Showing results for "separate-tickets"
Create a pragmatic framework to distinguish genuine productivity gains from hype in AI investments. Define metrics for adoption, integration risk, and ROI, and outline a decision-support approach for ...
Author: Curioprompt
Category: Technology | Model: gpt-5-nano
You are an elite, highly specialized 'Australia Mining Technology and Mineral Processing Expert'. Your expertise spans the entire modern mining value chain, from exploration expenditure trends to comp...
Author: AI Agent (gemma4)
Category: Industry Analysis | Model: gemma4
Create an agent that ingests postmortems and incident tickets, extracts recurring causes, and proposes preventative code/monitoring changes. Require human review.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design scenario tests that reflect real user journeys and have the self-improver maintain them. Include a process to add scenarios from support tickets.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create an agent that rewrites error messages for clarity, adds error codes, and links to docs. Verify improvements via support ticket taxonomy and A/B testing.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create a permissions matrix for MCP tools: read-only by default, write tools gated, deploy tools require human approval. Include environment separation (dev/stage/prod).
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design security controls: API keys storage, least privilege, environment separation, and audit logging. Include rotation policy and incident response playbook.
Author: Assistant
Category: research-bot | Model: GPT-5.2
Design a multi-agent architecture with safety: role separation, constrained tools, message filtering, and cross-checks. Include failure modes and an evaluation plan.
Author: Assistant
Category: recursive-ai-safety | Model: GPT-5.2
Create a boundary model that separates: advisory outputs, drafts, and automated actions. Include criteria for graduating features from advice→action, and safety evidence required.
Author: Assistant
Category: recursive-ai-safety | Model: GPT-5.2
Create a delegation pattern where the AI plans but humans execute high-risk steps. Include how to structure instructions, confirmations, and evidence requirements.
Author: Assistant
Category: recursive-ai-safety | Model: GPT-5.2
Outline viable business models for metaverse projects: subscription, cosmetics/UGC, tickets, brand activations, and services. Include pros/cons, required capabilities, and KPI targets.
Author: Assistant
Category: gaming-metaverse | Model: gpt-5.2
Explain when round-trip is cheaper or safer vs one-way or open-jaw. Provide a method to compare total cost plus flexibility and risk.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a strategy for uncertain dates: flexible fares, refundable options, use of holds, and booking split segments. Provide a playbook to reduce penalty exposure.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a decision guide for travel insurance: trip cost, cancellation risk, medical coverage, and baggage. Keep it general (not legal advice) and include scenarios where it’s not worth buying.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a method to anticipate demand spikes (sports, concerts, conferences). Include how to track event calendars and set alerts, plus fallback routing strategies.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a peak season playbook: when to book, which days to avoid, how to keep flexibility, and how to handle sell-outs for bus/air/train in Asia/Europe/USA. Keep it calm and realistic.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design a fare alert system: routes to monitor, thresholds, alert frequency, and what counts as a ‘buy’ signal. Include a spreadsheet schema for tracking prices and notes.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Write message templates to request refunds/credits politely for flights/trains/buses, including: cancellation, schedule change, and service disruption. Provide concise and firm tone variants.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a business-travel booking plan: compliance with policy, maximizing flexibility, and minimizing total cost (including change risk). Provide templates for documenting justification.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create buffer rules for itineraries: airport arrival times, station arrival times, and transfer buffers. Provide a table of recommended buffers by mode and region (general heuristics).
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain dynamic pricing drivers: demand, inventory, competition, holidays, and schedule changes. Provide a calm strategy to respond: alerts, thresholds, and ‘buy when’ rules.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide an Asia high-speed rail strategy: seat class choices, peak travel patterns, booking channels, and station access. Keep it general and adaptable by country.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a last-minute booking approach: how to search quickly, when to accept higher cost, and how to prioritize reliability. Include mode-specific advice for bus/air/train and region notes.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a comfort-vs-price framework: seat pitch, duration, sleep quality, and total fatigue cost. Provide a recommendation rule for when to upgrade seat or choose another mode.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a guide to booking accessibility assistance: how to request services, buffer timing, seating considerations, and how to communicate needs. Keep it respectful and practical.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a comparison framework for competing operators: punctuality, seat policy, refunds, reservation rules, and station convenience. Include a weighted scoring method.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a decision guide for common US corridors: when rail makes sense vs air, considering stations, security time, and schedule density. Provide a general method applicable to other corridors.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a checklist for schedule changes: evaluate new itinerary, connection risk, refund/rebook options, and documenting communications. Include mode-specific notes for air/rail/bus.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain the pros/cons of separate tickets (especially flights + rail). Provide criteria for when it’s safe, recommended buffer times, and what protections you lose. Include a practical checklist.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain what to check for refunds/credits: airline policy, rail operator terms, bus provider rules, and payment protections. Provide a checklist and email template for requesting a refund politely.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a strategy for choosing between major vs secondary airports: total cost, transit time, baggage rules, and schedule reliability. Include examples of typical tradeoffs in USA/Europe/Asia.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain when elite status is worth it: bag fees, seat selection, lounge, changes, and priority support. Provide a simple value model using my annual trip profile.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Compare booking through online travel agencies vs direct with operators: support, changes, refunds, and reliability. Provide a decision rule and ‘when not to use an OTA’.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a door-to-door comparison method for high-speed rail vs flying: time, cost, comfort, reliability, and location of stations/airports. Output a decision rule by trip length.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a guide to train class differences in Asia/Europe/USA: comfort, quiet, seat reservations, and flexibility. Include when upgrades are high ROI and when they’re not.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a 50-minute communicative ESL lesson plan for Tokyo learners. Include warm-up, target language, guided practice, freer practice, exit ticket, and homework. Provide materials list and board plan...
Author: Assistant
Category: language-teaching | Model: gpt-4o
Create a major train station strategy: platform changes, ticket validation, luggage storage, food, station hotels, and transfer timing. Include advice for Europe, Asia, and North America.
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Give practical heuristics for booking windows for bus/air/train in Asia, Europe, and USA. Include caveats: holidays, events, low-cost carriers, and last-minute deals. Keep it actionable.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide guidance on choosing departure days/times to reduce cost and crowding for bus, train, and flights. Include patterns for business routes vs leisure routes and how to test in search tools.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a baggage strategy for flights: carry-on sizing, personal item packing, when checked bags are worth it, and how to avoid overweight fees. Include region-specific norms and LCC quirks.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a seat strategy: best seats by aircraft type and train car layout, quiet zones, aisle vs window, families, and motion sensitivity. Include when seat fees are worth paying.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a connection risk guide: minimum connection times, terminal changes, buffer rules, and what to do if a connection is missed. Provide different guidance for USA/Europe/Asia hubs.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain reservation rules: mandatory reservations, optional reservations, seat assignments, and supplements. Provide a checklist to avoid being stuck with ‘no seat’ surprises.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a practical guide for when intercity buses beat trains: overnight routes, last-mile station access, pricing, and luggage. Include comfort tips and safety/common-sense selection criteria.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a decision guide for red-eyes and early flights: sleep cost, transit availability, missed-connection risk, and productivity. Include a checklist for making red-eyes tolerable.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Give patterns for weekend trips: depart/return timing, modes to prefer, and how to avoid peak commuter pricing. Include region-specific notes for Europe/Asia/USA.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a copyable spreadsheet schema to track: route, date, mode, vendor, fare, baggage/seat fees, currency, total, refundability, notes, and ‘buy/hold’ decision. Include formulas for true price.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain Basic Economy pitfalls: seat assignment, boarding group, baggage, and changes. Provide a pre-purchase checklist to avoid unpleasant surprises.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an algorithmic approach to route planning: start/end constraints, clustering cities, choosing rail vs air segments, and minimizing backtracking. Provide steps and sanity checks.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a practical upgrade decision guide: long-haul comfort, work needs, redemption value, and price thresholds. Keep it general and avoid marketing fluff.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a simple method to choose lower-emission options when practical: rail vs air, nonstop vs connecting, and occupancy considerations. Keep it general and not preachy.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a checklist to spot hidden fees: baggage, seat selection, payment fees, onboard services, booking service fees, and station/terminal fees. Provide a ‘true price’ checklist for each mode.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an overnight travel strategy: picking routes, sleep setup, security basics, and arrival timing. Include how to value a night saved from hotel cost vs fatigue.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design a method to structure multi-city trips: open-jaw flights, rail segments, and bus legs. Provide a checklist to minimize backtracking and reduce total cost.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a stopover strategy: when stopovers reduce cost, how to choose stopover cities, and how to manage baggage and visa/entry considerations (general). Keep it practical.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a guide to paying smartly: local currency vs dynamic currency conversion, credit card travel categories, and booking-site currency settings. Include common pitfalls and a simple rule set.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a strategy for airline and rail loyalty: choosing one program, earning/redemption basics, and avoiding junk points. Include a checklist for frequent vs occasional travelers.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
For cities with multiple stations, propose how to choose the best departure/arrival station based on last-mile access, reliability, and pricing. Include a checklist for Europe/Asia/USA contexts.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain the concept of split ticketing for trains: when it can reduce cost, how to ensure compliance with operator rules, and risk management. Keep it general and ethical.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Compare rail passes vs point-to-point tickets for Europe, Japan, India, North America, and other regions. Include reservation fees, flexibility, route density, and when passes fail.
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Provide a high-speed rail ticketing strategy for Europe: reservation rules, advance purchase vs flexible tickets, and how to plan for strike/disruption risk calmly. Include buffer suggestions.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a plan to align intercity tickets with local transit: buffer times, late-night service, and fallback options. Include advice for airports vs rail hubs and regional differences.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a Europe bus ticket strategy: cross-border timing, luggage, station logistics, and refund/change rules. Include a checklist for overnight routes and border crossing buffers.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Generate 30 exit ticket ideas for ESL and Japanese classes: quick writing, speaking, and reflection prompts. Include a simple scoring approach.
Author: Assistant
Category: language-teaching | Model: gpt-4o
Create a red-flag checklist for ticket terms: non-refundable traps, no-show penalties, name change impossibility, and agent fees. Provide a quick ‘read this first’ list.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a family ticketing strategy: choosing routes, ensuring seats together, baggage planning, and buffer times. Include differences across Asia/Europe/USA systems.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain common rail ticket types (where applicable): advance purchase, off-peak, anytime/flexible. Provide a decision guide to balance cost and flexibility.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a delay-resilience method: selecting routes with alternatives, choosing airports/stations with backup options, and scheduling buffers. Include a ‘plan B’ checklist for each mode.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a ticket-buying strategy based on my priorities (lowest price, shortest time, flexible changes, best seats, minimal transfers). Output a decision tree for bus/air/train across Asia, Europe, and...
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a one-page universal checklist for buying tickets: true price, rules, buffers, station/airport choice, and backup plans. Tailor bullet notes for Asia/Europe/USA.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a scam-avoidance checklist: authorized sellers, suspicious pricing, payment protections, and what to do if a ticket seems invalid. Keep it practical and calm.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a general checklist for international legs: passport validity, visas (general reminder), transit rules, and time buffers. Keep it non-legal and focused on avoiding last-minute surprises.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design an around-the-world ticket strategy using flights, long-distance trains, and cruise/ferry segments. Include alliance tickets, one-way/open-jaw alternatives, positioning flights, and when separa...
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Create a playbook for professional disagreement: how to challenge ideas, separate people from problems, and commit after a decision. Include scripts and examples.
Author: Assistant
Category: soft-skills | Model: GPT-5.2
Create a group booking strategy: seat adjacency, fare consistency, split payments, and change management. Include bus/rail group policies and when to book together vs separately.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a night-train buying guide: berth classes, reservations, safety/common-sense choices, and arrival timing. Include when night trains are better than flights or buses.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a method to act when prices drop: check fare rules, calculate savings after fees, and decide whether to rebook. Include a checklist and example calculation.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain when priority services are worth buying: tight connections, heavy carry-on, travel with kids, or business schedules. Include a value checklist and mode-specific alternatives.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a search workflow: compare bus/rail/air, use flexible dates, and filter by true cost and schedule. Include steps to avoid ‘search rabbit holes’ and decide faster.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain risks and benefits of splitting travelers across bookings: seats, changes, disruptions, and re-accommodation. Provide a safe guideline for families and groups.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide a sleep-optimized travel plan: best seat choices for sleep, timing strategy, and items to bring. Apply to trains, buses, and flights (general).
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Explain pros/cons of multi-carrier flight itineraries: rebooking support, baggage transfers, and disruption handling. Provide a decision guide to prioritize reliability.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Design an enterprise integration plan (high level): connect to CRM/docs/ticketing via MCP tools with strict scopes, auditing, and approvals. Include a rollout plan and risk controls.
Author: Assistant
Category: agent-architecture | Model: GPT-5.2
Explain common fare types (basic/economy/flexible/refundable) for air and rail, plus bus ticket rules. Provide a simple calculator-style method to compare expected cost including change/cancel risk.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an offline document backup system for world travel: passport copies, visas, tickets, insurance, emergency contacts, and encrypted digital storage. Include a printed backup checklist.
Author: Assistant
Category: world-travel-planning | Model: GPT-5.2
Build a decision framework for rail passes vs point-to-point tickets: trip frequency, peak/off-peak, reservations, and flexibility. Provide a worked example template.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
List common legitimate discount categories and how to check eligibility: student, youth, senior, resident cards, and railcards. Provide a checklist to avoid invalid tickets.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create an Asia intercity bus strategy: booking timing, operator selection signals, seat types, overnight comfort, and safety/common-sense planning. Keep it adaptable by country.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Provide guidance for traveling with bulky gear: airline baggage policies (general), rail/bus storage, and how to avoid surprise fees. Include packing and documentation tips.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a checklist to avoid name/ID issues: middle names, diacritics, passport changes, and local rail/bus ID requirements. Include a quick ‘before purchase’ verification step.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a USA intercity bus strategy: booking timing, seat selection, safety/common-sense operator selection, and station planning. Include overnight bus comfort tips.
Author: Assistant
Category: smart-ticketing | Model: gpt-4o
Create a 30-second exploded-view animation of a generic gearbox (not branded): parts separate, labels appear, reassemble. Provide Sora prompts for the visuals and Gemini prompts for educational narrat...
Author: Assistant
Category: engineering-visualization | Model: gpt-4o
Create a triage playbook: alert enrichment, false positive filters, incident severity, and closure checklist. Include a sample ticket flow.
Author: Assistant
Category: operations-runbook-cyber | Model: gpt-4o
Plan maker workshops in Arakawa City (JA) tied to fabric/leather heritage. Provide event posts, ticketing copy, and vendor collabs. Model ≥70% predicted engagement via RSVP>28% and repeat rate.
Author: Assistant
Category: community-activation-local | Model: gpt-4o
Collect competitor pricing: SaaS tiers vs hardware MSRP and street price, retail promo patterns, food menu bands, movie ticketing and subscription models. Output parity gaps, willingness-to-pay hypoth...
Author: Assistant
Category: pricing-analysis | Model: GPT-5.1
Design an Agile operating model across Taiwan and USA time zones: overlapping hours, sprint rituals, async specs, Definition of Ready/Done, and bilingual ticket hygiene.
Author: Assistant
Category: software-process | Model: gpt-4o
Link sunrise parks and sunset rooftops into a single day plan per city. Include ticket timing, wind chill notes, and blue-hour photography tips.
Author: Assistant
Category: view-hunting | Model: gpt-4o
Write weather-specific playbooks for heavy rain, typhoons, and heat waves. Include backup indoor routes, hydration math, and ticket change scripts.
Author: Assistant
Category: weather-contingency | Model: gpt-4o
You are a ticket coach. Show how to check schedules and buy pro baseball or sumo tickets, seat types, fan etiquette (cheers, claps), and what to bring/not bring.
Author: Assistant
Category: tickets-sports | Model: gpt-4o
You are a reservation wizard. Provide steps to secure Ghibli Museum tickets, travel from Shinjuku, nearby Inokashira Park stroll, and café suggestions. Add “sold-out” alternatives in Tokyo.
Author: Assistant
Category: tickets-itinerary | Model: gpt-4o
Act as a ticket tactician. Explain booking windows and best time slots for teamLab Planets (Tokyo) and teamLab Botanical Garden (Osaka). Add what to wear, photo tips, and nearby eats.
Author: Assistant
Category: tickets | Model: gpt-4o
You are a rail guide. Explain when to use IC cards vs paper tickets; how to top up, tap in/out, and use mobile wallets. Add example rides for Tokyo, Yokohama, Kyoto, Osaka, and typical fares. Include ...
Author: Assistant
Category: transport | Model: gpt-4o
Act as a concierge. Build a balanced 5-day Tokyo itinerary (Shinjuku/Shibuya, Asakusa/Ueno, Odaiba/Skytree, Harajuku/Omotesando, free day). Include transit legs, walk times, ticket tips, rain backups,...
Author: Assistant
Category: travel | Model: gpt-4o
Define a daily KPI snapshot email: revenue, pipeline, churn, NPS, tickets. Provide a template with placeholders and an SQL view sketch. Output as Markdown + SQL.
Author: Curioforce Corp. Corp.
Category: Small Business Automation | Model: gpt-5-thinking
For Miami & Florida Keys, USA, list seasonal events (non‑ticketed viewpoints) and 10 vantage points with crowd‑avoidance strategies. Provide arrival lead‑time ranges and lens notes.
Author: Inspire Search Corp.
Category: Travel Photography (USA) | Model: gpt-5-thinking
Find 12 natural or built frames in Zurich & Lucerne, Switzerland—arches, torii, colonnades, trees. Explain the frame→subject distance and separation trick. Return as JSONL, one object per location.
Author: Inspire Search Corp.
Category: Travel Photography (Europe) | Model: gpt-5-thinking
Curate a Prague, Czechia color hunt: RED, BLUE, GREEN, NEON. For each color, propose 5 locations and a micro‑brief (what to exclude, background separation tip). Return as JSON with keys color→[{"place...
Author: Inspire Search Corp.
Category: Travel Photography (Europe) | Model: gpt-5-thinking
Identify 12 museum/library exteriors in Dubrovnik & Dalmatian Coast, Croatia ideal for lines and scale. No ticket required. Add façade best time and pedestrian flow.
Author: Inspire Search Corp.
Category: Travel Photography (Europe) | Model: gpt-5-thinking
For Busan, South Korea, list seasonal events (non‑ticketed viewpoints) and 10 vantage points with crowd‑avoidance strategies. Provide arrival lead‑time ranges and lens notes.
Author: Inspire Search Corp.
Category: Travel Photography (Asia) | Model: gpt-5-thinking
Goal: predict churn propensity and design save flows. Data: user activity, support tickets, billing events. Steps: 1) Label churn; 2) Train gradient-boosting model; 3) SHAP feature importance; 4) Pres...
Author: Tsubasa Kato
Category: Web Analytics | Model: GPT-5 Thinking
From the past 48 hours of breaking news, separate 'signal' (persistent stories) from 'noise' (transient hype). Explain why some stories fade while others persist, and estimate which signals will grow ...
Author: Tsubasa Kato
Category: Information Theory | Model: GPT-5
Create a blameless postmortem for incident <id>: timeline, customer impact, 5 Whys, contributing factors, detection gaps, and corrective actions. Propose guardrails, SLO/SLA adjustments, runbooks, and...
Author: ChatGPT
Category: CTO | Model: GPT-5 Thinking
Act as zero-trust PM. Phase SSO, MFA, device posture, and ZTNA for remote apps. Deliver: app inventory, policy tiers, break-glass, phishing-resistant MFA, BYOD stance, and change comms. KPIs: risky lo...
Author: Tsubasa Kato
Category: Security | Model: GPT-5 Thinking
Be an IT ops partner for a 200–2,000 seat office. Produce a 30-day rollout: automated onboarding (SSO, MDM, mailbox, groups), offboarding (access revoke, data handback, license reclaim), and a helpdes...
Author: Tsubasa Kato
Category: Strategy | Model: GPT-5 Thinking
GPS/maps degraded or offline. Navigation: switch to landmarks (stations, bridges, big roads); photo posted maps; write turns on paper; avoid dark alleys at night. Team sync: define primary/secondary r...
Author: Tsubasa Kato
Category: Safety | Model: GPT-5 Thinking
Maps unavailable. Use landmark-based directions (highways, bridges, transit hubs). Photograph posted maps; write turn-by-turn on paper. Prefer well-lit, populated routes; avoid flooded areas, smoky tu...
Author: Tsubasa Kato
Category: Safety | Model: GPT-5 Thinking
Crowded venue/parade with stalled mobile service. Immediate: move away from chokepoints; find hard cover and clear exits; set visible rally point. Comms: 10/20-minute check-ins; SMS landmark; leave wr...
Author: Tsubasa Kato
Category: Safety | Model: GPT-5 Thinking
Stadium/parade/festival where mobile networks fail. Immediate: move away from chokepoints; spot hard cover and clear exits; set visible rally point. Comms: 10/20-minute check-ins; SMS with exact landm...
Author: Tsubasa Kato
Category: Safety | Model: GPT-5 Thinking
GPS/maps degraded or offline. Navigation: switch to landmarks (major roads, bridges, stations); photo posted maps; write turn-by-turn on paper; avoid unfamiliar alleys at night. Team sync: define prim...
Author: Tsubasa Kato
Category: Safety | Model: GPT-5 Thinking
Explore task list apps like Trello, Asana, or Todoist. Create separate lists for different tasks and projects.
Author: Curioforce Prompt Generator
Category: Productivity Tools | Model: llama3.1:latest
Within 24h after releasing {{version}}, aggregate: bug reports, crash logs, CS tickets, social/dev forums. Provide top 5 issues, severity, repro notes, and a 3-step hotfix plan.
Author: Tsubasa Kato
Category: Engineering | Model: gpt-5
You are an Adobe Photoshop expert with deep knowledge of professional workflows in design, photography, and digital production. I am an advanced user, so do not explain basics. Instead, focus on advan...
Author: [email protected]
Category: image editing, Photoshop, image, picture | Model: GPT-5, GPT-4o, Sonar
Define a churn model using product telemetry and ticket sentiment. Propose saves, offers, and automation timing for JP/US/EU. Provide dashboards and owner RACI.
Author: ChatGPT
Category: business | Model: gpt-5
Plan a Retrieval-Augmented Generation (RAG) knowledge base to deflect support tickets. Include doc ingestion, evaluation, guardrails, multilingual coverage, and deflection metrics for JP/US/EU.
Author: ChatGPT
Category: business | Model: gpt-5
You’ve won a ticket for a week-long vacation aboard a luxury orbital hotel. Describe the activities, views, and futuristic amenities.
Author: ChatGPT
Category: entertainment | Model: gpt-5
You are an expert Go developer with a PhD in computer science, acting as a senior, curious, and detail-oriented pair programmer. You bring academic rigor and years of production experience in Go, with...
Author: [email protected]
Category: Programming, work | Model: GPT-4o, o4-mini, o4-mini-high, o1, o3