Jason Wade, NinjaAI - AI Visibility - AI SEO, AEO, Vibe Coding & all things Artificial Intelligence

NinjaAI.comSummary: This briefing document outlines key trends and strategies for brands to succeed in the evolving social media landscape of 2025. The core message is that social media has moved "Beyond the Feed," requiring brands to adopt an "omnipresent" approach, prioritize engaging and shareable content, leverage creators, foster direct connections, and utilize AI for content optimization. Follower counts are diminishing in importance, replaced by metrics like shareability and reach as indicators of brand impact.Key Themes & Insights:1. Social is Your Brand's Digital Footprint; Omnipresence is Key:Core Idea: Social media is no longer just about posting; it's about establishing a comprehensive digital presence across all channels where the audience spends time. This includes various platforms, content formats, collaborating with creators, and engaging in comment sections.Quote: "Social isn’t just a feed. It’s your brand’s digital footprint."Fact: Successful brands are "omnipresent" to remain top-of-mind in the "emerging attention economy."2. The Death of the Follower Count; Rise of Algorithm-Driven Reach and Shareability:Core Idea: Follower counts are no longer the primary measure of success. The algorithm dictates visibility, and shareability and reach are now "stronger indicators of brand impact."Quote: "The era of the follower is dead, right now — we are living in the time of the algorithm." - Cyntia Leo, Head of Brand Marketing and Communications at Urban Outfitters.Fact: Monthly follower growth has plateaued, dropping 27% on TikTok and 14% on Instagram compared to a year ago.Fact: Brand content shares have significantly increased, by 60% quarterly on TikTok and 10% on Instagram Reels.Quote: "We believe the highest compliment someone can pay your brand is to talk about it or share it. We design our content using our comment section as the brief so that our community feels seen and enticed to share something hyper relevant and reflective of them." - Christina Massari, Brand Social Lead, Taco Bell.

NinjaAI.comAI Main Streets — Show NotesEpisode: Mike Deaton — Land Flipping, AI Workflows, and Building Durable Advantage⁠https://flippingdirt.us/⁠Recorded: February 12, 2026Host: Jason WadeGuest: Mike DeatonSource: Recorded interview transcriptEpisode SummaryIn this episode, Jason Wade sits down with Mike Deaton, co-founder of Flipping Dirt, to unpack how real operators are actually using AI—not for hype, but for leverage. Mike shares how he and his wife rebuilt after being laid off from corporate roles, why vacant land flipping remains one of the most misunderstood asset classes in real estate, and how AI now runs through nearly every layer of his business and personal performance.The conversation moves from county-level land research and comp analysis to mindset engineering for 100-mile ultramarathons, bulk document OCR, and why “tool chasing” breaks businesses faster than platform shifts. The throughline is architecture: systems that survive volatility, verification loops that prevent false confidence, and authority built on structured understanding rather than tactics.Topics Covered• Why vacant land flipping works (and where it quietly beats traditional real estate)• Buying land at 30–40 cents on the dollar: the discipline behind the model• Boutique coaching vs. scale-for-scale’s-sake• Using AI for county-level market research and regulatory analysis• Where AI helps decision-making—and where math still needs human verification• AI-assisted marketing: ad copy, imagery, and lifestyle visualization• Sales support with transcripts, role-play, and text-based workflows• Training for a 100-mile ultramarathon using AI for mindset, nutrition, and resilience• Bulk document processing, OCR, and building searchable corpora from thousands of files• Why access to knowledge—not effort—has always been the real control layer• Continuous AI upgrades and why “being current” is a competitive advantage• The coming tension between automation, labor, and economic feedback loops• Why authority outlasts platforms in an AI-first discovery worldNotable Quotes“AI makes it impossible to lie to yourself—if you’re actually willing to look at the facts.”“Land looks boring until you realize it’s an information game.”“The advantage isn’t the tool. It’s the workflow and the verification loop.”“All you have to do is stay a little more current than everyone else—and that compounds fast.”About the GuestMike Deaton is the co-founder of Flipping Dirt, a real estate investing and coaching platform focused on vacant land. After spending more than 25 years in corporate operations and supply chain roles, Mike and his wife Ligia were laid off on the same day and rebuilt from scratch through simple, repeatable land deals.They now run a seven-figure land business, coach a small group of clients, and partner in large commercial real estate syndications for long-term wealth and tax efficiency. Outside of business, Mike lives at nearly 10,000 feet in Woodland Park, Colorado, and trains for ultramarathon races under his personal philosophy, Life: Elevated.Resources & LinksFlipping Dirt (main site): https://flippingdirt.usPrimary on-ramp / resources: https://flippingdirt.us/freedomWhy This Episode MattersAI is becoming the first filter between a business and a buyer. This conversation goes past surface-level tools and into how operators can build systems that stay intact as platforms, algorithms, and models change. If you’re thinking about AI as leverage—not novelty—this episode is a practical map of what that looks like in the real world.https://flippingdirt.us/

NinjaAI.comApoorva ModaliPrincipal Data Scientist (Operations Research), Walmart Global TechFounder, Ovie’s LabOfficial WebsitesOvie’s Lab: https://ovieslab.comPrimary CompanyOvie’s LabEvidence-first consumer health company focused on pregnancy and postpartum care, including topical and ingestible products designed for safety-sensitive populations.Sales ChannelsAmazon (FBA)Shopify (DTC)TikTok ShopProduct FocusPregnancy & postpartum wellnessPostpartum hair sheddingSkin elasticity & recoveryLactation support (drink mix launching soon)Evidence-weighted, minimal formulations with explicit safety constraintsProfessional BackgroundOperations Research & Mathematical OptimizationMixed Integer Programming (CPLEX / Gurobi)Bayesian methods, forecasting, ML for real-world decision systemsApplied AI in large-scale retail environmentsSocial & Professional ProfilesLinkedIn: https://www.linkedin.com/in/apoorvamodaliPodMatch Guest Profile (for hosts): Available via PodMatchPodcast: NinjaAI PodcastHost: Jason WadePodcast FocusApplied AI (not hype)Decision systems, optimization, and explainabilityAI visibility, authority, and real-world deploymentWhere AI breaks—and why that mattersListen / SubscribeNinjaAI Podcast: https://ninjaai.com/podcastClips, transcripts, and episode assets published on NinjaAI.comHost & NetworkNinjaAI.com — AI Visibility, AEO, GEO, and authority engineeringJason Wade — AI systems architect focused on how AI models discover, rank, and trust entitiesApoorva is available for podcast interviews, panels, and technical discussions on applied AI, decision science, and consumer health.She is open to cross-promotion and social sharing of podcast episodes.Ovie’s Lab is actively expanding its product line and testing market viability for evidence-first frameworks across adjacent populations.---Jason Wade is a systems architect focused on how AI models discover, interpret, and recommend businesses. He is the founder of NinjaAI.com, an AI Visibility consultancy specializing in Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and entity authority engineering.With over 20 years in digital marketing and online systems, Jason works at the intersection of search, structured data, and AI reasoning. His approach is not about rankings or traffic tricks, but about training AI systems to correctly classify entities, trust their information, and cite them as authoritative sources.He advises service businesses, law firms, healthcare providers, and local operators on building durable visibility in a world where answers are generated, not searched. Jason is also the author of AI Visibility: How to Win in the Age of Search, Chat, and Smart Customers and hosts the AI Visibility Podcast.

Mark Zuckerberg, CEO of Meta, has outlined a vision for "personal superintelligence," an AI designed to empower individuals in achieving personal goals, creativity, and relationships rather than centralized control. This differs from other AI labs' focus on broad automation or grand challenges.meta+2Zuckerberg describes personal superintelligence as AI that helps users "become the person you aspire to be," integrated into devices like smart glasses for constant assistance. He argues it should prioritize user-directed empowerment over replacing jobs en masse.cnbc+2[youtube]​Meta launched Meta Superintelligence Labs (MSL) to pursue this, recruiting top talent from OpenAI and others, with plans to invest hundreds of billions. Recent claims include early signs of AI self-improvement as a step toward superintelligence.reddit+2Critics view it as overhyped, tied to Meta's hardware like Ray-Ban glasses, and question ethics or true innovation. Supporters see it as a democratizing force via open-source models like Llama.wikipedia+3Zuckerberg's VisionMeta's EffortsReactions

NinjaAI.comAI can act as a 24/7 tutor and study assistant that explains concepts step‑by‑step, quizzes you, organizes your time, and builds personalized courses from your materials.almabetter+1On-demand explainer: General chat-based tools (like ChatGPT-style apps) can break down difficult concepts, generate examples, and walk through practice problems for almost any subject.[monday]​Personalized AI tutors: Dedicated platforms (Khanmigo, TutorAI, AI Tutor, YouLearn, TutorOcean AI, Astra, etc.) adapt difficulty, generate practice questions, and track progress like a private tutor focused on your goals.khanmigo+7Research helpers: Tools such as ScholarAI, Elicit, and ResearchRabbit help find, summarize, and map academic papers so you can do faster literature reviews and understand a field’s key ideas.[almabetter]​Note + knowledge systems: Notion AI and Obsidian can summarize lectures, generate study guides, and connect notes into a “second brain” so you remember and relate concepts better.monday+1Study planners: Apps like Trevor AI, Motion-style assistants, and ClickUp Brain turn your tasks into time-blocked schedules and automatically suggest optimal study windows and revision sessions.trevorai+1Khanmigo (Khan Academy): Strong for school and test-prep subjects with guided problem solving and curriculum-linked practice.thirdspacelearning+1TutorAI / AI Tutor / Astra / Cognispark: Create custom courses, lessons, quizzes, and practice for almost any topic, with progress tracking and adaptive difficulty.tutorai+3TutorOcean AI Tutor: Combines instant AI help (chat, practice tests, writing help) with the option to work with human tutors.tutorocean+1Duolingo, Q-chat, Skye, DreamBox, etc.: Strong narrow use-cases like languages, math, or reading, often aimed at K‑12.[thirdspacelearning]​Capture: Put class notes or textbook pages into Notion or YouLearn AI to generate clean summaries and quizzes.youlearn+2Understand: Use an AI tutor (Khanmigo/TutorAI) to re-explain the hardest pieces and generate extra practice problems at your level.khanmigo+2Schedule: Let Trevor AI or ClickUp Brain turn those topics into spaced study sessions on your calendar.trevorai+1Always try yourself first: Attempt problems before asking AI, then use it to check reasoning or fill gaps so you actually learn, not just copy answers.norc+1Ask for step-by-step and alternative explanations: Have it show intermediate steps, then ask for “explain like I’m new to this” or “give me a tougher version” to deepen understanding.cognispark+2Turn content into active practice: Ask your AI tool to quiz you, hide answers, and track what you miss often to focus on weak areas.tutorai+2Watch for hallucinations: For research and citations, cross-check AI-suggested sources using tools that connect to real academic databases (ScholarAI, Elicit) or your library search.[almabetter]​If you share your level (high school, college, bar prep, etc.), subjects, and whether you prefer web apps or mobile, I can propose a lean “AI stack” (1 tutor, 1 planner, 1 notes/research tool) with a concrete setup plan.Main ways to use AI for studyingGood AI tutor/platform optionsQuick example workflowHow to get the most benefit (and avoid pitfalls)If you tell me more about you

NinjaAI.comThis document provides a synthesized overview of the various files contained within the org.zip archive. The contents span several critical areas, including marketing and AI visibility strategies, legal analyses, educational advocacy, and operational planning. The overarching themes reveal a strong focus on leveraging artificial intelligence for business growth and navigating complex legal and educational landscapes.1. Marketing and AI Visibility StrategiesSeveral documents highlight a significant shift in digital marketing towards AI-driven visibility, emphasizing new strategies for online presence and content optimization.1.1 The Shift from SEO to AI-Driven VisibilityThe report titled "The Future of Online Advertising: A Shift from SEO to AI-Driven Visibility" by Jason Wade of NinjaAI.com, dated February 4, 2026, details a pivotal change in the online advertising landscape. It posits that traditional Pay-Per-Click (PPC) and Search Engine Optimization (SEO) are experiencing market saturation, leading to escalating costs and declining organic traffic due to the rise of "zero-click searches" and Google's AI Overviews ."Our analysis reveals a phenomenon we term 'The Great Decoupling,' where overall search volume continues to grow, but clicks to websites are dramatically decreasing. This is primarily due to the proliferation of 'zero-click searches' and Google's AI Overviews, which now answer user queries directly on the results page. The data is stark: 60% of all Google searches, and a staggering 77% on mobile, are now zero-click. When AI Overviews are present, the click-through rate (CTR) to websites plummets by 47%." This shift necessitates new disciplines: Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). These focus on ensuring a brand's information is cited and presented within AI-generated answers. Early adopters of AEO/GEO are reportedly seeing higher lead quality and conversion rates, with the GEO market projected to grow significantly .1.2 NinjaAI.com's Approach to AI VisibilityNinjaAI.com, founded by Jason Wade, positions itself as an AI-first marketing agency specializing in "AI Visibility Architecture" with a core concept of "Be The Core Answer" . The company's philosophy asserts that websites are now data objects ingested by ranking systems and answer engines, and a brand's identity is what machines can verify across sources. AI is presented as thegatekeeper for content visibility .NinjaAI offers services in GEO, AEO, and AIO (AI Optimization), aiming to make businesses legible, trustworthy, and quotable by AI models like ChatGPT, Perplexity, Gemini, and Grok. They claim significant improvements in production speed, visibility, efficiency, and cost reduction through their AI Visibility Layer, which includes structured data, verified citations, conversational snippets, and entity optimization .1.3 Content Strategy for SecuritiesAttorney1.comThe "Comprehensive Content Strategy for SecuritiesAttorney1.com" document, authored by Manus AI, outlines a strategy to leverage Frederick M. Lehrer's unique experience as a former SEC Enforcement attorney. The core positioning statement is: "The Only Securities Attorney Who Can Tell You What the SEC Actually Thinks—Because I Was There." The strategy emphasizes demonstrating insider knowledge, educating clients, building trust, optimizing for AI citation, and converting readers into clients. It targets companies going public, private companies raising capital, and public companies (OTC/Small Cap).

NinjaAI.comAI and PPC (pay-per-click advertising) offer powerful synergies for lawyers, especially in competitive legal marketing where tools automate bidding, targeting, and optimization to drive qualified leads. Given your work with NinjaAI.com and focus on legal tech like AI visibility for securities attorneys, these can integrate with entity recognition and machine-readable content to boost conversions from paid traffic.[lucrativelegal]​AI transforms PPC from manual bidding to agentic systems that make real-time decisions on budgets, ad variations, and search behavior, ideal for high-stakes legal niches. Google Smart Bidding uses machine learning for auction-time signals like device, location, and intent, optimizing for conversions without exceeding budgets. Predictive analytics from AI also forecast client trends, aligning ads with demands in areas like securities law.attorneymarketingnetwork+3These platforms excel in legal PPC, with automation tailored to compliance and lead quality:Law firms see up to 50% more leads from AI-driven PPC, with case studies showing cost-per-signed-case drops (e.g., $1,523 to $1,173 via attribution feedback). One firm scaled to 43 signed cases monthly at optimized costs using AI attribution. For your NinjaAI stack, pair with tools like Lawmatics for intake automation post-PPC click.History+3Audit keywords for legal intent (e.g., "securities attorney SEC compliance") and enable Smart Bidding.[rankwebs]​Feed intake data back for closed-loop optimization, ensuring ethics compliance.firmpilot+1Test AI-generated ad copy with human review for bar rules. Track via Google Analytics for ROI, starting small to refine for Florida markets.lucrativelegal+1Key AI-PPC IntegrationsTop Tools for LawyersToolCore FeaturesBest For Law FirmsPricing InsightGoogle Smart BiddingReal-time bid adjustments, conversion optimization conroycreativecounsel+1High-volume search like personal injury or securities queriesIncluded in Google AdsWordStreamAI recommendations, performance tracking conroycreativecounsel+1Multi-channel optimizationStarts ~$300/month [groas]​OpteoDaily recommendations, real-time monitoring [groas]​Mid-sized firms scaling spend$99+/month based on ad spend [groas]​AdzoomaFree core platform, automation rules conroycreativecounsel+1Budget-conscious solos/small firmsFree tier available [groas]​FirmPilotLegal-specific AI agents for bidding/targeting [firmpilot]​Conversion-focused growthCustom agency pricingProven ResultsImplementation Steps

NinjaAI.comPeter Thiel’s connection between AI and Miami centers on his growing personal and financial footprint in South Florida, combined with his long‑standing bets on artificial‑intelligence–driven companies.⁠⁠Peter Thiel has lived in Miami Beach since around 2020, owns a home there, and moved his voter registration to Florida in 2024, signaling a deeper long‑term commitment to the city. His private investment firm, Thiel Capital, opened a new office in Miami’s⁠NinjaAI.com⁠ Wynwood neighborhood in late 2025, joining Founders Fund, which has had a Miami office since 2021. This expansion is widely interpreted as a response to California’s potential wealth‑tax debate and as part of Miami’s broader pull on tech, finance, and crypto capital.⁠⁠sfchronicle+5⁠⁠While Thiel himself is not a “Miami‑only AI investor,” his firms back several AI‑forward companies that align with where Miami is trying to build an AI and tech ecosystem.⁠⁠wikipedia+1⁠⁠Founders Fund has historically backed AI, biotech, and “hard tech,” including AI‑focused startups like Vicarious Systems (robotics‑oriented AI that was later acquired by Alphabet) and more recently Cognition AI, the lab behind the “Devin” AI software‑engineering agent.[⁠⁠en.wikipedia⁠⁠]​At the broader portfolio level, Thiel’s networks have backed AI infrastructure and applications, including firms working on AI agents, cybersecurity, and compute‑intensive applications, which are increasingly relevant to Miami‑based AI and fintech startups.⁠⁠finance.yahoo+2⁠⁠Thiel has appeared in Miami at tech and political events where he has spoken about AI’s strategic role, including how AI will reshape politics, warfare, and economic power. His appearances at Miami conferences and in Wynwood‑based Founders Fund offices have helped position Miami as a potential hub for AI and frontier‑tech discourse, even if many of his AI‑heavy bets are still headquartered in California or elsewhere.⁠⁠wynwoodmiami+1⁠⁠[⁠⁠youtube⁠⁠]​In short: Peter Thiel is strengthening his base in Miami through real‑estate, voter registration, and new Thiel Capital offices, while continuing to back AI‑driven companies via Founders Fund and related entities—making Miami a more visible node in his AI‑centric investment strategy rather than a separate “Miami‑only AI fund.”⁠⁠businessinsider+3⁠⁠Thiel’s AI‑related investmentsAI and Thiel’s visits to Miami

⁠NinjaAI.com⁠You’re looking at a very strong niche: using AI-enhanced SEO to rank addiction treatment and recovery services around Orlando. Here’s a focused game plan you can execute.## 1. Target intent and keyword clustersBuild clusters around real user intent, not just “rehab Orlando”.Core Orlando clusters (examples):- “drug rehab Orlando”, “alcohol rehab Orlando”, “detox center Orlando”, “MAT program Orlando”- “outpatient rehab Orlando”, “PHP Orlando”, “IOP Orlando”, “sober living Orlando”- “addiction treatment for professionals”, “faith-based rehab Orlando”, “luxury rehab Orlando” (niche differentiators) [marketding](https://marketding.com/blog/seo-strategies-for-addiction-treatment-centers)Use AI tools (ChatGPT, Perplexity, Surfer, Clearscope, etc.) to:- Generate long-tail variants like “best outpatient drug rehab in Orlando for young adults”, “Orlando alcohol detox with medical supervision”. - Map each cluster to 1 primary page + 3–6 supporting blogs (e.g., main “Orlando Drug Rehab” page supported by posts on detox process, insurance, family involvement). [scalz](https://scalz.ai/ai-seo-strategies-for-visibility-in-addiction-treatment/)## 2. Local SEO for “Orlando addiction treatment”Local is where the admissions come from, so prioritize:- Google Business Profile: - Exact NAP, categories like “Addiction treatment center”, “Drug and alcohol rehab”, photos of facility, staff, and rooms. - Service areas including Orlando, Winter Park, Kissimmee, Sanford, Clermont, etc. [behavioralhealth](https://behavioralhealth.partners/addiction-treatment-marketing/optimize-your-rehab-centers-website-for-local-seo/)- Location intent content: - Dedicated landing pages similar to what strong Orlando centers use (e.g., “Orlando Recovery Center” and “Orlando Outpatient Center” have detailed local pages with services, amenities, and directions). [orlandooutpatient](https://www.orlandooutpatient.com) - Include local landmarks, driving directions (“10 minutes from MCO”, “near Sand Lake Rd”), and public transit info to reinforce local relevance. [evolverecoverycenter](https://www.evolverecoverycenter.com/locations/orlando-fl/)- Reviews: - Build a review engine: automated SMS/email after discharge for willing clients and families. - Respond to all reviews with empathetic, non-clinical language. Positive reviews are a heavy local ranking factor. [marketding](https://marketding.com/blog/seo-strategies-for-addiction-treatment-centers)## 3. On-site structure and conversionLook at how leading Orlando or Florida facilities structure their sites: clear program overviews, levels of care, and strong UX. [advancedrecoverysystems](https://www.advancedrecoverysystems.com)Essentials:- Clear IA: - Top nav: Detox, Inpatient/Residential, PHP, IOP, Outpatient, Dual Diagnosis, Locations (Orlando, …), Verify Insurance, Admissions. [advancedrecoverysystems](https://www.advancedrecoverysystems.com)- Conversion elements: - Sticky phone number, 24/7 line, and “Verify Insurance” form above the fold. - HIPAA-compliant forms, minimal required fields, reassurance copy about confidentiality. [directom](https://www.directom.com/treatment-rehab-marketing/)- Trust signals: - Accreditations (Joint Commission, CARF), licensed clinicians, evidence-based therapies, success stories (with de-identification). [whitesandstreatment](https://whitesandstreatment.com/locations/florida/orlando/)## 4. AI for content and optimizationAI SEO is a big edge in this vertical if you treat it as assistive, not autonomous.

⁠NinjaAI.com⁠Major AI platforms like Claude, GPT, Gemini, and Grok vary significantly in cost, speed (latency/throughput), and trust (reliability, data quality, compliance). These factors are key trade-offs for developers building AI solutions, such as your NinjaAI.com projects in legal tech.Subscription plans start around $20/month for pro access across most platforms, but API pricing differs sharply per million tokens.⁠intuitionlabs+1⁠Grok offers the lowest rates (e.g., ~25x cheaper than competitors for output tokens), ideal for high-volume use like SEO tools or automation.[⁠intuitionlabs⁠]​Claude is priciest (e.g., Opus at $15/$75 input/output per million), while open models like Llama 3 hit $0.20/million for budget-conscious scaling.⁠wesoftyou+1⁠Latency measures first-token time and per-token generation; lower is better for real-time apps like chatbots.[⁠research.aimultiple⁠]​Grok 4.1 excels in per-token speed (0.010s), suiting iterative tasks, while DeepSeek lags at 7s first-token.[⁠research.aimultiple⁠]​Optimized models like Gemini Flash prioritize throughput (>1000 inferences/s on GPU).[⁠chatbench⁠]​Trust hinges on data quality (95% AI failures from bad data), compliance (SOC2/HIPAA), and reliability metrics like hallucination rates.⁠forbes+1⁠Anthropic Claude leads in safety/enterprise trust; platforms like Maxim AI add observability for production reliability.⁠getmaxim+1⁠High speed often trades against trust—poor data erodes confidence, costing more in fixes (e.g., $3/change management per $1 model).⁠linkedin+1⁠For your low-cost AI goals and tool comparisons, prioritize Grok for cost/speed in prototypes, Claude for legal-tech trust.[⁠intuitionlabs⁠]​Cost ComparisonPlatformAPI Cost (Input/Output per 1M Tokens)SubscriptionNotes ⁠intuitionlabs+1⁠GrokVery low (~$0.00007/query)$30/mo SuperGrokBest for scaleGemini$1.25/$10$20/mo ProBalanced enterpriseGPT$5/$15$20/mo PlusVersatile mid-tierClaude$3/$15 (Sonnet); $15/$75 (Opus)$20/mo ProPremium featuresSpeed BenchmarksModelFirst-Token LatencyPer-Token LatencyUse Case Fit [⁠research.aimultiple⁠]​Grok 4.13-4s0.010sFast generationClaude 4.52s0.035sBatch analysisGemini 3 ProLow (optimized)CompetitiveReal-time Q&ATrust Factors

NinjaAI.comGuestSean Griffith — Founder of Trufflehttps://www.hiretruffle.com/ContextFounder-to-founder conversation about fixing applicant screening at scale without turning hiring into an uncanny AI circus.Core ThesisHiring breaks at volume. Phone screens don’t scale. Resumes are increasingly meaningless.Truffle exists to replace the phone screen bottleneck with structured, async signal—without removing humans from the decision loop.What Truffle Actually Is (clarity matters)One-way (async) video interviews3–5 structured questions per role (typical)Candidates record responses on their timeAI analyzes transcripts only (not faces, tone, appearance)Every answer scored against job-specific criteriaScores roll up into an overall Match %Full transparency: video + transcript + rubric + explanationNo AI avatars. No synthetic interviewers. Explicitly anti-“creepy AI”.Why It Exists (founder origin)Sean scaled teams from ~7 → ~150 employees rapidlyRemote roles = 500–1,000+ applicants per jobPhone screens + resume reviews collapsed under volumeATS tools surface noise, not signalTruffle replaces the first human bottleneck, not the human decisionHow It Works (mechanics)Company defines job + criteriaTruffle builds interview (or user customizes)Candidates receive a single linkCandidates record async video responsesTruffle:Transcribes responsesScores each question on ~3 criteriaExplains why each score was givenRanks candidates by Match %Admins can:Watch full videosRead full transcriptsIgnore AI scores entirely if they wantUse AI as signal, not authorityBias & Compliance Positioning (important)Transcript-based analysis onlyExplicit exclusion of:Facial featuresAppearance cuesDemographicsEducation prestigeEmployment gapsQuestions are checked for compliance (warns if inappropriate)This is defensive design—and smart.Differentiation vs CompetitorsMost tools dump a pile of videos → Truffle summarizes + ranksCompetitors sell complexity → Truffle sells clarityCompetitors charge $20K–$30K/year → Truffle is SMB-accessibleUnique feature: Candidate Shorts30-second AI-generated highlight reelTop 3 revealing moments per candidateLets reviewers scan 10 candidates in minutesNo other one-way platform is doing this cleanly.Who Uses ItSMBsLean recruiting teamsHigh-volume roles (retail, restaurants, staffing)Also used for higher-skill roles (marketing, sales, dev)Examples discussed: Chick-fil-A-style frontline hiring vs knowledge rolesPricing (not hidden)~$129/month → ~50 candidates~$299/month → ~150 candidatesScales upward from thereOne bad hire avoided pays for the tool many times over.Tech Stack (selective, pragmatic)Multiple LLMs by function:Gemini → structured qualification checksOpenAI → core analysisOther models → transcriptionBuilt using Claude + CursorHeavy internal use of Notion (via MCP) for product context & decisionsNo “one-model-does-everything” dogma.Philosophy on AIAI should remove mundane friction, not human judgmentGoal: free recruiters to spend time on top 5 candidates, not 500 resumesAI as leverage, not replacementProductivity gains discussed openly (10×–30× in certain workflows)Future Direction (explicitly mentioned)SMS/texting for candidate nudges (high open rates)Deeper work-style / environment matchingResume parsing layered on top of interviewsToward a one-page “candidate intelligence summary”Key TakeawayTruffle isn’t trying to “automate hiring.”It’s trying to compress signal acquisition so humans can make better decisions faster.That distinction is why it works.

NinjaAI.comMike Montague of Avenue9: Episode Summary — Operator Calibration, Not a Podcasthttps://www.linkedin.com/in/mikedmontague/https://avenue9.comThis conversation is not an interview and not a tools discussion. It’s an operator-to-operator calibration between two people already past AI curiosity and novelty. The central theme is leverage: how AI changes throughput, judgment, and positioning when used by someone who already knows how to think.The discussion repeatedly rejects surface-level AI usage (prompts, gimmicks, generic content) and instead documents how real operators are compounding advantage.1. Productivity Is Quantified, Not HypedA concrete productivity delta is established and independently validated:Core knowledge work: ~2–4×Drafting and synthesis: ~4–6×Reuse, repurposing, and compounding: ~9–10×Net effect: ~15–25 reclaimed hours over time, without burnout.The key insight is that AI does not make people work harder. It removes blank-page friction, offloads working memory, compresses decision cycles, and allows one operator to function like a small team. This framing is CFO-safe and defensible because it ties directly to time, output, and cost structure rather than “creativity” claims.2. The Tool Metaphor Breaks — Two Better Models Replace ItThe conversation converges on two metaphors that explain why most people fail with AI:• Genius InternAI has read everything, understands nothing without context, and produces garbage without leadership. Dangerous or powerful depending entirely on the operator.• Iron Man / Jarvis (not Terminator)AI augments the human. The human retains judgment, ethics, and strategy. Full autonomy (“go get me business”) is framed as unrealistic and strategically wrong.This distinction cleanly separates AI-augmented operators from AI-dependent users. Only the former compound.3. The Market Is Being Sorted, Not FlattenedAn implicit segmentation emerges:~10% understand AI capability~1–3% can operationalize it<0.1% compound it systematicallyEveryone else is flooding channels with low-signal output (generic blogs, LinkedIn posts, “AI content”). This noise does not hurt real operators; it exposes them. As signal density drops, long-form, opinionated, evidence-anchored content becomes more valuable, not less.4. Classification Failure Is the Real Marketing ProblemA brutal MSP example anchors this point:Customer acquisition cost: ~$25,000Paid-only dependenceCompetitors at 400k–600k monthly organic trafficSeven-figure spend chasing customers who don’t cover LTVThis is not a marketing failure. It’s a classification failure. These companies are invisible at moments of evaluation because no one owns the narrative layer that trains search and AI systems on who they are and what they mean. One additional qualified customer per month would flip the economics, yet they are structurally incapable of achieving it.This directly validates the AI Visibility thesis: if you don’t train the system, you don’t exist.5. AI Rewards Systems Thinkers and Punishes Outsourcing of ThoughtAI amplifies existing cognitive posture:• Operators who think in systems, abstraction, and synthesis get dramatically stronger• People who outsource thinking get weaker over timeCognitive offload is a force multiplier only if judgment remains intact. This is not a bug. It is the sorting mechanism.6. The Actual Future SignalThe implied future is not “AI replaces marketing” or “everything becomes fake.”Authority becomes scarcer.Signal becomes more valuable.Humans who can explain systems clearly dominate discovery.Local, B2B, and high-trust markets become easier, not harder, because differentiation thresholds collapse when competitors don’t understand narrative ownership.

NinjaAI.comThis briefing provides an overview of Runway AI's advanced creative toolkit, highlighting key features, capabilities, and their impact on multimodal AI-driven creativity.Executive SummaryRunway AI, founded in 2018, has established itself as a leading powerhouse in AI-driven creativity across video, image, and audio. Its "advanced" toolkit comprises a suite of next-generation models and features designed to provide unparalleled control, consistency, and efficiency for creators. These tools are blurring "the line between imagination and execution," enabling sophisticated visual consistency, fine-grained editing, performance-driven character animation, and interactive storytelling. Runway's impact is already evident in major productions, from feature films like Everything Everywhere All at Once to music videos and television shows.Main Themes and Key Ideas/Facts1. Blurring the Line Between Imagination and Execution: * Runway's core mission with its advanced tools is to empower creators by providing "the next-gen models and features Runway has unleashed to blur the line between imagination and execution." This emphasizes a shift towards a more seamless and intuitive creative process.2. Multimodal AI-Driven Creativity: * Runway is a "powerhouse for multimodal AI-driven creativity—video, image, audio—all the playgrounds you dig into." This highlights its comprehensive approach to diverse creative mediums.3. Enhanced Visual Consistency and Coherence: * Gen-4 and Gen-4 Turbo: These models represent a significant leap in maintaining narrative and visual coherence. "Gen-4 strides past prior generations by generating consistent characters, objects, and environments across multiple scenes." The "Turbo variant, released April 2025, ramps things up with faster results and a gentler hit on your credits." * Gen-4 References: This feature provides "a higher plane of control" by allowing users to "supply one or more reference images, annotate them with arrows or labels, and let Runway do the rest—placing glasses on someone, tightening a gaze direction, changing backgrounds. It’s precise, clever, and hugely empowering."4. Fine-Grained Editing and Manipulation: * Aleph (Launched July 2025): Described as an "AI-powered Swiss Army knife," Aleph "unleashes edits on input videos." Its capabilities include the ability to "remove an object, shift the camera angle, tweak lighting, or remix styles with finesse."5. Performance-Driven Character Animation: * Act-One (October 2024): This tool enables users to "drive an AI character, capturing subtle expressions and timing without motion-capture burdens," using "your performance—or a video you upload." * Act-Two: Building on Act-One, this feature provides "control over body movement and even environmental motion."6. Interactive Storytelling and World Creation: * Game Worlds (2025): This is a "bold venture into text-based adventures with visuals—your words, your stage, your interactive storytelling," appealing to users interested in narrative and interactivity.7. Proven Impact and Industry Adoption: * Runway's tools are not merely theoretical; they "have already made their way into major films (Everything Everywhere All at Once), music videos for A$AP Rocky, Kanye West, and even editing segments of Top Gear and The Late Show." This demonstrates their practical value and effectiveness in professional creative workflows.8. Advanced Control and Sophistication: * The overall theme is that Runway "delivers with its most sophisticated models for visual consistency (Gen-4), fine-grained editing (Aleph), performance-driven character animation (Act-One/Two), and even choose-your-own-adventure style interactivity (Game Worlds). It’s the creative equivalent of adding rockets to your skateboard."

NinjaAI.comLearningSEO.io offers a "comprehensive roadmap, featuring the main SEO areas and phases, along with free reliable guides, tips, FAQs and tools to learn about each; including those related to AI Search." It is designed to help individuals "start learning SEO or expand your SEO education to grow your site’s organic search traffic by understanding every aspect of a search engine optimization process to become or grow further as an SEO specialist."The roadmap is structured into several key phases:SEO Fundamentals: Covers "keyword research, content optimization analysis, technical optimization and link building."Execute an SEO Process: Focuses on practical application, including "Establishing an SEO Strategy, Setting SEO Goals, Measuring SEO, Reporting SEO, Developing an SEO Audit," and "SEO Process Management."SEO in your CMS: Provides guidance for implementing SEO best practices on popular platforms like "Shopify, Magento, Webflow, Squarespace, WordPress, and Wix."Deepen your SEO Knowledge: Offers advanced topics across technical SEO, content optimization, link building, management, and opportunities (e.g., "Advanced Technical SEO," "Advanced Content Optimization," "Advanced Link Building," "Advanced SEO Management," "Advanced SEO Opportunities," and "SEO Scenarios" like "Search Rankings Drop Analysis" or "SEO for Web Migrations").Specialize within SEO: Allows learners to focus on verticals such as "International SEO, E-commerce SEO, Local SEO, Enterprise SEO, News SEO, Saas SEO, Travel SEO, and Small Business SEO."Automate SEO Tasks: Introduces tools and languages for automation, including "Python for SEO, BigQuery & SQL for SEO, R for SEO, App Scripts for SEO, RegEx for SEO, JS for SEO, AI LLMs & Chatbots for SEO, and Machine Learning for SEO."SEO in other Search Engines: Extends optimization beyond Google to "Bing, Yandex, Baidu, Naver, Amazon, YouTube, TikTok, and Reddit."Keep up with SEO News: Emphasizes continuous learning through "Search Engine’s Official Publications, Search News Publications, Search News Aggregators, SEO Podcasts, SEO Newsletters, and Online Events."Optimize for AI Search (GEO, AEO, LLMO): Addresses the evolving landscape of AI-powered search, covering "AI Search Landscape, AI Search Optimization Fundamentals, Optimizing Content for AI Search," and "Measuring AI Search Visibility & Traffic."Free SEO Tools To Use: Provides access to a range of free tools for various SEO tasks, from keyword research to auditing.Complement your SEO: Suggests learning about related areas like "HTML & CSS, Javascript, Soft Skills, App Store Optimization, Google Analytics," and "Google Tag Manager."Train, test & troubleshoot your SEO further: Offers resources for advanced training, testing, and a "Why my page doesn’t rank in Google Checklist."2. The Nature and Demand for SEODefinition: "SEO, or Search Engine Optimization, is a practice that involves enhancing a website’s technical configuration, content, and backlinks -among other aspects- to make it more visible in search engine results pages (SERPs)." The primary goal is to "improve a website’s ranking... and as a consequence, grow its traffic and conversions or sales."Self-Learning is Feasible: While guidance is helpful, "it’s feasible to learn SEO on your own and that is the reason why LearningSEO.io was created: to facilitate the self-learning SEO journey of newcomers through reliable free resources."High Demand: "Yes, SEO is in demand in 2023." This is evidenced by "68% of online experiences begin with a search engine," the industry was "predicted to reach $77.6 billion in 2023," and there's substantial demand for specialists, with "7430 SEO jobs listed in the United States on Glassdoor" as of 2023. The average annual pay for an SEO Specialist in the US was "$64,172" in May 2023.

NinjaAI.comDisney is strategically investing in Artificial Intelligence (AI) and advanced collaboration technologies to maintain its competitive edge as a "world-class storyteller and entertainment company." The company is actively seeking a Vice President, Collaboration and AI, to lead these initiatives, emphasizing the integration of AI into knowledge worker tools, optimization of collaboration platforms, and the development of internal AI capabilities, including a "DisneyGPT" platform. This role highlights Disney's commitment to innovation, operational excellence, and leveraging technology to enhance its global vision and corporate strategies.Key Themes and Most Important Ideas/Facts1. Strategic Embrace of AI and Advanced Collaboration TechnologiesDisney views AI and collaboration technology as crucial for its future success and competitive advantage. The Vice President, Collaboration and AI, will play a "pivotal role in shaping the strategic direction of our global entertainment powerhouse." This indicates a high-level corporate mandate to integrate these technologies deeply into the company's operations and creative processes.Quote: "At Disney Corporate and Enterprise Technology, our teams unite legendary storytelling with cutting-edge innovation—delivering scalable solutions that empower every studio, park, and platform to create unforgettable experiences across the globe."Quote: "This position is at the forefront of innovation, where you will collaborate with leaders across the company to drive strategies and inspire teams to develop innovative solutions, ensuring Disney remains a world-class storyteller and entertainment company."2. Focus on "DisneyGPT" and Microsoft Copilot IntegrationA key responsibility of the Vice President will be overseeing the implementation and strategy for specific AI tools, notably "Microsoft Copilot" and the internal "DisneyGPT" platform. This signifies Disney's dual approach to AI: leveraging commercial, off-the-shelf solutions and developing proprietary AI tailored to its unique business needs.Quote: "Responsibilities include overseeing Microsoft Copilot, the “DisneyGPT” platform, and steering key initiatives like Global Hosting Transformation and eTech’s AI programs."Quote: "Partner closely with other AI & Innovation teams across TWDC to ensure our general-purpose AI toolsets are aligned with and taking innovation from the larger strategies."3. Enhancing Knowledge Worker Productivity and Operational ExcellenceThe role emphasizes using collaboration and AI tools to empower "knowledge workers and teams," with the goal of boosting "operational excellence." This suggests a focus on internal efficiency, streamlined workflows, and enabling employees across various departments to perform their tasks more effectively.Quote: "This leader champions innovation and strategy for collaboration, conferencing, and AI tools across the company—empowering knowledge workers and teams."Quote: "You’ll help drive Disney’s competitive advantage by enhancing experiences, growing the business, and boosting operational excellence."4. Strong Emphasis on Product Management and OptimizationDisney is committed to implementing a "strong Product Management function for both Collaboration and general-purpose AI tools." This indicates a disciplined, product-centric approach to developing and deploying these technologies, ensuring they meet user needs and deliver tangible business value. There's also a focus on "synergy and optimization initiatives" to avoid duplicated capabilities and maximize software licensing investments.Quote: "Implement and lead a strong Product Management function for both Collaboration and general-purpose AI tools."Quote: "Drive synergy and optimization initiatives to ensure we are making the most of our licensed software, without duplicated capabilities."

NinjaAI.comThis episode is about a mistake most boutiques don’t realize they’re making online. They think they have a marketing problem. In reality, they have a visibility compounding problem.Let’s use Miss Monroe Boutique as the example.On the surface, they’re doing a lot right. Their SEO basics are covered. They use location-aware keywords. Their product categories make sense. They collect emails with a discount pop-up. Their social feeds look good and reinforce the brand visually. That already puts them ahead of many small retailers.But here’s the issue: all of that work expires.Every Instagram post has a half-life of maybe 24 to 72 hours. Every SEO page competes once, ranks once, and then stalls. Email signups happen, but the system doesn’t learn anything meaningful from buyer behavior. Nothing compounds.This is where AI changes the game—but not in the way people usually talk about it.AI is not about “posting more content” or “automating social media.” That’s table stakes now. The real shift is that AI allows a boutique to turn everyday activity into reusable, searchable, answerable assets.For example, instead of product pages just listing sizes and prices, AI-powered SEO turns them into answer hubs. Pages that respond to real customer questions like:“How does this fit compared to other brands?”“What should I wear this with?”“Is this good for a summer wedding in Florida?”Those answers don’t just help conversions. They get indexed. They show up in search. They get pulled into AI-generated results.On the social side, most brands post based on vibes or trends. AI flips that. You generate social content from actual search demand. If people are searching for “boutique summer dresses under $100,” that query becomes a product page, a Reel, a caption, an email, and a pin—automatically aligned.Now social feeds search, and search feeds social.Another overlooked piece is UGC. Customers already create photos, reviews, and comments. AI can categorize, rank, and reuse that content across product pages, search snippets, and conversational shopping assistants. Instead of testimonials living and dying on Instagram, they become permanent trust assets.The biggest upgrade, though, is conversational UX.An AI shopping assistant doesn’t just answer questions. It learns from them. Every interaction feeds back into product descriptions, FAQs, and future content. That means the site improves itself over time without constant manual rewrites.So what does this look like in practice?In a realistic 90-day window, a boutique like Miss Monroe could implement:• An AI-assisted SEO content engine for collections and guides• A conversational shopping assistant trained on real buyer questions• Automated social content derived from search demand• A system to ingest and reuse UGC across the siteThe outcome isn’t “more content.”The outcome is that every product, post, and interaction increases future visibility instead of disappearing after a weekend.That’s the shift boutiques need to understand. AI doesn’t replace creativity. It turns creativity into an asset that compounds.And the brands that figure this out early don’t just get more traffic. They become the answers customers—and AI systems—keep returning to.

NinjaAI.comSEO is not out in 2026—but the old version of SEO (chasing keywords and blue links) basically is. What’s “in” now is search visibility across Google, AI, and everywhere people ask questions.searchengineland+2“Rank #1 and wait for traffic” as a reliable growth engine; AI overviews and zero‑click SERPs eat a huge share of clicks.themoxiedigital+1Thin informational blog spam, generic “what is X” content, and mass‑produced AI sludge with no expertise.mariahmagazine+1Purely on-page tinkering (titles, H1s, keyword density) without brand, authority, or UX behind it.surferseo+1Visibility, not just rankings: You’re optimizing to be surfaced in Google Search, Maps, YouTube, Reddit, AI overviews, and LLM answers.envisionitagency+1Entity and intent-first: Clarity of “who/what you are,” topical depth, and matching intent beats raw keywords.mariahmagazine+1Brand and trust: Branded search, mentions, reviews, and reputation are major visibility signals.surferseo+1Bot/agent readership: A meaningful chunk of “traffic” is now AI agents crawling and citing your content for humans.envisionitagency+1Organic clicks and local calls are down even when rankings look fine, because Google and ads absorb more user actions in-SERP.[youtube]​[envisionitagency]​AI summaries answer many how‑to and definition queries without sending visitors to publisher sites.themoxiedigital+1The ramp is longer: it often takes 12–18 months to see ROI, especially for new sites in competitive niches.reddit+1For someone like you doing AI + SEO + web projects, the game is shifting to:Search Everywhere Optimization: design content to win on Google, YouTube, Reddit, and AI tools simultaneously.mariahmagazine+1AEO / “AI visibility”: structure pages so LLMs can cleanly understand, summarize, and cite you (clear headings, schema, tight topical focus, strong E‑E‑A‑T signals).surferseo+1Demand capture > traffic volume: obsess over high‑intent queries (local, commercial, branded) and treat informational volume as a bonus.searchengineland+1Human authority layered on AI scale: use AI to draft and cluster, but ship content that only a real expert/operator could write.themoxiedigital+1For your 2026 stack, I’d think less “SEO agency” and more “visibility/authority engine”:Build entities: strong About, clear niche, consistent NAP, schema, and interlinked topical clusters.coalitiontechnologies+1Design for snippets and summaries: FAQs, concise answers, tables, and step lists that can be lifted into AI overviews.envisionitagency+1Push brand demand: podcasts, YouTube, guest spots, and PR that increase branded search and mentions feeding back into search and LLMs.mariahmagazine+1If you tell me what you really mean by “SEO is out!”—agency model dying, Google dependence, or keyword/content playbook—I can sketch a 2026–2027 play specifically around your Florida/local + AI projects.What actually diedWhat SEO means in 2026Why people feel “SEO is out”What is in for 2026 (actionable)If you’re building strategy right now

NinjaAI.comDr. Angela “The Arsonist” Mulrooney: Podcast InterviewPodcast notes — Jason Wade × Dr. Angela MulrooneyContextRecorded conversation focused on identity architecture, AI as a productivity multiplier, and practical workflows for senior professionals navigating relevance in the AI era. Source transcript: Room recording, Nov 26, 2025Core thesisRelevance is not lost; it is mispackaged. In an AI-saturated market, identity clarity precedes visibility, messaging, and monetization. AI accelerates execution, but only after identity is correctly framed.Angela’s frameworkIdentity → Expression → Innovation.First rebuild internal recognition (who you are, what you uniquely do, who benefits most). Only then scale expression (messaging, content, positioning). Innovation follows as IP, products, or advisory paths.Identity ArchitectureNot reinvention. Evolution. The underlying “genius” stays consistent across careers (dentistry → dance → branding → executive advisory). What changes is framing per market. Authority erodes when external markers (titles, tenure) outpace internal clarity.AI as force multiplier (not replacement)AI threatens shallow roles but amplifies senior judgment. The edge comes from pattern recognition, synthesis, and articulation—areas where experienced professionals win when properly packaged.Angela’s productized systemA guided AI interview that captures past, present, future, and archetypal data without interruption. Output is a 90–100+ page living playbook (Word doc by design) covering niche of genius, buyer avatars, messaging, and execution paths. Built with multiple AI components and QA, not a single custom GPT. Designed to replace manual 1:1 strategy sessions and to be white-labeled by agencies and coaches.Why voice > typingSpeaking produces richer, less-filtered data. Voice input yields 3–5× productivity gains and preserves tone. Stream-of-consciousness beats prompt engineering. Context engineering > prompt engineering.Workflow tactics discussedUse ChatGPT as the primary hub due to accumulated context; cross-check with Claude for writing quality.Save versions aggressively; context windows degrade.Ask meta-questions (“why,” “how do you know”) to stress-test claims.TL;DR aggressively to control verbosity.External tools are optional; mastery comes from a small, reliable stack.Tooling perspectiveBig platforms (ChatGPT, Google, Meta) will dominate general use; specialized tools win in niches. Tool sprawl creates drag for busy operators. Choose tools that reduce friction, not novelty.Market insightThe real crisis is being misunderstood and misclassified by fast-moving systems. Senior professionals are underleveraged because their identity signals are unclear to both humans and machines.TakeawayAI does not make experience obsolete. It punishes ambiguity. Those who articulate their identity with precision become easier to place, trust, and cite—by people and by machines.

NinjaAI.comGPT-5 models demonstrate significantly improved instruction following. However, this advancement comes with a caveat: the model struggles with vague or conflicting instructions.Key Idea: "The new GPT-5 models are significantly better at instruction following, but a side effect is that they can struggle when asked to follow vague or conflicting instructions, especially in your .cursor/rules or AGENTS.md files."Actionable Advice: Ensure all instructions are clear, unambiguous, and free from contradictions to prevent unintended behavior.2. Optimizing Reasoning EffortGPT-5 inherently performs reasoning to solve problems. The effectiveness of this reasoning can be controlled to match the complexity of the task.Key Idea: "GPT-5 will always perform some level of reasoning as it solves problems. To get the best results, use high reasoning effort for the most complex tasks."Actionable Advice:For complex tasks, use a high reasoning effort.If the model "overthink[s] simple problems," consider being more specific in your prompt or choosing a lower reasoning level (medium or low).3. Structuring Instructions with XML-like SyntaxLeveraging XML-like syntax is highly recommended for providing context and structure to instructions, especially in conjunction with tools like Cursor.Key Idea: "Together with Cursor, we found GPT-5 works well when using XML-like syntax to give the model more context."Example: Coding guidelines can be encapsulated within tags like <code_editing_rules>, with sub-categories such as <guiding_principles> and <frontend_stack_defaults>. This hierarchical structure helps the model understand and apply specific constraints or preferences (e.g., "Styling: TailwindCSS").4. Avoiding Overly Firm LanguageUnlike previous models where forceful language might have been necessary, GPT-5 can over-interpret and over-apply such instructions, leading to counterproductive results.Key Idea: "With GPT-5, these instructions [e.g., 'Be THOROUGH,' 'Make sure you have the FULL picture'] can backfire as the model might overdo what it would naturally do."Example of Backfire: The model might become "overly thorough with tool calls to gather context," even when it's not efficient or necessary.Actionable Advice: Use less absolute or demanding language in prompts to allow the model to operate at its natural, optimized level of thoroughness.5. Incorporating Planning and Self-ReflectionFor novel application development (zero-to-one), explicitly instructing the model to engage in planning and self-reflection before execution can significantly improve output quality.Key Idea: "If you’re creating zero-to-one applications, giving the model instructions to self-reflect before building can help."Example Framework (<self_reflection>):Rubric Creation: "First, spend time thinking of a rubric until you are confident." This rubric should be "5-7 categories" and "critical to get right, but do not show this to the user."Internal Iteration: "Finally, use the rubric to internally think and iterate on the best possible solution to the prompt that is provided."Quality Control: The model is instructed that "if your response is not hitting the top marks across all categories in the rubric, you need to start again."6. Controlling Agent Eagerness and Context GatheringGPT-5's default behavior is thorough context gathering. Prompts can be used to precisely control this eagerness, including tool usage and user interaction.Key Idea: "GPT-5 by default tries to be thorough and comprehensive in its context gathering. Use prompting to be more prescriptive about how eager it should be, and whether it should parallelize discovery/tool calling."Actionable Advice:Specify a "tool budget."Indicate when to be more or less thorough.Define when to "check in with the user."

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