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
Most domain name generators produce bad results. Plenty Domains uses various AI models and layered prompting to produce truly great names. Try it and see for yourself! It features multiple projects, shortlists, Google research, and 1-click registration.
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
Spin up a terminal-style CV in minutes. Add your projects and custom commands, and let recruiters explore your skills like they're in a real shell.
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¦]
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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)
(Provided to Search Engine Land by PPCjobs.com)
Real Impact, Real People: Our mission at Point is to make homeownership more valuable and accessible. Your work directly helps homeowners access their wealth, achieve financial flexibility, and realize life changing goals. Funding: With over $175M raised from top investors like Andreessen Horowitz, WestCap, Greylock, [β¦]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.
ScanSkinAI is an AI skin scanner that lets you upload a photo to screen moles, rashes, acne, and other concerns, returning results in about 30 seconds. It analyzes images against 31+ skin condition categories and provides a detailed report with risk indicators and recommended next steps. You can add fast dermatologist review and track progress over time with monitoring, guides, and community support. Plans are available for individuals and enterprises, with API and SSO options for clinical integration.
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.
TendTo is a caregiver coordination platform that centralizes bills, medications, appointments, and documents for aging parents. It provides families with a shared dashboard, role-based access, and a calendar so everyone knows whatβs due and whoβs doing it. Tali, the built-in AI companion, delivers daily briefings, answers care questions, flags drug interactions, and scans pill bottles and insurance documents. TendTo sends reminders, tracks payment status, and stores records securely, replacing spreadsheets and group texts with one command center.
Guide IQ fine-tunes any AI or agent to think and act like a CMO who knows your business. It builds your brand DNA, buyer personas, and marketing strategy, pairs them with 26 expert marketing skills, and packages everything to upload into the AI you already use. Answer 20 strategic questions, export the system files, and get up and running in under 30 minutes. For a one-time $499, you gain CMO-level marketing judgment without hiring an agency or full-time exec, with a 14-day money-back guarantee.
Tick Dog offers features like deep analytics for forms with no subscription fee, charging strictly based on usage. That means you get all the bells and whistles without extra costs.
The newest feature set, Tests, enters the user testing and research area. It uses AI and a complex persona system to navigate your website like a real human, even on mobile.
Ugh Design is a browser-based generative design tool for creating bold visuals. Adjust algorithm and style, structure, scale, spacing, rotation, and regularity to shape compositions, then fine-tune tone, contrast, density response, sharpening, and noise. You can toggle invert and transparent backgrounds to fit any layout.
Use it to explore patterns, textures, and abstract graphics quickly while staying in control of every parameter.
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.
ApplyBtn is a Chrome extension that helps job seekers autofill applications on any job page. It generates tailored answers and cover letters from your CV and the job description, lets you refine them before submitting, and keeps you in full control. Free welcome credits are included. There is no auto-submission.
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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It combines text, voice prosody, facial cues, and optional biometrics to understand context, then learns your style overnight via on-device LoRA. Journal by typing, speaking, or sketching, and explore patterns over time without streaks or gamified pressure while your data stays local.
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.
DataEase AI offers a free AI-powered brand analysis that evaluates any website across seven dimensions: name, digital presence, visual identity, messaging, trust, AI discoverability, and web brand authority. Enter a URL to get instant scores and actionable recommendations with no sign-up needed. The tool extracts key brand attributes, highlights strengths and gaps, and guides you on how to improve visibility, consistency, and credibility.
Google's John Mueller answers question of whether splitting a sitemap is worth the extra work.
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LeadFluxA is a B2B lead generation platform that empowers sales teams by automating the process of finding, scoring, and exporting verified leads. The primary services offered include AI-powered prospect scoring, real-time verification of contact information, and advanced filtering options to build targeted outreach lists. LeadFluxA supports various types of users from sales teams and marketers to recruiters and agencies, helping them increase conversion rates, reduce prospecting time, and ultimately grow their pipelines.
Wovly is the AI co-founder for go-to-market. Trained on 500+ real startup case studies, it researches your market, identifies your best customers, and then does the actual workβwriting cold outreach emails, drafting SEO blog posts, generating pitch scripts, and creating detailed customer acquisition plans. Everything is built from your specific company context, not generic templates.
Wovly also defines experiments, tracks your progress, and remembers everything. It's not a one-off research tool but a persistent GTM partner that helps founders go from idea to first paying customers, with the actual assets to make it happen.
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TalkPilot is your real-time conversation copilot built for moments that define outcomes. Whether you're in a high-stakes job interview, closing a deal, or handling a difficult conversation, TalkPilot helps you stay composed, think strategically, and respond clearly without speaking for you. We believe the best performers donβt rely on scripts. They adapt in the moment. TalkPilot enhances that ability.
Composed is an AI communication tool for people stuck in the doom loop of high-conflict communication. Paste a hostile, manipulative, or guilt-trippy message from your narcissist ex, difficult coparent, toxic boss, or high-conflict family member. Composed identifies the tactics being used, drafts a calm strategic reply, and gives you a Composed Score based on expert-backed research so you can decide whether to send it, tweak it, or walk away. Built for co-parents, adult children of difficult parents, people navigating toxic workplaces, or anyone who dreads messages from THAT person. Composed helps you respond with clarity, relieve rumination, and get on with your day.
Built by a team with 15+ years of experience, Melon democratizes machine learning so any business can turn their data into predictions with no coding required. Traditional ML takes weeks and a team of experts, but Melon delivers results in minutes.
Upload your raw CSV data, describe your problem or let Melon auto-generate predictive questions based on your dataset, and get a production-ready ML model quickly. No ML background, Python, or SQL is needed. Melon is currently live in a fully self-serve, free beta.
Ekumene helps you decide what to do next by sorting every task into tiers based on deadlines, dependencies, and time left. It shows clear signals and an urgency score so you understand the reasoning and can override if needed. Connect your calendar and task sources, then use the web app and Chrome extension to view todayβs priorities, capture tasks, and check capacity. Templates and six life domains align work, health, and relationships, while clear constraints show when plans donβt fit.
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YourSolopreneurKit helps solo business owners choose the right tools with honest reviews, side-by-side comparisons, and practical guides across CRM, email marketing, website builders, analytics, home office, security, finance, productivity, and AI. Created by Renato, a former senior operations leader with 30 years of experience, it shares real-world strategies, curated recommendations, and a weekly newsletter so you can save time, cut costs, and run your business with confidence.
The company applied for lending and payment approval in the hopes of offering its users the ability to βhold balances, receive funds and make payments within βits app,β according to Reuters.
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The feature will launch with βCoachella TVβ in April and offer 24/7 streaming access to archival performances and 2026 festival highlights.
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Updates to the video generation app included higher quality exports, music generation tools and artificial intelligence-powered avatars.
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Uploaded PDFs in a carousel format are more popular on the platform than videos, according to new benchmark data from Socialinsider.
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The update will allow creators to decide when non-followers see their content, which could help align posts with regional engagement times.
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Hardware Hunter monitors Reddit, eBay, Slickdeals, and more to surface used computer hardware deals worth buying. It scores each listing for scam signals, vague specs, condition red flags, and price versus market, then delivers concise email or Telegram alerts with a verdict and link. Define what you're huntingβcategory, specs, sources, and price rangeβand it checks every two hours so you only see real opportunities.
Skedly is the reliability layer between your event sources and your application. It receives, filters, retries, and replays webhooks so you never miss a critical event, with real-time observability into payloads, headers, status codes, latency, and delivery history. HMAC signature verification, workspace isolation, and configurable alerts help you secure and monitor traffic.
Use the open-source CLI to test with real production events on localhost, and embed a customer-facing webhook dashboard in your app to let users manage endpoints, filters, and retries without building infrastructure.
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to balance cost and latency.
Preplo turns cooking videos from YouTube, TikTok, and Instagram into clear, actionable recipes. Paste a link and its AI parses transcripts or descriptions to extract ingredients, quantities, cost estimates, and timed steps you can follow in full-screen cook mode. Generate smart shopping lists, track a weekly cooking streak, and adapt recipes to your needs. Start free with limited extractions or upgrade for unlimited extractions, advanced features, and priority support. Available on iOS, with Android coming soon.
REAIGENT7 gives real estate agents their own listing platform with AI that answers buyer questions 24/7, captures leads, and routes every inquiry directly to your REAIGENT7 dashboard or your CRM. Build professional property pages in minutes, share anywhere, and keep your brand front and center.
Manage leads in a simple dashboard, move them through stages, and get follow-up reminders. Generate listing descriptions and social posts with one click, track showings and open house sign-ins, and grow your pipeline without portals or referral fees.
AI led all cited reasons for U.S. job cuts in March at 25% of the total, according to outplacement firm Challenger, Gray & Christmas.
The post AI Leads All Reasons For U.S. Job Cuts In March, Report Says appeared first on Search Engine Journal.
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The new ChatGPT ad format is standardizing, according to a new Adthena analysis of 40,000+ daily placements. What once felt experimental is becoming a disciplined, high-intent system for users already deep in decision mode.
The big picture: ChatGPT ads are converging on a short, structured, highly contextual style that favors precision over persuasion and utility over storytelling, marking a shift from creative-led advertising to real-time, intent-driven assistance.
By the numbers. Every word must carry weight and contribute directly to clarity or conversion:
Whatβs working. The dominant pattern is a βBrand: Benefitβ headline, separating the name from a specific value. It works because users in conversational environments expect immediate clarity, not intrigue or ambiguity.
Headlines are compressed. Headlines often read like functional labels rather than slogans. This brevity carries into the body copy. It typically uses two tight sentences: a proof point followed by an offer or nudge, showing youβre not trying to win an argument but give one compelling reason to act.
Context mirroring is a defining feature. The strongest ads directly reflect the userβs query or situation, signaling real-time tailoring. This marks a new level of AI-native targeting that goes beyond keyword matching into conversational relevance.
Concrete value signals carry outsized weight. Dollar signs and specific numbers β prices, savings, performance β consistently outperform vague claims. Numbers dominate body copy because they feel credible and native in a setting where youβre actively researching and comparing options.
Offers. Low-friction offers β especially βfreeβ trials or demos β are the most common conversion lever, reducing commitment barriers while users are exploring.
Calls to action. These are explicit and action-oriented, favoring direct phrases like βShop now,β βCompare,β or βBookβ while abandoning generic prompts like βLearn more.β
The overall tone. Calm, confident, and measured, with minimal exclamation points or question marks. It aligns more with helpful guidance than ad hype, helping ads blend into the conversational flow rather than disrupt it.
Why we care. ChatGPT ads reach users at high intent, where clarity and relevance matter more than creativity or storytelling. In a conversational environment, ads compete with useful answers, so vague or overly branded messages get ignored while precise, value-driven copy performs better. This shift rewards short, structured messaging and gives early adopters an advantage as the format standardizes.
Between the lines. While ChatGPT ads share DNA with paid search β especially in their focus on intent and relevance β they differ by integrating into dialogue, responding to high-intent users, and delivering messaging that feels assistive rather than interruptive.
The takeaway. Success in ChatGPT advertising depends on precision, relevance, and credibility over creativity, emotional appeal, or brand-led storytelling. The winning strategy: fit in perfectly when a user needs a clear, trustworthy answer.
The analysis. Adthena CMO Ashley Fletcher shared the data on LinkedIn.
N+One gives cyclists an AI coach that designs and adapts training to your goals and daily readiness. Connect Strava, Garmin, Wahoo, or WHOOP to sync activities, sleep, HRV, and heart rate, then view recovery, mood, and FTP estimates on a single dashboard. Chat with your coach anytime for guidance, nutrition tips, and real-time plan adjustments that fit your schedule.
Video Clipper helps creators repurpose long-form YouTube content into Shorts. Paste a YouTube URL and let AI transcribe, detect the most engaging moments, and cut ready-to-upload clips. You pay per minute processed with credits that never expire, starting with 20 free credits. Upload results straight to YouTube and scale your clipping workflow without subscriptions.
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Thereβs a flood coming. A downpour of noise β more content, more channels, more AI-generated everything, moving faster than most teams can keep up with. Somewhere in that volume, your customers are quietly drowning β overwhelmed, underserved, and one bad experience away from choosing someone else.
Youβve probably felt it on your team, too. Another tool. Another sprint. Another quarter of doing more with less. The productivity metrics look fine from the outside. But inside, people are running on empty.
Thereβs an old story about a man named Noah who, facing catastrophic disruption, didnβt freeze or panic. He didnβt look for shortcuts or try to outswim the storm. He built β with intention, with a clear design, and with people he trusted. When the waters rose, the ark held.
The brands that lead donβt adopt the most technology the fastest. They build with intention β designing systems and experiences that protect people.
What follows is the case for building your ark β and a practical framework to do it.
Customer-obsessed organizations achieved 49% faster profit growth and 51% better customer retention rates than their peers, according to Forrester. The gap between what customers need emotionally and what brands deliver comes down to design.
The strain isnβt only on the customer side.
That gap shows up in real ways.
For customers, it creates friction β too many choices, unclear navigation, and messaging that misses where they are. They arrive with a question and leave with more confusion. They donβt feel seen or helped.
For marketing teams, the impact is quieter but just as serious:
Brands that recognize these human issues move faster, retain stronger talent, build deeper customer loyalty, and drive better business outcomes. Enter what I call the wellness sweet spot.
The wellness sweet spot is the moment where AI, empathy, and human-first design converge β creating conditions where both your customers and your team can think clearly, act confidently, and trust the experience theyβre in.
Itβs an architectural decision about how your entire marketing ecosystem is designed to make people feel. When its three pillars are genuinely working together, four things become true simultaneously:
When these conditions are in place, something shifts. AI stops feeling like a disruption and starts working as a stabilizing layer β supporting, protecting, and quietly holding the system together. It manages the overwhelm. The ark keeps floating.
Dig deeper: How to avoid decision fatigue in SEO
Most marketing leaders still think about AI in terms of what it does β automate, generate, optimize, analyze. Those outcomes matter, but they donβt tell the full story. The more consequential question is how AI makes people feel while itβs doing those things.
For customers, AI used well is a guide that:
For teams, thoughtfully deployed AI absorbs the work that depletes people most: the repetitive, the reactive, and the administrative. It creates space for what human brains do best: strategy, creativity, relationship-building, and nuanced judgment.
When you build your marketing systems around it, the output quality goes up because the people producing it arenβt running on fumes.
This is empathy at scale. Not the kind that lives in a tagline, but the kind thatβs baked into how your systems are structured and how your content is designed to reach people.
This is where things get practical and start to move ahead of the curve. Most marketing dashboards show what happened β click-through rates, conversion rates, and time on page. Those metrics matter, but they donβt explain why someone left or how they felt along the way.
Emotional metrics help fill that gap by focusing on the conditions under which decisions are made. Research in psychology and neuroscience shows that people make better decisions, build stronger brand relationships, and become more loyal when they feel clear, confident, and calm.
Hereβs how traditional metrics map to emotional KPIs:
| Traditional metric | Emotional KPI | What it measures, reimagined |
| Time on page | Clarity index | How quickly someone finds what they need β without confusion |
| Conversion rate | Decision effort score | Cognitive load required to complete an action |
| Engagement rate | Customer calm markers | Behavioral signals of confidence, not stress (Qualified attention) |
| Team output volume | Wellness throughput | Strategic output produced with reduced burnout |
These are upstream indicators that help explain downstream performance. A low clarity index often shows up as stalled conversion rates. A high decision effort score can lead to rising cart abandonment. Declining wellness throughput tends to result in average output from top strategists.
Brands that start tracking these now gain an advantage over those that wait to react.
A caution before the roadmap: more speed and scale applied to a broken system will not fix it. It will amplify everything thatβs wrong with it. These five steps are meant to be done before you push harder on AI adoption.
Where are customers confused? Hesitating? Leaving? Map these moments using behavioral data combined with qualitative insight β customer interviews, session recordings, support tickets, search data. Focus less on what people clicked and more on where they felt lost.
Fewer choices. Plain language. Cleaner navigation. Every step you remove from a decision path is a small act of respect for your customerβs mental energy. This is generous. Itβs designing with intelligence.
Deploy AI to enhance orientation, clarity, and confidence. Donβt push aggressive automation or manufacture a sense of urgency. AI should make customers feel helped, not herded. Thereβs a difference, and your audience feels it.
Audit where your teamβs cognitive energy actually goes each week. Identify the work that is routine, reactive, or repetitive β and build AI into those gaps first. Protect the hours that require human judgment, creativity, and relationship-building. Those are the hours that drive real growth.
Begin tracking emotional outcomes alongside performance metrics. Start simple: add a one-question post-interaction survey.Β
Review search data for confusion signals. For example, growing volume for βhow do Iβ or βwhy canβt Iβ phrases on your own site may indicate your content isnβt answering questions before theyβre asked.Β
Monitor support ticket themes for friction patterns. A perfect measurement system isnβt required to start. The intention to look is.
Dig deeper: The secret to work-life harmony in SEO: Setting boundaries
In a market where nearly every brand claims to be customer-centric and frictionless, the real differentiator comes down to how people feel and whether systems consistently deliver on that promise.
Leading organizations donβt rely on bigger AI budgets. They align technology with clear intent, prioritize well-timed, empathy-led content over volume, treat customer well-being as part of the brand promise, and protect their teamsβ energy as rigorously as performance.
Creating value starts with protecting the people who create it. Noah didnβt survive the flood by ignoring it or fearing it. He paid attention, took action, and built with intention β something designed to carry what mattered most: his people, his purpose, his peace, and his future. Thatβs the kind of leadership this moment calls for.
You donβt have to figure this out alone. The tools are here. The framework is yours. The decision is whether to build before the pressure hits or react once itβs already underway.
Youβve done everything right. You have a fast website with comprehensive content, pages ranking in the top 10, and a strong backlink profile. Yet when you search the query you rank for, your site doesnβt appear in Googleβs corresponding AI Overview.
This is a retrieval problem, not a ranking issue. And the difference between the two is the most important shift SEOs need to understand right now.
AI Overviews donβt work like traditional organic rankings. Instead of considering which page has the most signals, AI Overviews look for the page that gives the cleanest, most usable answer.
If your content doesnβt meet that standard, your traditional search ranking is irrelevant. Hereβs whatβs going wrong, and how to fix it so your content appears in more AI Overviews.
The overlap between AI Overview citations and organic rankings grew from 32.3% to 54.5% between May 2024 and September 2025, according to a BrightEdge study.
This trend sounds encouraging. But it also means that even at peak convergence, nearly half of all AI Overview citations come from pages that donβt rank at the top of organic results. Google actively bypasses higher-ranking pages when it finds content that better serves the AI Overview format.
The pattern varies sharply by sector, though. BrightEdge data shows that in ecommerce, the overlap barely changed, remaining essentially flat over the entire 16-month period. And in your money or your life (YMYL) categories like healthcare, insurance, and education, the overlap between AI Overview citations and organic rankings ranges from 68% to 75%.
Ranking and visibility are no longer the same thing. You can rank second and be invisible. Or, you can rank on the second page and be the first thing a searcher reads.
Dig deeper: 7 hard truths about measuring AI visibility and GEO performance
Informational queries β specifically long-tail and conversational searches β typically trigger AI Overviews. Informational queries drive 57% of AI Overviews, while commercial queries trigger this AI feature far less frequently, according to Semrush research.
Googleβs AI engineΒ looks for content that matches what the user asks, not just the keyword youβve targeted. So, an AI Overview answering the query βwhatβs the best way to manage a remote teamβs workload?β probably wonβt cite a page that ranks for the keyword βproject management softwareβ and leads with features and pricing.
If your introduction spends three paragraphs establishing context, warming up the reader, or restating the question before answering it, the retrieval system moves on. It seeks information it can extract cleanly. If that answer isnβt near the top of the page, the system skips that page.
Traditional SEO content is built around comprehensive long-form content: 3,000-word guides covering every angle of a topic, written for readers who scroll and skim.
AI retrieval systems donβt work the same way. They need to identify discrete, self-contained answers within your content.
That requires clear heading hierarchies, short paragraphs, and content that AI systems can extract. A section under a specific heading should completely answer the question posed in that heading, without requiring the surrounding context to make sense.
Content written as one long, unbroken narrative is harder for AI systems to parse. Even if every word is accurate and authoritative, it may not earn a citation if the structure doesnβt help the retrieval system identify individual answer units.
Dig deeper: AI Overview citations: Why they donβt drive clicks and what to do
Google has been clear that experience, expertise, authoritativeness, and trustworthiness (E-E-A-T) signals are important for content quality in traditional search. It likely matters for AI Overviews, too. But these signals need to appear in the content itself, not just in your domain profile or link graph.
Strong domain authority counts for less than youβd think if the content itself carries no credibility signals.
A retrieval system evaluating an individual page doesnβt know your domainβs track record. The page must make the case for itself.Β
Content-level E-E-A-T signals are particularly important in YMYL categories, where AI Overviews are selective about sources because the risk of misinformation is higher.
Before optimizing your content for AI engines, itβs worth checking whether your target queries trigger AI Overviews at all. As of late 2025, AI Overviews appear in 16% of search results, though that figure isnβt evenly distributed across query types.
Transactional queries, navigational searches, branded queries, and highly local searches are far less likely to trigger an AI Overview. If most of your traffic comes from commercial or transactional keywords, the lack of AI Overview citation may not be a content problem. It may simply be that those query types are less likely to generate overviews in the first place.
The stakes are significant. Research by Seer Interactive shows that organic click-through rates (CTRs) for informational queries that displayed AI Overviews dropped 61%, from 1.76% to 0.61%, between June 2024 and September 2025. Paid CTR fell even further, from 19.7% to 6.34%.
But the same research reveals a critical asymmetry: Brands cited in AI Overviews saw 35% higher organic CTR and 91% higher paid CTR than when they werenβt cited. A citation in an AI Overview doesnβt just protect you from a CTR decline. It actively amplifies your visibility.
The Pew Research Centerβs study of searches by U.S. adults in March 2025 found that only 8% of users who encountered an AI Overview clicked a traditional search result, compared to 15% who clicked when no overview appeared. And 26% of searches with AI Overviews resulted in no clicks at all.
If AI Overviews appear for your most valuable queries and you arenβt cited, you arenβt just missing out on the overview. Youβre losing clicks you previously received from the organic listing underneath it.
These trends require you to adjust how you think about content structure and intent. Hereβs where to focus:
Dig deeper: Want to beat AI Overviews? Produce unmistakably human content
What AI Overviews represent is something thatβs been discussed for years, but few have truly prepared for: the separation of content quality from ranking signals.
For two decades, we used rankings as a proxy for quality. High-ranking content was, by definition, good enough.
But that assumption no longer holds. Ranking in traditional search indicates that your brand has authority and that your page is relevant to the search query. It says nothing about whether your content is structured in a way that AI retrieval systems can use.
Visibility now goes to whoever understands how AI systems identify, extract, and surface answers. A strong backlink profile wonβt help you if the answer is buried on page three of a 4,000-word guide.
Ranking in the top 10 is still worth pursuing. But itβs no longer the whole game.
Linux use amongst PC gamers is growing, and Valveβs Steam Machine isnβt even out yet Valve has released its March 2026 Steam hardware survey, and it is clear that Linux adoption continues to grow among gamers. Now, Linux use has reached an all-time high of 5.33% of Steam users. This month, Linux has over twice [β¦]
The post Linux use hits an all-time-high on Steam, passing 5% user share appeared first on OC3D.
ClawCloud provides fully managed hosting for OpenClaw, giving you a private, always-on AI assistant with no setup. Each plan includes a dedicated, isolated instance that stays online 24/7 while the team handles updates, security, scaling, and daily backups. Just log in and start using your assistant to automate tasks across email, code, the browser, files, and more, with priority support available on higher tiers.
Costlix is an AI-powered comparison engine that analyzes pricing, features, and reviews to deliver clear tables and detailed cost breakdowns. It reveals hidden fees, subscription tiers, and long-term value so you can see which option fits your budget. Use it to compare software, electronics, household goods, and travel, with recommendations tailored to your usage.
Google and Back Market's new USB kit makes it easy to install ChromeOS Flex, a free OS to revive your PC or Mac and reduce e-waste.
Your paid social operation is on fire. You know how your audience thinks, the creative process is dialed in, and the results get better every year. Leadership greenlights an expansion to Google Ads β a new channel and, critically, a new source of revenue.
As it turns out, applying that same strategy really just buys you an express ticket to a very difficult conversation.
Google rewards a different kind of thinking. Intent signals and campaign logic are different, and the mistakes that eat at your budget donβt always make themselves clear. Brands that apply their existing Meta playbook often find themselves looking at shiny dashboards and dull balance sheets.
These six common mistakes tend to do the most damage before anyone realizes whatβs happening. Theyβre what we see most often when ecommerce brands come to us after making the move to Google β and they can all be reversed.
You can definitely use Google Ads to support retention and brand defense. The problem is when that becomes your whole strategy.
We see this regularly with brands new to the platform who launch directly into Performance Max. Early ROAS looks strong, and everyoneβs happy. But a few months in, someone asks the right question: Are we actually growing, or paying to capture purchases that were going to happen anyway?
One client we worked with came to us with branded search and retargeting doing the heavy lifting inside PMax β essentially a tax on demand that had already been created elsewhere. Revenue flatlined because, while the ad spend was real, growth was not.
Net-new customer acquisition requires a different setup.
When Google has enormous reach into new audiences, treating it purely as a closing channel leaves most of that opportunity untouched.
Dig deeper: Ecommerce PPC: 4 takeaways that shape how campaigns perform
The SEO toolkit you know, plus the AI visibility data you need.
Paid social experience transfers to Google in some ways, but there are four areas where we see the biggest knowledge gaps.
Ads on social media are an interrupting moment. Ads in search engines meet people as theyβre looking for something you offer. This changes so much about campaign structure, ad copy, and keyword targeting.Β
Upper-funnel terms and lower-funnel terms require different approaches, bids, and landing pages. Collapsing them into a single campaign structure is one of the fastest ways to dilute intent and waste budget on traffic that was never going to convert.
For ecommerce brands running Shopping and retail Performance Max, the product feed is the foundation everything else is built on. Weak titles, missing attributes, and poor categorization limit how often your products show up and who sees them.Β
Most brands (including Google-native ones) underinvest here because the work is unglamorous. But a well-optimized feed consistently outperforms one thatβs neglected after setup.
Paid search is a keyword-driven channel, which makes keyword strategy its own discipline. Understand match types, search volume, commercial intent, and the relationship between what people type and what they actually want. This takes time to develop, but brands that skip this step usually over-restrict their reach or bleed spend on irrelevant traffic.
Sending high-intent but unfamiliar visitors straight to a product page on Google often underperforms. A more engaging landing page format, like an advertorial, puts that traffic in front of context and trust before asking for the sale.Β
Brands coming from paid social often overlook this because the funnel architecture theyβre used to doesnβt require it.
Dig deeper: 7 Google Ads search term filters to cut wasted spend
Googleβs algorithms need consistent data to make the best decisions for your account. But every time a campaign goes dark β for a day or a week β thereβs a risk that the learning resets. What feels like a minor admin issue can mean weeks of degraded performance and wasted ad spend.
Two types of disruption come up more than any other.
They are both preventable with automated alerts, weekly feed audits, and a person or AI agent responsible for monitoring account health between reporting cycles. The cost of oversight is low compared to what happens if you only discover issues after the fact.
The instinct among detail-oriented advertisers is to segment everything because it feels like control on the surface.
But Googleβs automation needs data to make good decisions. When you spread your budget across too many campaigns, each one operates on thin resources and even thinner information. Smart Bidding canβt optimize effectively without sufficient conversion volume, so campaigns stuck below that threshold tend to underperform and stay there.
By over-segmenting, youβve created the appearance of precision while actually limiting the systemβs ability to learn.
The same logic applies to budget. Ten campaigns with a modest shared budget will almost always produce worse results than three well-funded ones. Google needs room to test, adjust, and find the traffic worth paying for. Fragmented budgets donβt allow it to do that.
Build a tighter structure with fewer campaigns, clearly defined goals, and enough budget to compete. This gives the algorithm what it needs while keeping the account manageable enough to oversee effectively.
Dig deeper: How to find and fix the root cause of low conversions
Max Conversion Value is a Smart Bidding strategy that tells Google to spend your budget in whatever way generates the highest total conversion amount β no ceiling, no floor, no efficiency guardrail. Left unsupervised, it will find conversions, but wonβt care what it costs to get them.
For brands new to Google Ads, this setting can trick you into thinking youβre crushing it. Conversion value shoots up in the right direction, making the account appear healthy. The problem surfaces when you look at what you actually spent to generate that value.
Without a target ROAS, Google has no efficiency quotient, and optimizes for volume, not profitability. But the fix is straightforward.
Dig deeper: How each Google Ads bid strategy influences campaign success
When you launch a Google campaign or make a significant change (like doubling the budget), it enters a new learning period. This is the window for gathering data, testing different auctions, and calibrating toward the conversion patterns youβve defined.
Itβs a normal part of how the platform works, and every campaign goes through it.
But the learning period requires a minimum volume of conversions to complete. Google typically needs around 30-50 conversion events in a short window before bidding stabilizes. A campaign thatβs underfunded for this milestone will stay in learning indefinitely.
Itβs a common trap for brands being cautious when testing Google.
Funding a new campaign adequately from the start β even if it means consolidating into fewer campaigns and chasing fewer goals β gives it the best chance of learning fast and delivering accurate results sooner.
Track, optimize, and win in Google and AI search from one platform.
Diversifying away from a single ad platform is one of the smartest moves an ecommerce brand can make once itβs mature enough to fight on two fronts. It removes growth from the anchor of one platformβs algorithm changes, auction dynamics, seasonality, terms of service, etc.
Adding Google to Meta also gives you access to a different kind of demand that is actively expressed rather than passively targeted, which is a meaningful advantage worth building on.
These six mistakes are not reasons you should avoid Google, but a preventative guide to help you approach it with realistic expectations and enough patience to let the system learn. Treating it like a direct analog of what youβre already doing on Meta will make you leave before seeing whatβs truly possible.
If youβre still in the early stages of making this move, my guide on how to expand from Meta Ads into Google Ads is a practical place to start. If youβve seen early success and are now looking for the next layer of optimization, find out how to avoid getting sucked into Googleβs many automation traps.
Google launched a channel performance timeline view in Performance Max. It gives you a clearer breakdown of how Search, YouTube, Display, and other channels contribute to campaign results over time.
Whatβs new. A timeline graph shows channel-level contributions over a selected period, paired with investment and performance filters. You can quickly see which channels are pulling their weight β and which arenβt.
Why we care. Performance Max campaigns run across multiple channels at once, making it difficult to see where your budget is most effective. This gives you a timeline view of channel-level contributions β so if YouTube is underperforming while Search drives most conversions, you can see it without digging through exports or relying on guesswork. You can spot channel-level trends earlier and adjust your asset strategy or budget accordingly.
The big picture. This view gives you a more actionable way to evaluate PMax performance without relying solely on Googleβs automated decisions.
Bottom line. Itβs not full transparency, but itβs a meaningful step in the right direction. You get a cleaner way to spot PMax trend anomalies early and adjust accordingly.
First spotted. This update was first spotted by Axel Falck, Head of Search at Le Mage du SEA, who shared it on LinkedIn.
Tracking your brandβs visibility in AI-powered search is the new frontier of SEO. The tools built to do this are expensive, often starting at $300 to $500 per month and quickly rising from there. For many, that price is a nonstarter, especially when custom testing needs go beyond what off-the-shelf software can handle.
I faced this exact problem. I needed a specific tool, and it didnβt exist at a price I could afford, so I decided to build it myself. Iβm not a developer. I spent a weekend talking to an AI agent in plain English, and the result was a working AI search visibility tracker that does exactly what I need.
Below is the guide I wish Iβd had when I started: a step-by-step playbook for building your own custom tool, covering the technology, the process, what broke, and how to get it right faster.
My goal was to automate an AI engine optimization (AEO) testing protocol. This wasnβt just about checking one or two models. To get a full picture of AI-driven brand visibility, I knew from the start that we had to track five distinct, critical surfaces:
On top of that, I needed to score the results using a custom 5-point rubric: brand name inclusion, accuracy, correctness of pricing, actionability, and quality of citations. No existing SaaS tool offered this exact combination of surfaces and custom scoring. The only path forward was to build.
Here are a few screenshots of the internal tool as it stands. You can see some of my frustration in the agent chat window.
This project was built using vibe coding, a way of turning natural language instructions into a working application with an AI agent. You focus on the goal, the βvibe,β and the AI handles the complex code.
This isnβt a fringe concept. With 84% of developers now using AI coding tools and a quarter of Y Combinatorβs Winter 2025 startups being built with 95% AI-generated code, this method has become a viable way for non-developers to create powerful internal tools.
Dig deeper: How vibe coding is changing search marketing workflows
You can replicate this entire project with just three things, keeping your monthly cost under $100.
This is a development environment that lives entirely in your web browser. Its AI agent lets you build and deploy applications just by describing what you want. You donβt need to install anything on your computer. The plan I used costs $20/month.
This was the backbone of the project. Their APIs let you pull data from all the different AI surfaces through a single, unified system.Β
You can get responses from models like ChatGPT and Claude, and pull the specific results from Googleβs AI Mode and AI Overviews. It has pay-as-you-go pricing, so you only pay for what you use.
I also set up direct connections to the APIs for OpenAI (ChatGPT), Anthropic (Claude), and Google (Gemini). This was useful for double-checking results and debugging when something seemed off.
Building with an AI agent is a partnership. The AI will only do what you ask, so your job is to be a clear and effective guide.
Hereβs a repeatable framework that will help you avoid the biggest mistakes.
Before you even open Replit, create a simple text document that outlines exactly what you need. This is your blueprint. Include:
Start your conversation with the AI agent by uploading this document. It will serve as the foundation for the entire build.
This is the most important step. After you provide your requirements, the AI has context. Now, ask it to find the blind spots. Use these exact questions:
That last question is critical. I didnβt ask it, and I lost a whole batch of test results because the agent hadnβt built a database to save them.
Donβt ask the AI to build everything at once. Give it one small task, like βbuild a screen where I can upload a CSV file of prompts.βΒ
Once the agent says itβs done, test that single feature. Does it work? Great. Now move to the next one.Β
This incremental approach makes it much easier to find and fix problems.
Dig deeper: How to vibe-code an SEO tool without losing control of your LLM
When itβs time to connect to an API like DataForSEO, donβt assume the AI knows how it works. Find the API documentation page for what youβre trying to do, and give the URL directly to the agent.Β
A simple instruction like, βRead the documentation at this URL to implement the authentication,β will save you hours of frustration. My first attempt at connecting failed because the agent guessed the wrong method.
Before you ask for a major new feature, save a copy of your project. In Replit, this is called βforking.β New features can sometimes break old ones.Β
I learned this when the agent was working on my results table, and it accidentally broke the CSV upload feature that had been working perfectly. Having a saved version makes it easy to go back and see what changed.
Dig deeper: Inspiring examples of responsible and realistic vibe coding for SEO
Nearly everything will break at some point. Thatβs part of the process. Here are the most common issues I ran into, and the lessons I learned, so you can be prepared.
| Problem | The lesson and how to fix it |
|---|---|
| 1. API authentication fails | The agent will often try a generic method.Β Fix: Give the agent the exact URL to the APIβs authentication documentation. |
| 2. Results disappear | The agent may not build a database by default, storing data in temporary memory instead.Β Fix: In your first step, ask the agent to include a database for persistent storage. |
| 3. API responses donβt show up | You might see data in your API providerβs dashboard, but itβs missing in your app. This is usually a parsing error.Β Fix: Copy the raw JSON response from your API provider, and paste it into the chat. Say, βThe app isnβt displaying this data. Find the error in the parsing logic.β |
| 4. Model responses are cut short | An LLM like Claude might suddenly start giving one-word answers. This often means the token limit was accidentally changed.Β Fix: After any update, run a quick test on all your connected AI surfaces to ensure the basic parameters havenβt changed. |
| 5. API results donβt match the public version | ChatGPTβs public website provides web citations, but the API might not.Β Fix: Realize that APIs often have different default settings. You may need to explicitly tell the agent to enable features like web search for the API call. |
| 6. Citation URLs are unusable | Geminiβs API returned long, encoded redirect links instead of the final source URLs.Β Fix: Inspect the raw data. You may need to ask the agent to build a post-processing step, like a redirect resolver, to clean up the data. |
| 7. Your app isnβt updated | You build a great new feature, but it doesnβt seem to be working in the live app.Β Fix: Understand the difference between your development environment and your production app. You need to explicitly βpublishβ or βdeployβ your changes to make them live. |
Building this tool saved me a significant amount of money. Hereβs a simple cost comparison against a mid-tier SaaS tool.
| Item | DIY tool (My project) | SaaS alternative |
|---|---|---|
| Software subscription | ~$20/month (Replit) | $500/month |
| API usage | ~$60/month (variable) | Included |
| Total monthly cost | ~$80/month | $500/month |
The biggest cost is your time. I spent a weekend and several evenings building the first version. However, I now have an asset that I can modify and reuse for any client without my costs increasing.Β
The hidden costs are real: thereβs no customer support, and you are responsible for maintenance. But for many, the savings and customization are worth it.
Dig deeper: AI agents in SEO: A practical workflow walkthrough
This approach isnβt for everyone. Hereβs a simple guide to help you decide.
Build your own if:
Stick with a SaaS tool if:
For many SEOs, the answer is clear. The ability to build a tool that works exactly the way you do, for less than $100 a month, is a game-changer.Β
The process will be frustrating at times, but you will end up with something that gives you a unique advantage. The era of the practitioner-developer is here. Itβs time to start building.
GOGβs new versions of Capcomβs original Resident Evil games are now available on Steam Capcom has officially released its Resident Evil Classic Collection on Steam, bringing the original PC versions of Resident Evil, Resident Evil 2, and Resident Evil 3: Nemesis to PCβs most popular platform. These classic game re-releases were co-developed with GOG and [β¦]
The post The Resident Evil Classic Trilogy has arrived on Steam appeared first on OC3D.
FamilyFeed is a shared organizer where families manage shopping, medicines, travel lists, appointments, todos, and event plans in one place. Smart bots monitor this family data and generate helpful reminders and insights, like medicines running out, tasks needing attention, or upcoming events. The app is designed for the whole family, from kids to grandparents. It includes AI features like image scanning to create items quickly, smart tools such as cloning lists or event plans, and unique layouts like Checkout View for shopping lists and Chat View for appointments.
Cloudflare's WordPress competitor EmDash may be the future of CMSs, but there are six reasons why it's not that CMS today.
The post 6 Reasons Why Cloudflareβs EmDash Canβt Compete With WordPress appeared first on Search Engine Journal.
Pet Video is an AI pet video generator that turns your pet photos into shareable short videos in seconds. Upload a cat or dog photo, choose from over 50 trending styles like Woolen Pet or KβPop Dance, and instantly download HD results ready for TikTok, Instagram Reels, or YouTube Shorts. It includes dedicated cat and dog generators, effortless sharing, and a gallery of viral effects to inspire your next post.
Glowlytics is an AI-powered skin health tracker that helps you understand acne, sun damage, and inflammation with insights grounded in dermatology research. Built by doctors, it analyzes daily images to surface Skin Signals, track scores over time, and deliver evidence-based, privacy-first guidance to support your routine without offering diagnoses.
Maxxmod is an upcoming browser extension that upgrades YouTube with 200+ controls that shape how you watch and browse. Configure player behavior, speed, quality, volume, and captions, and use tools like Focus mode, volume booster, screenshots, Picture-in-Picture, and frame-by-frame to fine-tune playback. Clean up search and feeds by hiding Shorts, promos, premieres, and other distractions, all from a centralized admin with live previews.
Sign up at maxxmod.com to get notified at launch.
Maxxmod will offer 150 features on the free plan and 50 more on Pro.
CleanSmart streamlines data cleaning by automatically removing duplicates, standardizing formats, and filling missing values so you can export with confidence. Use SmartMatch for precise merges, SmartFill to predict gaps, AutoFormat to fix capitalization and phone numbers, and LogicGuard to flag outliers and impossible values. The platform encrypts data end-to-end, isolates each customer, and scales to 10,000+ records per minute, letting you upload a file and watch your Clarity Score rise.
Interactive pixel-level editing and consistent storyboards
5-minute philosophy audio lessons to elevate your spirit
Real-time multi-agent AI that debates itself to find truth.
Build and run your business while you sleep.
Prepare your Mac screen for calls, demos, and captures
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Speak your prompts into Claude Code
Your friendly screen guide for any task!
A Tamagotchi for your desktop, terminal, and AI agents
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Agentic AI copilot built for WordPress
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Know your gaps. Close them. Before it matters.
Run AI coding agents from your phone
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