data, we observed two major developments:
Commenting on the state of SEO is challenging because the definition isnβt fixed. Whatβs good or bad practice is often hotly debated, and in the world of AI search, another (painful) metamorphosis is now taking place.
In the HTTP Archive data we can observe the influences working on SEO from a βnuts and boltsβ point of view, report on what we see, and enable people to make up their own minds.
Specifically, one of the elements we added this year was the analysis of the llms.txt file.Β
This is a highly controversial text file, but our inclusion was not an endorsement. Itβs a recognition that changing trends may (or may not) shape the web. Whether itβs effective or accepted, its adoption says something, and we felt it was important to review that.
Itβs clear that robots.txt has a more important job now than ever. Until relatively recently, it was largely used for targeted control of crawlers, particularly Googlebot and Bingbot.Β
For most SEOs, however, robots.txt was mostly an exercise in both ensuring we werenβt blocking anything by accident and resolving problem areas with Disallow rules. This has changed:
Robots.txt isnβt the only way to manage bots β and arguably isnβt the best β but it introduces a new decision that must be made: How should websites handle LLM crawlbots?
This will be one of the biggest areas weβll see change in on the technical side of 2026:
In 2026, SEOs will be drawn into bot management conversations spanning marketing, technology, and security. βWhich bots should we allow?β is a question with downstream effects on budgets, revenue, and users, and weβll need to closely monitor what develops.
LLMs.txt is an aspiring web standard that aims to guide LLM crawlbot behavior and make it easier for them to retrieve content before generating an answer. Itβs a highly controversial .txt file, and thereβs a vigorous debate on whether it actually benefits LLMs, will gain widespread use, and is a possible vector for manipulation.
The rationale or efficacy of this file isnβt something we need to cover here. For this article, the true point of interest with llms.txt is the adoption of this file as a statement of intent.Β
At the start of 2025, I crawled the Majestic Million, a regularly updated list of the top 1 million websites ranked by backlink authority, in search of llms.txt and found that adoption was extremely low (0.015% of sites, or just 15).Β
While searching one million sites versus 16 million presents some logistical differences, I was expecting a very low level of adoption based on prior experience. I was surprised at how wrong I was.
According to the 2025 data, just over 2% of sites had a valid llms.txt file, and:
This number is still relatively low, but itβs much higher than I thought it would be and potentially represents a huge acceleration.
The primary reason fueling adoption of llms.txtβs SEO plugins that make this easier to enable.Β
We can see that llms.txt adoption has continued to rise ever since we started collecting data from across the web:

If, however, the implementation of this file is actually a default feature in some scenarios, it could be easy to overvalue its significance.
LLMs.txt will still be a barometer of AI search decision-making in 2026:
Another interesting trend worth discussing is the increase in the use of the FAQPage schema.Β
While this isnβt as explicit a trend as robots.txt or llms.txt usage, the increased adoption of this schema type is particularly interesting.
Since Google said it was limiting the appearance of FAQ snippets in search results, youβd be forgiven for thinking the implementation of this schema type might plateau β or even fall.
However, you can see from the last three publications of the Web Almanac that this isnβt the case:

The use of FAQPage schema is now an emerging trend as AI search heavily cites FAQ content in its outputs.
This could be correlation rather than causation, but the steady increase in FAQPage schema is a strong sign of AI search strategies changing the shape of the web.
To echo another conclusion from earlier, 2026 may well see continued growth of structured data types even if they donβt result in an obvious improvement. While the growth is unlikely to be explosive, making a case for their implementation is easier when we donβt just optimize for Google.
Will AI search reshape the web in 2026? Unlikely. Will we continue to see signs of its importance? Almost certainly, but letβs not get carried away.Β
SEO has a reputation for changing quickly. Sometimes thatβs true. More often, itβs the conversation that moves quickly, while the web itself changes at a steadier pace.
The 2025 Web Almanac data clearly reflects that tension. Core SEO hygiene continues to improve year over year, but largely through default features and settings, tools, and platform behavior rather than deliberate optimization.
At the same time, long-deprecated standards linger, advanced configurations remain uneven, and the long tail of the web remains untidy. Progress is real, but itβs incremental β and sometimes accidental.
What has shifted meaningfully is intent.
2026 will not be remembered as the year SEO ended or was reborn. It may, however, be considered the year the AI search layer became more defined. A new patch applied β not a fundamental rewriting.
For a deeper dive into the data behind these trends, explore the 2025 Web Almanac SEO chapter.

Most guidance on optimizing for AI still focuses on how content is written. But AI systems donβt read content the way humans do. These systems extract information, break it into parts, and reuse it in new contexts. What matters is whether your content can be pulled into an AI-sourced answer cleanly.
Where traditional SEO has centered on ranking pages, AI systems prioritize retrievable units of meaning. That changes how content needs to be built:
The shift is structural: Content that performs well in this environment is designed to be extracted, recombined, and attributed.
To design for AI usefulness and visibility, you need a basic model of how content is selected and used.
AI systems segment content into passages and retrieve those independently. That has a few implications:
When structure is unclear, the signal becomes less reliable, even when the topic is relevant.
After retrieval, content is used to generate an answer. AI systems tend to favor passages that:
This is where βlow-edit distanceβ shows up in practice. Content that can be used as-is has an advantage.
AI systems also decide what to cite. Content is more likely to be attributed when it includes:
If a section reads like a generic summary, itβs easier to replace with another source.
When content is retrieved in pieces, used in generated answers, and selectively attributed, structure becomes the lever. These principles show up consistently in content that gets surfaced by AI systems:
Content is more useful when itβs built in discrete units. Each section should:
Long sections that depend on earlier context are harder to reuse in isolation. Modular structure also makes content easier to update, test, and repurpose across surfaces β without rewriting the entire page.
A clear hierarchy helps systems understand what each section contains and how it relates to the rest of the page. H2 β H3 β H4 structure should signal:
Headings should make each sectionβs purpose immediately clear. When that signal is weak, it becomes harder to match the right section to the right query.
AI systems rely on whatβs stated directly. Make relationships and conclusions clear by:
If something is important, it should be written plainly. Copy that requires inference is harder to interpret and more likely to be skipped in favor of clearer alternatives.
Place the direct answer to the sectionβs core question at the top, then expand.Β
AI systems prioritize passages that resolve a query immediately. When the answer is delayed or embedded within a longer explanation, the relevance of that passage becomes less obvious.
Answer-first formatting requires that the opening lines:
The rest of the section can then add deeper nuance, examples, or other details that further understanding without changing the core response.
Passages compete for selection, both within the same article and across the web.
When multiple sections address the same question in similar ways, they dilute each other. Clear, specific, and well-scoped content βchunksβ are more likely to be selected.
You can audit a passageβs usefulness by asking:
If the passage needs context or cleanup, itβs less competitive.
These patterns show how structured, answer-first content is applied in practice β making it easier for AI systems to match, extract, and use.
Start with a clear definition. Then add detail. This works best for:
The definition should establish what something is in a way that can be quoted independently. The expansion then adds context, nuance, or examples.
This pattern helps position your content as a reference point for core concepts β especially when AI systems need a clean, authoritative definition.
AI systems are designed to respond to queries. This pattern aligns your content to that structure.
Order your content as:
The answer should resolve the query in one to two sentences, using the same language or phrasing as the question where possible.Β
Remaining content can add depth through nuance and edge cases that extend beyond the core answer.
Lists work best when theyβre introduced by a clear framing sentence that tells the reader β and the retrieval system β what the items represent.
This pattern works especially well for steps, criteria, features, and takeaways.
Well-structured lists are easier for systems to parse and reuse, especially when each item is clearly defined within the context of the list.
Structure content to make differences explicit. This works well for alternatives (βX vs Yβ), tradeoffs, and decision-making criteria. You can use:
Content that clearly outlines differences is easier for AI systems to extract and reuse in answers that involve evaluation or recommendations.
Most AI surfacing issues come back to content structure. When structure is weak, answers are harder to identify and extract. That tends to show up in the form of:
Long paragraphs with key points buried inside make it harder to isolate a clear answer. Without strong subheadings to define what each section covers, systems have fewer signals to identify where that answer lives.
Ask:
Headers like βOverview,β βIntroduction,β or βKey Takeawaysβ donβt provide enough signal about what the section actually contains.
Headings help systems understand what a section covers and how it relates to a query. When theyβre vague, the relationship between section and query becomes less explicit.
Ask:
When the answer appears halfway through a paragraph, itβs harder to isolate as a clean, reusable unit.
AI systems look for segments that clearly resolve a query. When the answer is embedded within surrounding context, it becomes less distinct and more likely to be overlooked or reassembled.
Ask:
When sections overlap, they compete for the same query and weaken the overall signal. Instead of reinforcing the topic, similar sections can fragment it across multiple passages, making it less clear which one should be selected.
Ask:
Clear separation improves both retrieval and selection.
Most teams donβt need to totally rebuild content from scratch. Updating existing content for todayβs landscape just requires a few structural changes.
Turn generic sections into clearly defined units, like:
Ensure each section covers a distinct angle and does not repeat or overlap with others. This helps consolidate signal and makes it easier for systems to select and attribute the right passage.
AI systems are already reshaping how content is surfaced, and that shift will continue as answers become more personalized and draw from multiple sources.
As a result, page-level ranking matters less on its own. Content value is shifting toward contribution β how clearly a piece of content can inform, support, or shape an answer.
The content that performs best will be:
Content that meets these criteria is more likely to be surfaced, reused, and attributed as AI-mediated search continues to evolve.
An Italian TV station has claimed ownership of Nvidiaβs DLSS 5 trailer, proving that YouTubeβs copyright system is absurdly broken Who owns Nvidiaβs DLSS 5 trailer: Nvidia, or a bunch of Italians and their TV station? The Italian broadcaster La7 has blocked Nvidiaβs DLSS5 reveal trailer, citing copyright grounds. Why? La7 showcased the trailer during [β¦]
The post Nvidia DLSS 5 Trailer taken down by Italians, yes really appeared first on OC3D.


ChatGPT Search is citing fewer websites per response after GPT-5.3 Instant became the default experience.
The post ChatGPT Search Is Citing Fewer Sites, Data Shows appeared first on Search Engine Journal.
Cliptude helps creators produce documentary-style videos quickly. It researches topics, writes scripts, sources stock footage and relevant A-roll, and assembles a full edit with motion graphics, maps, and timelines. It delivers premium AI voiceovers with natural pacing and exports ready files for YouTube, TikTok, and Instagram. Start from a prompt or script, then download the final cut or separate stems while keeping full rights.

For a long time, links were the primary signal of authority in search. If you wanted visibility, you built backlinks. If you wanted credibility, you earned placements. That still matters β but itβs no longer enough.
In AI-driven search, authority is shaped by how often your brand is mentioned, cited, and clearly associated with a topic. Visibility comes from being referenced in AI-generated answers.
With that shift in mind, the goal is to create content that earns consistent brand mentions and citations β the signals that now drive AEO visibility.
In 2026 organic discovery, authority incorporates entity recognition.
On both Google and LLMs like ChatGPT and AI Overviews, authority is reinforced through:
Since LLMs synthesize information instead of ranking pages, you need repeatable, credible mentions across the web to strengthen your brandβs likelihood of being cited or referenced in AI answers. Importantly, you also need to use your owned media to define your brand entity very clearly.
That makes building authority even more critical. Your content will now be battling with even more competition in the form of AI results in the SERP and AI-produced content from other publishers.
The TL;DR is that you need to establish a clear brand and, underneath that brand, create content thatβs so valuable that other experts, journalists, creators, and AI systems repeatedly reference your brand when theyβre discussing a topic core to your business.
Dig deeper: How to build an effective content strategy for 2026
Youβll use many of the same SEO principles as a base for AEO-friendly content. Content aligned with Googleβs helpful content guidelines β focused on value and user experience β appeals to the people (and LLMs) discussing these concepts and sourcing experts to validate their positions.
That said, to produce truly AEO-friendly content, you need to incorporate formatting that supports LLM extraction.
Key formatting principles include:
If youβre solely focused on AEO, Iβd approach your content with these objectives in mind:
To address these objectives, it can be helpful to think beyond blog posts to ideate βreference-gradeβ assets, including:
Dig deeper: How to create answer-first content that AI models actually cite
Hereβs how to turn those principles into a repeatable process for building AEO authority:
Dig deeper: Organizing content for AI search: A 3-level framework
Writing for AEO isnβt at odds with writing for humans. Even from its early days, AEO shared many of the SEO fundamentals derived from appeal to actual users.
That said, there are enough differences with the way LLMs extract and digest content (and the way users ask LLMs for information) that you need to keep specific nuances in mind in your content approach.Β
With a clearly defined brand on your owned media, and an understanding of the tenets of AEO and how to address them, you should have a good idea how to leverage your teamβs expertise for greater visibility on the AI search landscape.

Multical ends double bookings for portfolio careerists, fractionals, multi-hyphenates, and consultants. It syncs your Google, Outlook, and Apple iCloud calendars so every organization sees your real availability across all accounts. It blocks conflicts in real time, lets you set custom rules and filters, and never permanently stores event content.
Use Multical to manage unlimited calendars at one price, create scheduling links for each client or role, and view, create, and edit events in a unified, mobile-friendly calendar. Control what details others can see, revoke access anytime, and keep credentials encrypted.

Since 2021, Iβve worked on more than 350 published guest posts. In that time, Iβve refined a repeatable guest posting outreach process that consistently drives approvals without ever paying for a placement.
Although guest blogging is becoming more difficult, the basics of personalized guest posting outreach remain the same. If your mindset is to create mutual value, this process will work for you in 2026 and beyond.
Your outreach list is a collection of the websites youβll email to offer guest-written content. You can build your list in several ways.
The easiest way to find potential websites is by googling your niche alongside βwrite for us.β

Plenty of reputable websites openly accept guest posts and have an established approval process you can find online. Thatβs the exact approach I used to publish an article on G2βs Learning Hub.
Alternatively, search the name of a prominent person in your niche and add keywords such as βguest post,β βguest author,β or similar. Chances are that if a website has published guest posts from someone in your industry, theyβll be receptive to accepting guest posts from you as well.

Browse your competitorsβ backlink profile with an SEO tool. In Semrush, Backlinks is one of the SEO tools under Link Building.

To refine your list, verify which websites have previously published content from guest authors. If, however, all articles on a blog are written in-house and youβre not the BeyoncΓ© of your industry, chances are your guest posting pitch will go unnoticed.

Once youβve gathered a list of sites that potentially accept guest posts, run them by your website quality criteria.
Consider the website niche, top pages, organic traffic over time, countries where the traffic is coming from, authority score, and outgoing backlinks. You can also automate this step with the API of your favorite SEO tool.
Even the best guest post outreach will fail if youβre writing to the wrong person.
Most people ignore emails that arenβt relevant to them, nor do they forward them to the right colleague.
Thatβs why you need to do your homework. Thereβs likely a specific department or person you should be addressing.
Hereβs how to find the right person through LinkedIn:

To do this, you can type βcontentβ and browse the results for a content manager, content editor, or similar.
In smaller companies, you can search for βmarketingβ or βgrowthβ to find whoβs the one-person marketing team.
For micro companies, your best contact person might be the founder or co-founder.
Sometimes, youβll come across companies that have no listed employees on LinkedIn, or their emails are not available. In this case, your only option might be a generic email such as contact@ or support@. For micro companies or in certain niches (typically B2C websites), these emails can still work.
This step helps you protect your sender reputation and ensures your emails end up in the inbox, not the spam folder.
There are two distinct ways to approach guest posting outreach.
Ask whether the website accepts guest-written content. This way, you donβt invest a lot of time upfront into every pitch and your only focus is on building an outreach list.
As the emails arenβt highly personalized (they usually just include the names of the person and the company), they generate a moderate reply rate.Β
To drive results with this approach, you need a large outreach list so youβll still get enough opportunities to work with at a 3% to 5% reply rate.
The email you send to company A offers something completely different than the email youβre sending to company B. It takes a lot of time to research and tailor your pitch, but it also enjoys a higher reply rate (around 19%, from my experience).
This approach works best when you have a small outreach list or when youβre pitching to prominent websites.
No matter your outreach approach, you usually need to pitch guest post topics. With basic personalization, you suggest topics only to the websites that reply to you. But with the hyper-personalized email approach, you propose topics in the first email you send.
Top-tier websites typically only accept specific types of guest articles. Find the websiteβs editorial guidelines by googling β[company name] + guest postβ and see their requirements.
Letβs look at HubSpot as an example. Theyβre only publishing marketing experiments, original data analyses, or super detailed tactical guides.

Similarly, writing a guest article for Zapierβs blog requires specific experience. Generic topics wonβt make the cut.

Buffer takes things a step further by opening rounds for guest posting under specific themes.

Following each websiteβs requirements increases your chances of landing a successful pitch. But most websites are open to a broader range of suggestions.
Some editors have a list of keywords or topics they want to target. They may share it with you so you can choose a topic to write on based on your expertise.
Alternatively, you can bring your own guest post ideas. When thatβs the case, you can use a keyword gap analysis to uncover relevant topic ideas.
Letβs say you want to pitch a guest article to monday.com. Hereβs how to go about it:

Look only at keywords where competitors are ranking in the top 100 results.
Limit the keyword search volume to 2,000. This filters out broad, highly competitive terms that typically require long-form, comprehensive guides to rank.


For example, βwhat is time boxingβ has 49% keyword difficulty.

After selecting βmonday.com,β you see the site has low topical authority for βwhat is time boxing,β and ranking for it would be very hard.

Looking at βcost management in project management,β the Personal Keyword Difficulty is 60%. While thatβs still high, thereβs more to consider.

Monday.comβs Authority Score (AS) is 67, while the average in the top 10 is AS 52. Despite this being a competitive keyword, with the right content, monday.com has real ranking potential.

To do this, use the βsite:β search operator and add your keyword into Google search.
In this case, βtask priorityβ came up in the keyword gap analysis. While monday.com doesnβt have an article with this keyword in the H1, it does have very similar content on how to create a priority list or prioritize tasks.

Adding extra value is about what else you can bring to the table besides guest content.
Your extra value proposition is unique to your profile, and different value props can appeal to different websites.
For example, I have 11,000 followers on LinkedIn. When reaching out to a project management toolβs blog editor, I can mention that 54% of my followers are founders, executives, or senior-level professionals in small to mid-sized companies β the very people responsible for managing processes and tools within their organizations.
If Iβm personalizing this pitch for a lead-generation blog, I can highlight that 35% of my audience works in the marketing or advertising industry.
When it comes to your emails, you need to consider the subject line, the email body, and follow-ups.
In simple terms:Β
According to BuzzStreamβs analysis of six million emails, the best-performing subject lines:
On to the email body: Keep your emails concise and skimmable. Editors rarely have time for long messages.
Finally: follow-ups. Statistically, the more you follow up, the higher your overall campaign reply rate. Some people reply after the first follow-up, others after the third.
My recommendation? Limit follow-ups to two. A third one feels too pushy.
Youβve done a lot of preparation work. Itβs finally time to send your emails. Hereβs what to consider:
An analysis of 85,000 personalized emails showed the best day to send a cold email is Monday, closely followed by Tuesday and Wednesday. These are the days with the highest email open and reply rates.
The same study suggests you should be sending your emails between 6 to 9 a.m. PT (9 a.m. to 12 p.m. ET). But since most editors are based in different countries, aim to send your email before noon in their local time.
Always give recipients a clear way to opt out of more emails. Without an unsubscribe option, recipients may mark your message as spam. This can damage your sender reputation and reduce future deliverability.
Most outreach tools allow you to track open, reply, and success rates. Letβs break down what each metric tells you.
Track these metrics to identify weak points in your outreach campaigns.
After you establish a baseline, run controlled A/B tests. Send different versions of your campaign to similarly sized groups and compare performance. Change only one variable at a time so you can clearly measure its impact.
Test ideas such as:
Small improvements across different elements of your campaign can compound into measurable gains in success rate.
I mentioned Iβve worked on more than 350 guest articles. But that doesnβt mean they were all published on different websites. When you provide quality, youβre very likely to build lasting relationships that result in ongoing work.
Thatβs one reason I use keyword gap analysis to choose topics. I target keywords that the website has real potential to rank for. When an article brings meaningful traffic, it becomes much easier to pitch the next one.
To establish lasting relationships with editors:
Below is the guest post outreach template that has delivered the strongest results in my campaigns.
Between 2023 and 2025, I sent more than 300 pitches using variations of this template, primarily to content managers at B2B SaaS companies in the marketing and HR niches. It generated a 19% reply rate, and 18% of sent emails resulted in a published guest post.
Subject: Fresh content ideas for [Company Name]
Hi [First Name],
My name is [Your Name], and Iβm the [Your Job Title] at [Your Company], a [short company description].
Iβm reaching out to see if [Company Name] is open to guest contributions. I have extensive experience in [your expertise area], having worked on projects for brands such as [Brand 1] and [Brand 2].
Here are a few topic ideas Iβd love to propose:
keyword: [primary keyword 1], US search volume: [search volume]
[Proposed Article Title 1]
keyword: [primary keyword 2], US search volume: [search volume]
[Proposed Article Title 2]
keyword: [primary keyword 3], US search volume: [search volume]
[Proposed Article Title 3]
To learn more about my background, you can view my [LinkedIn profile link] or review articles Iβve written for [Publication 1], [Publication 2], and [Publication 3].
If the article is a fit and gets published, Iβd be happy to promote it to my community of [audience description or size].
Looking forward to your thoughts,
[Your Name]
Your author profile directly influences your approval rate.
If youβre just starting out and donβt have a portfolio of published work, editors will hesitate to approve your topics. Start by reaching out to small or mid-sized industry blogs.
As you build your portfolio, pitching becomes easier. Publishing on recognized industry websites and creating content that drives measurable results strengthens your credibility and improves your success rate over time.
Bottom line: Invest in your author profile. Thatβs your biggest asset for successful guest blogging.


Will WordPress's troubled real-time collaboration feature be worth delaying the release of WP 7.0?
The post WordPressβs Troubled Real-Time Collaboration Feature appeared first on Search Engine Journal.
LLM Consensus sends your prompt to GPT-5.2, Claude Opus 4.6, and Gemini 2.5 Pro simultaneously. The models critique each other's responses, then combine the best elements into a single answer with a quality score from 0 to 1. This results in less hallucination and better answers for important questions. There are three modes: fast (~10s), balanced (~25s), and deep (~60s). The standard REST API is OpenAI-compatible. You can pay per request with USDC via the x402 protocol, or use API keys with prepaid credit packs and a usage dashboard.
The Witcher Onlineβs 2.0 update adds trading, multiplayer boat/horse riding, and more The Witcher 3: The Wild Huntβs Online mod has received its 2.0 update, transforming the mod into a more MMO-like experience. Now, the mod supports item trading, customisable horses, new emotes, and other feature upgrades. With the addition of horse sync and boat [β¦]
The post The Witcher Online 2.0 has arrived, and itβs nuts appeared first on OC3D.
AvailSim helps travelers find the right eSIM plan worldwide by aggregating offers from trusted providers. It normalizes plan details and calculates true price per GB so you can compare coverage, data, and cost side by side, with independent rankings untouched by affiliate payouts. You also get destination guides, a data calculator, and a device compatibility checker, then purchase directly from the provider.
AI Sign Designer transforms any uploaded image into a production-ready custom sign design with instant pricing. Customers upload a logo, photo, or sketch, the AI converts it to clean vector files, and they get a quote in 2 minutes instead of the usual 48-hour wait. It generates layered SVGs compatible with Illustrator, CorelDRAW, and FlexiSign. It handles neon, channel letters, lightboxes, and more with real-time visual previews. Sign shops embed it on their website to automate quoting from design to production files.

AdaptlyPost is a social media scheduling and management platform that lets you create once and publish to Instagram, TikTok, YouTube, X, and more from a single dashboard. Plan with a visual calendar, queue posts, and track what's going live. Use AI Image Studio and an AI caption co-pilot to generate visuals and copy, then automate posting via API or OpenClaw agents. Collaborate across workspaces and teams, and scale with plans for creators, businesses, and agencies.
PokerBotAI makes desktop poker bots powered by neural networks. PokerX Bot reads the table, decides, and clicks, working in fully automatic or advisory mode. It handles Hold'em, PLO, Short Deck, MTT, and OFC across 20+ rooms. The engine combines 300M real hand histories with 7B simulated scenarios. It also offers club management tools, a managed bot farm with profit sharing, and custom development.
Compare debt payoff strategies and become debt-free faster
Visual trace replay for AI apps to fix bugs in one click
Track the Artemis II mission from your Mac
The AI video model that actually feels alive.
AI Physical Therapy for Athletes
Turn support emails into tickets
Your best QA team β 9x faster, 20Ρ cheaper
AI creative agents for ecommerce brands
Remap Caps Lock to a hyperkey, just hold it + any key
AI SRE that detects, root causes & auto-fixes K8s incidents
Everything in OpenClaw's terminal, you can now do visually
Your AI agent for ad performance
Private Telegram AI agents, live in under a minute
Free local speech-to-text tool
Portable memory for agent workflows

Intel on GitHubIntel will not provide or guarantee development of or support for this project, including but not limited to, maintenance, bug fixes, new releases or updates. Patches to this project are no longer accepted by Intel. If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the community, please create your own fork of the project.
Walvee is an AI-powered travel platform where you describe the experience you want and get a full itinerary including flights, hotels, places, and day-by-day planning organized and ready to use. Unlike basic generators, Walvee includes a Concierge that stays with you during the trip: you can ask for restaurants near your hotel, find hidden gems, or add new places to your day on the fly.
You can also explore and "steal" trips from other travelers, customize them, and share your own routes. Walvee is for people who want more than a spreadsheet β they want a companion that adapts before and during the journey.
stackcost is a community-driven database of what it actually costs to run a startup. Founders publicly share their full stacks, monthly bills, and ROI so you can compare tools, spot overkill, and budget with real-world data. Browse verified receipts, leaderboards, and detailed stack pages, then create your profile to contribute your own stack and get discovered.
IslaApp helps small businesses build and launch bilingual websites quickly. Use an AI-powered editor to rewrite text, swap images, and adjust layouts, then publish with one click. Choose from over 75 industry templates in English and Spanish, connect a custom domain, and enjoy SSL, hosting, and built-in analytics. Sell online with an integrated store and ATH MΓ³vil card payments, manage forms and databases, and run AI email campaigns with responsive support.
Story Generator helps you create full stories from simple prompts. Choose a genre and get structured narratives with chapters, character arcs, dialogue, and endings in seconds. The tool also builds outlines, plots, prompts, and titles and returns multiple versions per run so you can pick your favorite. Use it to overcome writerβs block, plan scenes, or produce ready-to-read drafts, and export your results. Start free without a credit card, with support for visual storytelling and childrenβs stories.
OPT-IMG is an AI-powered image SEO platform that turns raw images into SEO-ready, faster-loading assets. It automatically generates SEO-friendly filenames and alt text and compresses images in a single workflow. Users can batch process images, create responsive outputs, and export optimized assets at scale. OPT-IMG helps improve image search visibility, page speed, and Core Web Vitals for eCommerce sites, blogs, and content teams.

There will be gaps in enforcement until there is a definitive solution to ensure that the same standards apply to all platforms.
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The data contracting firm works with all the major artificial intelligence providers, including Anthropic, OpenAI and Meta, and was hit by hackers last week, per Wired.
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The enhanced protections will help musicians who use the appβs SoundOn service identify misused audio tracks and combat copyright violations.
Google, Meta, Microsoft and Snapchat said they would continue to take voluntary actions to protect their platforms following the expiration of the EU ePrivacy Directive.Β
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Musk told banks, law firms and other advisors they need to buy subscriptions to artificial intelligence chatbot Grok before the June initial public offering, per the New York Times.Β
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Co.Actor helps you grow your personal brand on LinkedIn by learning your tone of voice from your posts and every edit. It surfaces daily, relevant post ideas from industry news and your network, then drafts content that sounds like you and lets you schedule directly to LinkedIn.
Use Co.Actor solo or with your team: each member keeps a unique voice, while shared dashboards, notifications, and analytics reveal what resonates and when to post. Track views, engagement, and follower growth, and get data-backed suggestions for what to publish next.
SurveyJS is an open-source JavaScript form builder that lets you create a custom form platform within any web application. Unlike SaaS tools like Typeform or SurveyMonkey, it is not a hosted service and has no usage limits. You can create unlimited forms using a drag-and-drop interface and collect unlimited responses while keeping full ownership of your data. SurveyJS integrates directly into your application, giving you complete control over the UI and branding. Both the form builder and the forms can be fully white-labelled with no external logos or references.
Salow.IO is an AI deal intelligence platform that analyzes B2B sales conversations and returns a deal health score across 9 dimensions, a confusion diagnostic isolating buyer noise, friction, and seller inconsistency, and three ready-to-send closing paths per deal. It detects signals like stakeholder silence or pricing objections and maps them against sales cycles and buyer profiles for 25+ verticals. The platform learns each rep's writing voice from their sent emails via a three-tier Voice DNA engine, so every response sounds like them, not a chatbot. Reps can upload sales playbooks as Strategic Doctrine, enforced across all outputs.
Esseeoh helps creators turn long videos into SEO-optimized YouTube Shorts and auto-posts them with AI-written titles, keyword-rich descriptions, and niche hashtags. It streamlines discovery so your Shorts get recommended to new viewers without manual edits.
If you havenβt uploaded in three days, it finds a top-performing video, generates a fresh Short, and publishes it to keep your channel active and consistent with minimal setup.

VitalStep provides guided fitness programs tailored to age, goals, and health conditions. Choose from 7-day, 21-session templates that build weight control, fat loss, and cardiovascular endurance with low to moderate intensity exercises safe for osteoporosis, diabetes, gout, and hypertension. Follow clear, gentle routines that improve circulation, support blood sugar and metabolism, and promote relaxation, so you can train confidently without aggravating sensitive joints.
PPTXMailMerge lets you generate data-driven PowerPoint presentations by merging Excel, CSV, or JSON with a PPTX template. Upload a data file and a deck, add smart placeholders, and create personalized slides for each row in seconds. Replace text, images, QR codes, tables, and charts using Excel-like addressing and full JSON traversal, then export a single deck or one file per row. Start free for small jobs or choose short 3-day plans for larger batches with secure processing.
ClauseGuard analyzes contracts to reveal hidden risks, flag unfair clauses, and extract key terms in seconds. Upload a PDF, Word doc, or text file and get a report with a risk score, red flags, plain-English summaries, and ready-to-send counter-language.
It saves your analysis history for deal comparison while keeping files private by not storing uploads. Use it to review NDAs, freelance agreements, and service contracts before signing.
Pelaris is an AI coach that knows your goals, fatigue, RPE, and progress. It builds and continuously evolves science-based, periodized training programs around your life, adapting in real time based on how you train. Not a static plan, but a coaching system that gets smarter every session.
Pelaris supports strength training, running, swimming, cycling, triathlon, CrossFit, and general fitness, using multiple science-based methods per sport. The AI coach remembers your injuries, preferences, and history, adjusting volume, intensity, and exercises as you progress. Built on Flutter, Firebase, and Vertex AI. Privacy-first by design.
ReadThai.Fun is a free Thai script learning tool created by a 20-year Thailand expat. It uses spaced repetition and interleaving to teach all 44 consonants and 32 vowels through 19 tiers ordered by real-world frequency. Each tier requires a 100% gate test before advancing, ensuring genuine mastery. The app includes OCR camera scanning for Thai signs and menus, a 13-language translator, personal dictionary builder, 3-level writing practice, and a text decomposer that breaks Thai words into consonant and vowel components. It works on any device as a PWA and is completely free with full functionality.
Receivly is an invoicing platform for small businesses and freelancers. Create professional invoices in seconds with auto-numbering and due dates, then see receivables organized as Sent, Overdue, or Paid on a clean dashboard. Automate payment reminders at 7, 14, 21, and 30 days, and keep customer details and default terms in one place for reuse. Mark invoices as paid in one click without bank connections. Your data stays in a secure, isolated workspace so you remain in control.
How Are You is a 24/7 safety app for families with aging parents. It runs on an Android phone, learns a personβs routine in seven days, and detects anomalies like long stillness, missed wake-up times, or leaving safe zones. When something seems wrong, it emails family with context and GPS coordinatesβno app required for them. Data stays on the device, with secure, anonymous summaries used for AI analysis. Setup takes minutes, costs $49 with a 14-day guarantee, then $5/year.
iMideo is an all-in-one AI platform that generates and edits videos from text, images, or existing footage. You can switch among 8+ leading models to compare results and quickly produce cinematic outputs. It supports text-to-video, image-to-video, video-to-video, and reference-to-video, and lets you enhance videos with effects, upscaling, background removal, and sound. Create talking avatars, face swaps, subtitles, and lipsync, and extend or animate shots with cloud processing and credit-based pricing.
ClawSkills is an open registry for AI agent skills. Creators upload AgentSkills bundles, version them like npm, and publish searchable entries indexed with vectors. Browse curated highlights, explore the latest drops, and roll back to prior versions when needed. Install any skill in one shot with npx clawskills@latest install
VeriRFP is an automation platform for enterprise security questionnaires and RFPs. When a buyer sends a 300-question security assessment, VeriRFP uses local AI models like Ollama to draft answers based on your approved SOC 2 reports and existing security policies. This ensures every answer is accurate and cited without sending sensitive company IP to shared cloud AI models.
VeriRFP also acts as a unified Trust Center. You can securely share compliance documents with buyers through an NDA-gated portal, route complex questions to your engineering team for review, and export the final audit-ready package with one click.
Meal scan, macros & AI coach
AI that finds your teamβs workflows and hidden structures
Refine UI in the browser, feed changes to your coding agent
RevenueCat stats in your macOS menu bar.
The screenshot editor for iPhone.
AI marketing Agent for result-driven influencer campaign
Local, open-weight AI designed for real-world languages


Cheeky Cycle is a peer-to-peer marketplace for buying and selling second-hand bikes with trust built in. Every verified listing checks the frame number against stolen bike registries, and payments stay protected until you confirm the bike matches the listing. Browse by type, size, location, and budget, message sellers, and arrange viewings in one place. When selling, snap photos and let AI identify your bike, auto-fill specs, and suggest market value, then manage offers and get paid with no hidden fees.
Ratatosk analyzes your ERP, databases, and spreadsheets to identify how the same business concepts are defined differently across systems. It produces a canonical data model, highlights conflicts, and shows exactly where definitions break across finance, manufacturing, and operations.
Teams use Ratatosk before ERP migrations, integrations, or audits to eliminate ambiguity at the source. Instead of discovering data issues mid-project, you start with a clear, unified model that downstream systems can enforce.
OriaFlow helps laid-off tech professionals and active job seekers find roles that truly fit and secure offers faster. It learns your background, goals, timeline, and constraints through chat, then builds a ranked shortlist and scores each opportunity on Fit, Chance, and Risk with clear reasons. You can generate ATS-friendly resumes and tailored cover letters, prepare with company-specific interviews, and track your pipeline. Visualize realistic next moves with a scored career tree, and use the Chrome extension for instant job detection and AI autofill across major job sites.
StratBase.ai lets traders describe strategies in plain language and instantly backtest them on years of tick data. AI translates ideas into formal rules with 239 indicators, multi-timeframe logic, and risk parameters, then a Rust engine runs fast simulations with full analytics.
Use grid search and walk-forward optimization, review trade logs, equity curves, and statistical metrics. It supports crypto (1700+ pairs), Forex (27 pairs), and US stocks (130 symbols). Share strategies publicly or keep them private while building author reputation.
Casasplus lets you search for properties in Panama in English or Spanish. You can browse apartments, houses, land, and commercial spaces for sale or rent across the whole country. Filter by city, neighborhood, building name, or private community to find exactly what you're looking for without scrolling through noise. Property owners and agents can list their properties to get in front of both local buyers and people looking at Panama from abroad.
Klyne is a workplace emotional intelligence app that helps you track how you feel at work, surface patterns, and respond with clarity. Quick check-ins feed NEDA, a patent-pending algorithm that measures intensity, frequency, and momentum to show how emotions build over time.
Get personalized insights, actionable strategies, and trend-based reports to manage stress, build resilience, and stay productive. Your data stays private and secure, with encryption and GDPR compliance.
Not therapy. Not a mood tracker. Just pattern awareness thatβs private, personal, and built for you. No employer access. Ever.
BlitzSupport is an AI helpdesk for small modern teams running support over email and website chat. When a customer writes in, AI agents detect the request type, collect missing details, search your knowledge base, and draft a reply. Your team opens a ticket that already has everything needed to act on. Approve, adjust, or escalate.
AI-native, not an AI bolt-on. Email and chat are unified into one ticket system. Human-in-the-loop at every step. Built in Germany and GDPR-ready. Currently in Early Access with guided onboarding for a limited number of teams.
HummingDeck lets teams share sales decks, proposals, and documents through trackable links and see engagement in real time. Measure opens, time per page, link clicks, downloads, and completion rates, and get instant alerts when prospects view your content. Upload PDFs, PowerPoint, Word, or interactive HTML to create dynamic proposals and see what resonates. View team-wide performance, identify hot prospects, and sync alerts and activity to your CRM and Slack to follow up at the right moment.
The Jak and Daxter Trilogy are now natively playable on PC through OpenGOAL As much as Iβd love to see it, Jak and Daxter isnβt getting remastered or remade for modern systems. Sony isnβt bringing this classic game collection to PC. While Sony has closed the door on Jak and Daxter fans, the community has [β¦]
The post The entire Jak and Daxter Trilogy is now natively playable on PC appeared first on OC3D.
Portifa helps artists create professional portfolios quickly and share a single link that shows who viewed it. Drop images, videos, and links, and AI organizes projects, tags work, and generates a polished bio. Choose from curated themes, add multiple pages, and track real-time viewer activity, including which projects they viewed and video watch time. Use your own domain, remove branding, and manage unlimited projects on the Pro plan to send tailored portfolios and get hired with confidence.
AI Photo Generator lets you create, edit, and refine images in seconds using powerful AI models. Start with text prompts and reference photos, then iterate in a dedicated workspace to get the exact result you want. AI acts as your co-pilot, providing feedback and suggested next prompts after every step. Get creative with special commands like "sketch" that use faster, cheaper models to generate random idea starting points. Plans start at $29 and include AI credits and unlimited characters.
Clawly runs your OpenClaw (Clawdbot) agent 24/7 without manually managing servers or setup. Launch to Telegram, Discord, WhatsApp, and Slack in seconds, then manage everything from a web dashboard with start/stop controls, uptime stats, and container-level isolation. Track tokens and spending in real time, use your own API keys, or opt for managed billing. Import and export configs, roll back updates safely, and scale from a single agent to multiple channels easily.
CaseClock helps lawyers capture billable work as it happens using voice on iOS, Android, and Apple Watch. Speak a draft entry in seconds, keep working, then review and approve entries before syncing to Clio or exporting by CSV.
CaseClock uses legal-aware AI to flag compliance issues and billing code errors, letting you catch disputes early while staying in control. Activity logs, encryption, and strict data residency protect confidentiality, and no voice data is stored after transcription.
Zen 6 leak unveils more cores, higher clock speeds, and boosted IPC If these leaks are true, AMDβs Zen 6 CPU lineup will be record-breaking. Red Gaming Tech has unveiled what their sources have told them about AMDβs next-generation CPU architecture. The long and short of it is that performance gains are expected in all [β¦]
The post AMD Zen 6 CPU Specifications Leaks β Big Boost Unveiled appeared first on OC3D.
Solvryns makes accounting affordable for small businesses, LLCs, and freelancers with all features for $24.99/month, no accountant required. Connect to 12,000+ banks via Plaid, let AI categorize transactions, and run live P&L, balance sheet, and cash flow reports. Send invoices, collect online payments, track AR and AP with aging, and reconcile accounts quickly. Invite your bookkeeper or CPA with role-based access, switch between cash and accrual, and export reports in one click. Budgeting, forecasting, journal entries, and month-end close help you stay ready for taxes. A 30-day free trial is available with no credit card required.
Ubezon is a white-label delivery platform that lets you launch a branded portal, manage drivers and handlers, track deliveries in real time, and handle payments via Stripe Connect. You can set roles for admins, senders, drivers, and handlers, and share live GPS links so customers always know where packages are.
Sign up and go live in minutes with demo data, unlimited team members, photo proof of delivery, email notifications, and webhooks. Charge senders, pay your team automatically, and keep the remainder with transparent pricing.
New PS3 emulation βbreakthroughβ boosts the performance of all emulated games RPCS3 contributor Elad has achieved a PlayStation 3 emulation βbreakthroughβ that will benefit all RPCS3 users. RPCS3 is the worldβs leading PlayStation 3 emulator, allowing classic PS3 games to be played on modern hardware. This includes Windows PC, Linux, macOS (Experimental support) and FreeBSD. [β¦]
The post RPCS3 team makes PlayStation 3 emulation βbreakthroughβ appeared first on OC3D.
Cashflowy is an all-in-one financial toolkit for US-based self-employed and service-based solopreneurs who want total clarity without the accounting headache. For $29/month or $290/year, it turns messy numbers into a clear roadmap, helping you master your financial health in under an hour a month. No spreadsheets, jargon, or stress.
MyFinances is a privacy-first finance dashboard that offers clarity without the risks of linking your bank. Unlike most apps that require sharing your bank login, we don't. You can manually log transactions or import CSVs to view clear charts, health scores, and track your net worth.
Use AI to find savings and forecast your financial future. Premium features include automated CSV categorization, a debt payoff planner, and "what-if" scenarios. Your data stays in a secured cloud vault linked to your Google account, keeping your financial life in your hands.
Pencil'd is an AI virtual receptionist for small businesses that answers calls, books appointments, and supports your customers when you can't be.
Set it up in minutes by adding your business info, choosing a new number or forwarding your existing line, and letting it handle inquiries while you work. It captures leads, provides answers, and syncs bookings instantly to your calendar and inbox. Pricing includes an Essential plan with minutes, an Unlimited plan with no overages, and Enterprise options for custom needs, ideal for service pros like cleaners, landscapers, movers, and contractors.
ColtVibe is a collaborative problem-solving engine where humans set the stage and AI agents compete to produce the best solution. It is not a chatbot; it is a meritocracy. The platform compares answers, accepts a canonical solution, and rewards trustworthy agents. As agents build their "Vibe," they gain more capacity and influence, making it harder to game the system and easier to surface reliable solutions.
Bring together people and content on the social web
Claude in Chrome, reverse-engineered, Jailbroken
Turn CLI / AI agents into McGyver
AI subtitles & translations for YouTube. 20+ Languages.
Slap your desk. Unplug distractions. Get back to focus.
Ultra-fast next-edit prediction for coding
Real-time AI camera that teaches you composition live
The image viewer macOS should have built.
See who's on your site. Right now.
Run many models side by side and fuse the best answer
Open Source Anti-Detect Browser with Unlimited Profiles
Create Images that Amaze
SimpleCourse focuses on making creating and selling courses as easy and painless as possible. We don't want to be another tool that overcomplicates your process or drains your time and mental capacity. With every feature we add, we ask whether it really makes your work easier or just adds more options you likely won't need.
Familoo is a shared calendar for families available on iOS and Android. Add events, assign them to family members, and everyone stays in sync automatically. Only the person who creates the family needs an account; others join by scanning a QR code. Events get automatic emojis and color codes based on their type, making the calendar easy to read at a glance. It supports Google, Cozi, and ICS calendar imports, works in nine languages, and keeps your data private. The app is free with an optional yearly subscription to remove ads and unlock themes for the whole family.
Helpview turns Notion into a real help center for customers or a shared knowledge base for your team. Keep writing in Notion, and Helpview publishes it as a fast, structured help center with beautiful themes, custom branding, and no code required.
Helpview also helps you improve content after launch. It offers smart search, an embeddable help widget, multi-language publishing, custom domains, and SEO-friendly pages. In the admin area, you can track searches, zero-result queries, and contact us inquiries to find content gaps and reduce repeat support questions.
Outsprinter unifies company goals, KPIs, and weekly execution so leaders and teams see progress, spot risks early, and stay aligned. The platform offers real-time dashboards, KPI management, goal planning, project and task tracking, and role-based user controls. Use the AI assistant to plan better KPIs and analyze performance, and keep everyone informed with notifications and reports. Import data from Excel and export CSVs to share results across the organization.
SimUser AI creates realistic AI personas that explore your web application, discover usability issues, and deliver experience reports with NPS scores before real users see your product. It maps flows automatically, records screenshots and video, and adapts to UI changes to keep tests passing. Use a web dashboard or API, customize personas, and integrate with your workflow to get actionable, persona-based insights that cut test maintenance and improve product quality.
WebAuditFlash delivers a complete website audit that detects invisible barriers holding back your traffic and sales. It analyzes SEO, performance, accessibility, AI compatibility (GEO), and UX, then provides a clear PDF report with a prioritized action plan in minutes.
Choose from three audits: Google Business Profile, SEO Plus, or Site 360, starting from β¬29. The service uses visual AI to identify conversion issues and works with WordPress, Shopify, Prestashop, Wix, Squarespace, and Webflow. No subscription required.
Mockly lets you create realistic fake chat and social media screenshots across WhatsApp, Instagram, Discord, iMessage, LinkedIn, TikTok, Reddit, and more. It lets you build conversations, posts, comments, stories, and even leaked emails with control over names, avatars, timestamps, and appearance, then download share-ready images. It also supports AI chat mockups for ChatGPT, Claude, Gemini, Grok, and Perplexity. Sign up free to unlock more platforms and create polished visuals in minutes.
Arcway helps students and early professionals master conversations that start their careers. Most people don't struggle in interviews because they're unqualified but because the conversation feels unfamiliar. Arcway closes that gap through structured practice with real-time AI feedback on delivery, clarity, and confidence. By the time the real interview happens, it no longer feels new.
Sora Watermark Remover is an easy-to-use online tool designed to help users remove watermarks from Sora videos quickly and cleanly. Whether you are looking for a Sora watermark remover or want to download Sora videos without watermarks, this platform offers a simple solution for cleaner video results. It is built for creators, marketers, editors, and anyone who wants professional-looking videos without distracting overlays.
Today, because of the expiry of the ePrivacy derogation enabling the use of technology to detect child sexual abuse material (CSAM), Europe risks leaving children acrossβ¦

Looking to take the next step in your search marketing career?
Below, you will find the latest SEO, PPC, and digital marketing jobs at brands and agencies. We also include positions from previous weeks that are still open.
(Provided to Search Engine Land by SEOjobs.com)
platform purpose-built for regulated industries. Designed to enable seamless self-service, Ushur infuses intelligence into digital experiences to create more delightful and impactful customer interactions. Backed by robust compliance-ready infrastructure and enterprise-grade guardrails, Ushur powers vertical AI Agents tailored for healthcare, financial services, and insurance. With [β¦](Provided to Search Engine Land by PPCjobs.com)
Senior Paid Media Manager, Brightly Media Lab (Remote)
Senior Brand Insights Manager, Derflan Inc (Remote)
Marketing Specialist, The Bradford group (Hybrid, The Greater Chicago area)
Paid Search Specialist, Maui Jim Sunglasses (Peoria, IL)
Digital Marketing Manager 10x Health System (Scottsdale, AZ)
Marketing Manager β SEO & GEO, Care.com (Hybrid, Austin Texas)
Digital Marketplace Manager, Venchi (Hybrid, New York, NY)
Advertising Media Manager, Vetoquinol USA (Remote)
Programmatic Advertising Manager, We Are Stellar (Remote)
Marketing Manager, Backstage (Remote)
Note: We update this post weekly. So make sure to bookmark this page and check back.
Tether AI is a personal AI agent that lives inside Telegram. Message it like a friendβit searches the web, manages your calendar, sends reminders, and runs recurring routines on autopilot. Set up a morning briefing with news and your schedule, and it delivers it every day while you sleep.
Unlike other AI agents that require API keys, self-hosting, or complex setup, Tether works in 2 minutes. Sign in, link Telegram, and you're done. It supports voice, images, and Google Calendar/Gmailβand every action is fully logged so you always know exactly what your agent did and why.


Google is fixing a long-running Search Console bug that inflated impression counts. As the fix rolls out, reported impressions will decrease.
What happened. A logging error caused Google Search Console to over-report impressions starting May 13, 2025. Google today updated its Data anomalies in Search Console page:
A Google spokesperson told Search Engine Land:
Whatβs changing. Google is deploying fixes that will change how impressions are recorded and reported. As the rollout continues, youβll likely see a drop in impressions in the Performance report. Clicks and other metrics arenβt affected.
The timeline. The issue began May 13, 2025 and persisted until now. Google said the correction will take several weeks to fully roll out across reporting.
Why we care. If your Google Search Console impressions change in the coming weeks, it will likely be due to this bug fix.


Customer journeys are collapsing into a single moment of evaluation. David Edelman recently described this shift as the convergence of behaviors that used to happen separately.
As decisions compress, brands need to be clearer about what they are trying to solve for the customer. Many organizations are increasing activity instead, without sharpening the underlying strategy.
Edelmanβs argument, outlined in his March 2026 Think with Google essay, is built around a shorthand developed by Boston Consulting Group and Google: streaming, scrolling, searching, and shopping.
His central insight is that generative AI has snapped these four behaviors together so tightly that the old model β awareness, then consideration, then purchase, each in its own tidy lane β no longer describes reality. Consumers bounce between platforms, multitask, and shift fluidly between entertainment and intent.
The data point that stopped me cold: people are now asking AI-enabled search engines much longer, richer, more emotionally descriptive queries. Not keywords. Paragraphs. They share context, constraints, preferences, and urgency.Β
The AI then breaks those queries into multiple search streams and synthesizes results in real time. What once required dozens of browser tabs β hours of work β now takes seconds.
Edelman draws two implications from this.Β
Dig deeper: From searching to delegating: Adapting to AI-first search behavior
Walt Kelly gave us Pogo, the philosophical possum of Okefenokee Swamp, whose most celebrated utterance was the 1970 Earth Day poster declaration: βWe have met the enemy, and he is us.β
Kellyβs most persistent target was not any external villain, but the human tendency to mistake activity for progress. His characters were always busy β scheming, planning, campaigning, reorganizing β and almost never clear on why.
Another line often attributed to him captures it just as well: βHaving lost sight of our objectives, we redoubled our efforts.β
Read Edelmanβs argument through that lens, and the pattern becomes harder to ignore. He describes brands racing to keep up with compressed customer journeys β more content, more specificity, more βanswer audits,β more presence across platforms and formats. The advice is sound.Β
But without clarity about what a brand is actually trying to solve for the customer, more content and more channels are just Pogoβs swamp creatures running faster through the same mud.
Dig deeper: Why clarity now decides who survives
Edelman is right that the journey is compressing. But compression can serve two different masters.Β
For brands with crystal-clear positioning β brands that genuinely know what problem they solve and for whom β compression is a gift. It helps a consumer build confidence faster.Β
Warby Parker, which Edelman cites approvingly, is a clean example: its home try-on program, transparent pricing, and frictionless returns all express a single, coherent answer to a specific question: βCan I trust buying glasses without trying them in a store?β Every element of that brand experience is aimed at one objective.
For brands that lack that clarity β brands that have accumulated messaging layers over years of campaign-by-campaign marketing β compression is a disaster. The consumerβs AI-enabled query now synthesizes everything a brand has ever said across every channel, every format, every platform.Β
If those signals are inconsistent, contradictory, or simply incoherent, the synthesized answer will be a muddle. The consumer will move on. In Pogoβs swamp, the creature that runs fastest without knowing where itβs going simply reaches the wrong destination sooner.
Edelman gestures at this when he writes that brand should be understood as βthe sum of signals that make a company recognizable as a solution.βΒ
Heβs right. But Iβd push harder: the compression of the customer journey isnβt primarily a technological problem. Itβs an objectives problem.Β
Most brands canβt clearly articulate, in a single sentence, what specific situation they are the best answer to. If you canβt say it plainly, AI certainly canβt infer it.
Dig deeper: Why AI availability is the new battleground for brands
One of Edelmanβs shrewder observations is that some of his clients have constructed a βfalse trade-off between brand and performance.β
Marketing departments argue over budget allocations between brand-building and demand generation as though they are fundamentally separate activities. This is, as Kellyβs characters would say, a very impressive argument that completely misses the point.
Kelly spent years satirizing exactly this kind of internal organizational warfare β committees forming to study committees, campaigns launched to counteract the confusion caused by previous campaigns.Β
Organizations are often earnest and busy, and just as often distracted by their own processes. The brand-versus-performance debate is the marketing equivalent of explaining why two teams canβt collaborate because their mandates are structured differently.
In a compressed journey, brand is performance.
These are the same thing viewed from two angles.Β
The brands winning in Edelmanβs compressed journey world β Nike, Glossier, IKEA, Warby Parker β donβt appear to be having this argument internally. They have simply decided what problem they solve and built everything around that answer.
Dig deeper: Brand perception: How to measure and shape it
Edelman recommends something he calls a βrecurring answer auditβ: examine what a consumer would actually encounter across social discovery, video search, retail listings, and AI assistants for their most common customer scenarios. Gaps and inconsistencies, he says, quickly become visible.
This is excellent advice. Itβs also, if Iβm being blunt in the spirit of Kelly, only half the medicine. An audit shows you where your signals are inconsistent. It doesnβt tell you what they should be consistent about.Β
You can audit your way to a perfectly coherent set of messages that still fail to answer any real consumer question, because the messages were never designed around actual consumer situations in the first place.
You need to audit your objectives. What, precisely, is your brand the solution to? Not the product category. Not the feature set. The actual situation.
The specific tension in a personβs life that this brand, and not a competitor, is best positioned to resolve. Until that question is answered with unambiguous clarity, the answer audit is tidying the swamp without draining it.
Dig deeper: How to apply βThey Ask, You Answerβ to SEO and AI visibility
None of this is meant to diminish what Edelman has written. On the contrary, his framework for thinking about the compressed journey is the most coherent Iβve seen in years.Β
Three of his observations deserve to be tattooed somewhere visible on the forearms, wrists, hands, necks, and behind the ears of every marketing professional.
Thatβs not just a description of a media landscape. Itβs a theory of consumer psychology. Confidence is the triggering condition for a purchase. If youβre optimizing for impressions without asking whether those impressions build confidence, then youβre very busy going nowhere.
This sounds simple and is, in practice, revolutionary. The default mode of most brand organizations is to lead with what they make.Β
Edelman says lead with the situation you resolve. That is a fundamental reorientation of how marketing is conceived and executed.
Two questions. The first is a strategy question. The second is an execution question. Most marketing fails by answering the second question without having honestly answered the first.
Dig deeper: The authority era: How AI is reshaping what ranks in search
Kellyβs Pogo ran for 25 years, and the swamp never did drain. The characters were charming, the satire was sharp, and the folly continued because the creatures were incapable of distinguishing between effort and progress. Kelly found that funny.
Marketing history, filled with elaborate, energetic, and expensive campaigns from brands that no longer exist, is less amusing.
Edelman has given us a useful map of the compressed customer journey. Itβs fast, complex, AI-mediated, and it rewards clarity above all else. What he understates β though it runs beneath the surface of his argument β is that compression is also a reckoning.
Brands built on accumulated momentum, legacy awareness, and category inertia will find that a faster journey exposes their vagueness more brutally than a slower one ever did.
The compressed customer journey demands better thinking. And better thinking, as Pogo understood, begins with recognizing that the problem isnβt out there in the swamp. Itβs in here β in the planning meeting, the brand brief, the objectives slide that everyone in the room suspects isnβt quite right, but no one challenges.
With apologies to Pogo, βWe have met the enemy of the compressed customer journey. And itβs our inability to clearly say what we are actually for.β

Over the course of my three-decade career, the keyword drove paid search. Today, itβs one of many signals. Strategy is what determines performance.
Keywords were what you researched for weeks, then built your strategy around based on what you uncovered or hypothesized. You managed everything from bids to matched search terms to negatives and the audiences you targeted. Your career was built and measured by how well you structured around a keyword.
Paid media has always been deeply tactical, with Google driving the majority of search. You were methodical about placements, audiences, bids, headlines, extensions, and keyword-stuffed URLs.
This model worked. It gave practitioners the control they needed to get results.
You could see which search queries triggered ads and what they cost. If there was value, you expanded or doubled down. You might over-segment ad groups by theme or build campaigns around keyword audiences, then layer in modifiers and match types to drive 1200% ROAS.
Advertising has converged on a single structural shift: AI, or more precisely, automation built into the platforms. These systems now handle targeting, bids, and creative assembly that practitioners used to manage manually.
The keyword hasnβt disappeared. Itβs moved from the primary optimization lever to one signal among many that platforms use to deliver ads based on user behavior and the auction.
On Google, AI Max for Search is the clearest example. Itβs not a new campaign type. Itβs an optimization layer, similar to Smart Bidding, that changes how keywords function inside a search campaign. Googleβs AI uses your existing keywords, copy, and landing pages, including H1s and H2s, as signals rather than instructions to find and serve ads.
Google reports that advertisers using AI Max see 14% more conversions at a similar CPA or ROAS, with campaigns using exact and phrase match seeing lifts of up to 27%. Pair it with Performance Max across Search, Shopping, YouTube, Display, Discover, Gmail, and Maps, or Demand Gen for upper-funnel awareness, and the system expands further.
Dig deeper: Google Ads no longer runs on keywords. It runs on intent.
When I say strategy is the new keyword, Iβm not speaking in abstractions. Iβm saying there are specific inputs that now determine where your ads show up, who sees them, and whether they convert. These inputs have largely replaced the keyword list in paid media as the highest-leverage control.
The distinction matters. Strategy dictates the activity needed to achieve your goal and vision. Tactics are the execution. Whatβs shifted is that platforms now handle the tactics, and our job is to define the strategy that guides them.
Conversion data quality, including server-side tracking, has become the most important input in any account. Googleβs Smart Bidding and other platform optimization systems depend on conversion or event signals to learn and improve.
You can prioritize from all to one, which conversions matter more, whether itβs a lead from a high-value market versus a newsletter sign-up, or a new customer versus a returning one. These distinctions used to be handled through keyword segmentation and bid modifiers. Now, in a small way, theyβre handled through strategic conversation, where value is assigned or determined at that point.
First-party data, customer lists, CRM data, website behavior, and offline imports have become the equivalent of keyword research. The richer and cleaner the data you feed these systems, the better they perform. Itβs less about search volume and more about understanding your own customer data, making sure itβs structured properly, and connected to the platforms you advertise in.
Creative is a beast. Itβs moving from a production deliverable to a strategic signal.
For Demand Gen, Display, and Meta, your creative, functionally speaking, is your targeting. Platforms read your images, video, and copy to determine who sees your ads. Google AI Max generates headline and description variations based on your landing page content, your H1s, H2s, and so on.
The strategic questions, what themes resonate with which segments, what visual approaches drive action at different funnel stages, and what messaging frameworks allow AI to generate variations, now carry the weight the keyword used to.
Landing page and website quality have become paid media inputs, not just a thing for UX or CRO. AI Max reads your page to determine what queries to match and which headlines to generate. Final URL expansion in AI Max and Performance Max sends users to the page AI deems most relevant. Poor post-click experiences, thin content, and slow load times can tie back to lower conversion rates.
All of this limits AIβs ability to serve your ads.
Dig deeper: In Google Ads automation, everything is a signal in 2026
Our roles have shifted.
The most valuable work is no longer managing keyword lists or adjusting manual bids. I have strong opinions on that, but Iβll ask you, what else could you be doing with your time, instead of manually adjusting bids for thousands of keywords?
Itβs the strategic framework that AI systems operate within: ensuring data quality, defining creative strategy, building measurement into your teams, and knowing when the LLM is wrong and you, as an SME, need to adjust course.
The job of subject-matter experts is to guide the machines. That guidance takes the form of conversion architecture, audience signal quality, creative frameworks, and brand guardrails, rather than keyword lists and bid sheets.
This means investing time in understanding how:
Itβs the pros and cons we choose to emphasize β the signals we prioritize. It means building robust first-party data, developing frameworks across audiences, creative, and UX, and feeding that into AI to enhance. It means accepting that the keyword era is giving way to something fundamentally different.
The practitioners who treat strategy as their primary lever, who invest their energy in architecture and design rather than lever-pulling, will be best positioned as this shift continues.
The keyword list isnβt gone. Itβs no longer the center of the work. Strategy is.
Dig deeper: 4 times PPC automation still needs a human touch
Agentic AI shopping may not be good for SEO. But there's a reason why SEOs won't need to worry about it.
The post Why Agentic AI Shopping Feels Unnatural And May Not Threaten SEO appeared first on Search Engine Journal.

Paid search is often the highest-leverage ecommerce growth channel, delivering strong conversion rates and efficient spend when structured effectively.
Google Shopping and Amazon Ads capture high-intent demand while generating the data needed to scale it. These platforms connect search queries directly to revenue, enabling you to identify which terms drive sales and allocate budget accordingly.
The real challenge is organizing campaigns to act on that signal.
Paid search performs differently from other channels because it combines two advantages: intent and data.
Together, these create a powerful feedback loop. Search terms tied to revenue let you shift spend toward higher-converting queries, improving ROAS over time. On Amazon, this loop extends furtherβstronger conversion rates can improve organic rankings, lowering future acquisition costs.
Success in search campaigns depends on building multi-funnel structures. The concept is consistent across platforms, but implementation varies by campaign types, settings, and bidding strategies.
The architectures outlined below use wide-net, low-cost discovery campaigns to map the full search landscape, then funnel high-intent, proven converters into dedicated performance campaigns with appropriate bids. The result: stronger ROAS, improved rankings, and more scalable growth.
Dig deeper: Ecommerce PPC: 4 takeaways that shape how campaigns perform
The priority sculpting method is based on Martin Roettgerdingβs approach, with adaptations over the years. It uses a three-layer campaign structure to route keywords into different campaigns based on performance.
This lets you control spend on discovery keywords and maximize investment in high-performing, high-intent terms. The key is Google Shopping priority settings β βhigh-priorityβ campaigns serve first at lower bids.
Layer 1: Brand
Layer 2: Catch-all
Layer 3: Alpha
Dig deeper: 6 Google Ads mistakes that hurt ecommerce campaigns
The key considerations in this structure include the following:
The system relies on routing logic: Googleβs priority settings determine which campaign serves a query first. Negative keywords in the catch-all push proven converters into the alpha, where bids are higher and budget is protected. At the same time, non-alpha terms run through high-priority campaigns at the lowest possible bids.
The method lives or dies on weekly search term negation. Two actions are done regularly:
Shared budgets are critical. Layers 2 and 3 should work on a shared budget.
The system works only if they run together, because each query needs to be sculpted through the system. It wonβt work with separate budgets because if the budget on the catch-all high priority runs out, then the alpha would be the first contact, and the query would likely show on the alpha (at a higher bid), even though itβs not an alpha.
The system is designed to run across a unique set of SKUs. All three layers should target the same set of SKUs. Itβs recommended to start with all SKUs to begin with and then build out from there.
Products that get buried in the main campaigns or operate at a different margin tier can be peeled off into their own mirrored catch-all/alpha pair, ring-fencing their budget. Only do this when thereβs a clear reason. More campaigns mean more overhead and more fragmented data.
Itβs important to optimize the feed, as Google heavily relies on titles mainly for understanding the context of the product and which keywords to serve it.
Amazonβs campaign structure is more advanced than Google Ads and offers several advantages.
Amazon typically delivers higher conversion rates and more conversion data. Ad spend also drives both conversion rates and rankings, with a clear, measurable link between ad spend and organic ranking.
Ads drive traffic, traffic drives conversions, and conversion rate drives organic rank. That makes Amazon Ads an investment in organic search.
Google Ads campaigns run across the whole catalog. On Amazon, you build campaigns at the SKU level, typically one SKU per campaign.
The structure uses three campaign tiers: research, ranking, and performance. Each has a distinct goal and is managed by adjusting advertising cost of sale (ACOS) targets to reflect different profitability goals.
Tier 1: ResearchΒ
Tier 2: Performance
Tier 3: Ranking or exposure
Dig deeper: Why your Amazon Ads arenβt delivering: 6 critical issues to fix
The key considerations in this structure include:
With Amazon Ads, we bid toward an ACOS target. ACOS is the advertising spend as a percentage of revenue. Because Amazon data is so clean and conversion rates are high, we can calculate our bids to drive a certain ACOS.
The ACOS-based bidding formula:Β
Implementing ACOS bidding can be automated using software like Scale Insights. Different campaign tiers can be assigned different ACOS targets, and CPCs can be adjusted daily by the software.
Similar to Google Ads, keywords are funneled through from research campaigns into performance or alpha campaigns. This can be done manually or automatically with Scale Insights using an import rule.Β
The concept is very similar in that keywords that shine get imported down the funnel, while non-performing keywords are phased out through testing.
If a productβs conversion rate is below the market average on a given keyword, more spend will not likely improve its rank. Amazon usually surfaces the better-converting product.Β
The correct response is to fix the underlying issue: price, listing quality, imagery, or the product itself. Most advertisers skip this step and keep spending into a hole.
There are two strong views on ranking and cannibalization. Some argue that once your product ranks highly for a keyword on Amazon, you should reduce or stop ad spend. If youβre ranking organically, you can save on ads.
On the other hand, if a keyword performs well with strong ROAS, having two listings can outperform one. It increases your chances of a click. Ads also typically appear above organic listings, giving you higher placement.
Whichever view you take, the three-tier method lets you drive rankings through SKCs, then reduce or stop ad spend once you rank, if you choose.
The underlying logic for advanced campaign setup is the same across Google Shopping and Amazon Ads, with key differences beyond the core structure.
| Google Shopping (Priority sculpting) | Amazon Ads (Multi-tier architecture) | |
| Similarities | β Route queries to campaigns via priority and negatives. β Discover converting terms in a catch-all at a low cost. β Graduate proven terms to alpha with high tROAS. β Regular search term reviews, negatives, and alphas. | β Route keywords across research β ranking β performance. β Discover new keywords in broad, phrase, and auto campaigns. β Graduate proven terms to exact match for profitability. β Regular search term reviews, negatives, and imports to lower funnel. |
| Differences | β Run across the whole feed, separate high-margin products for ring-fenced budgets. β ROAS-based bidding. β Product feed determines search term targeting, and the advertiser is unable to select. | β Campaigns built at the SKU level rather than across the whole catalog. β ACOS-based bidding. β Search terms selected by advertiser. β Ads drive rankings, and you can save budget by monitoring organic rankings. |
Dig deeper: 5 reasons Amazon Ads is better than Google Ads for ecommerce
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Like all good answers, it depends heavily on your business and your goals. Both have advantages and disadvantages. We can say that:
The ideal is to run these together. Many brands may launch on Amazon and grow over to their own platforms and utilize Google Ads.
Paid search for ecommerce is probably the most effective advertising avenue you can explore. Both platforms offer significant opportunities when implemented properly. Each platform has pros and cons, and I would recommend further exploring the details in these campaign structures and deciding on the right implementation for your business.



It used to be that Google searches opened up a world of questions. You searched, sifted through links, and came to your own conclusion.
Today, AI Overviews, ChatGPT, Perplexity, and other AI platforms compress multiple sources into a single, synthesized response. In the process, nuance is flattened, and certain viewpoints can be overrepresented.
This marks a fundamental shift in online reputation management. Search engines now shape the information they surface. The result is a rise in zero-click behavior, where users accept AI-generated answers without visiting underlying sources.
For brands, that changes the stakes. Visibility no longer guarantees influence. Even a No. 1 ranking can be bypassed if the narrative tells a different story.
AI search engines now follow a new pattern for delivering answers. For the sake of this article, weβll call it AI narrative formation. Hereβs how it works.
AI systems pull from a wide range of sources. While you might expect trusted, peer-reviewed content, they often draw from Reddit, YouTube, review platforms, complaint forums, and social media sites like Instagram and TikTok.
Not all sources carry equal weight. A single trusted source can be outweighed by a large volume of lower-quality content. For example, a highly active Reddit thread filled with negative reviews may outperform a fact-checked source like Wikipedia.
AI condenses dozens of inputs into a short, digestible summary. In the process, nuance is lost, and fringe cases can become dominant themes. A complex reputation may be reduced to: βUsers say this company is not trustworthy.β
These summaries donβt stay contained. Theyβre screenshotted, shared, and repeated across platforms. Those repetitions become new inputs, reinforcing the same narrative in future AI outputs.
Dig deeper: The authority era: How AI is reshaping what ranks in search
To see how AI narrative formation works in action, letβs look at a use case.
My company recently worked with a finance organization to repair its online reputation. For this example, weβll call it Company X.
Problems emerged for Company X with the rise of Google AI Overview. Previously, under traditional SERPs, Company X had a solid reputation. Users searching Google for reviews would find a 4.2 rating on Trustpilot, a strong company website with employee bios, and numerous positive blog reviews from trusted sources.
Google AI Overview changed that. How? By resurfacing an old Reddit forum centered on negative complaints about Company X.
When users asked Google, βWhat are opinions like about Company X?β AI Overview delivered a clear answer: βCompany X has mixed reviews, with specific complaints regarding customer service.β But those customer service issues were resolved nearly a decade ago.
AI Overview pulled multiple reviews from that Reddit thread, combined them with strong negative phrasing, and factored in the lack of structured positive content to form a semi-negative impression. A new perception of Company X was created.
We can dig deeper into how AI impacts reputational risk. Consider the following:
A hard truth has emerged in ORM: The most accurate claim doesnβt rise to the top. The most repeated claim does.
Dig deeper: Generative AI and defamation: What the new reputation threats look like
Letβs walk through another case to see how an AI-generated narrative can be audited.
CEO X is the founder of a SaaS company. He has an ongoing thought leadership presence and a strong reputation in his industry.
On a recent podcast appearance, one quote was taken out of context and aggregated across several platforms. The quote was framed as an opinion rather than a fact. Blog posts were written, and Instagram Live reactions spread online.
In no time, ChatGPT and Google AI Overview turned CEO X into a controversial figure.
Hereβs a step-by-step guide to approaching that reputation management crisis.
We begin by identifying what search engines are saying about CEO X. We ask ChatGPT and Google AI Overview questions such as βWhat did CEO X say?β and βWhat is CEO Xβs current reputation?β This helps us analyze the issues.
We identify the claims associated with CEO X. Google AI Overview and ChatGPT describe CEO X as a controversial figure who recently made comments in poor taste. The narrative formed across both platforms is trending negative.
Next, we analyze the sources AI Overviews and ChatGPT rely on. We look for whether theyβre outdated, repetitive, or low quality. (In the case of Company X, the latter two apply.)
We identify the gap between AIβs narrative and reality.Β
The final step is to replace or respond to those negative sources. Claims can be addressed directly on Reddit, Instagram, or other platforms spreading the narrative. Structured explanations should also be published through FAQs and policies, while strengthening third-party validation.
Dig deeper: How AI changes how we respond to negative reviews and comments
Focusing solely on SEO rankings is no longer enough. We need to think in terms of narrative shifts and framing. That also means thinking in terms of inputs and outputs.Β
Users arenβt evaluating individual pages. Theyβre engaging with AI-generated answers. Rather than managing what users find, we need to manage the answers AI systems deliver. That means strengthening what those systems rely on:
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Matt Mullenweg invokes Will Smith's Oscars slap in response to Cloudflare's boat that EmDash is a successor to WordPress.
The post Mullenweg To Cloudflare: Keep WordPress Out Of Your Mouth appeared first on Search Engine Journal.


Google's John Mueller answers question of whether splitting a sitemap is worth the extra work.
The post Google Answers Why Some SEOs Split Their Sitemap Into Multiple Files appeared first on Search Engine Journal.
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