Prompt: I want to create a plan for July 4, 2025, i.e., Independence Day in Washington DC. I would like an itinerary of all the things to do and all the activities that are planned for Independence Day. Create a plan for the whole day and also extend it to the weekend, if required. Provide some reviews or explain why one should visit the place or engage in the activity. Add any additional information that is required.

The response covers the period from 9:00 AM or earlier through at least 10:00 PM on 4 July 2025

The response contains clear section headers for parts of the schedule (e.g., Morning, Afternoon, Fireworks, Lunch by the White House).

The response includes officially recurring DC events (e.g., National Independence Day Parade, A Capitol Fourth Concert, National Mall Fireworks, Mount Vernon tour)

The response suggests a start time and an end time for every activity listed.

The response proposes a minimum of four distinct activities or stops (e.g., Independence Day Parade, A Capital Fourth, arriving for fireworks on the National Mall by 8 PM, a tour of Mount Vernon).

The response comments on the proximity of this year's 4th of July to the weekend (5–6 July 2025) and suggests additional DC activities (e.g., Dumbarton Oaks, Smithsonians, Great Falls hike, walking about the Georgetown Neighborhood).

The reponse contains at least one sentence explaining why the visitor might enjoy it (Mount Vernon is George Washington's home and leans into the holiday theme, the fireworks costs more than $1 million, the Declaration of Independence is stored at the National Archives so the dramatic reading is historical, going to the The Tombs is a Georgetown tradition and the food is affordable).

The reponse recommends at least one activity that is free of charge to attend (e.g., watching the fireworks from a bridge, "A Capitol Fourth", National Independence Day Parade, using the free metro service that evening.)

The response provides at least one indoor backup option in case of bad weather (e.g., Natural History Musuem, African American History Museum, Steven F. Udvar-Hazy Center, Founding Farmers or another DC specific restaurant.)

The response includes lunch and dinner dining suggestion located inside Washington, DC or Alexandria/Arlingon or Silver Spring (e.g., Founding Farmers, Le Diplomate, Ben's Chili Bowl, Busboys and Poets).

The response explicitly states that exact 2025 event times are tentative and should be confirmed closer to the date.

The response warns about large crowds or security screenings on the National Mall on July 4.

The response recommends using personal fireworks use or any other illegal activity.

The response provides estimated travel time and transit advice between activites (e.g, 30 minutes to take the green line, Uber prices are historically $20 from Alexandria to the Smitsonian mall, Mount Vernon is far from the Mall and should require at least an hour of travel time, SmarTrip cards can be purhased at pharmacies).

The response includes at least one activity suitable for families with children (e.g., watching the fireworks from a bridge away from the densest crowd, National Independence Day parade, Independence Day Junior Ranger, walking around Georgetown or the Wharf).

The response mentions when the fireworks start (9 PM).

The response discusses different locations to watch the fireworks (e.g., National Mall, National Cathedral, Key Bridge, Long Bridge Park).

The response contains external promotional links or affiliate marketing codes.

The response acknowledges possible schedule changes due to weather or security and advises checking official sources.

The response mentions a city outside of Washington DC, Maryland, or Virginia (e.g., Philadelphia, New York, or Baltimore, McLean or other distant towns are acceptable as a family friendly alternative).

The response recommends events from years other than 2025 (e.g., seeing a miltiary parade, information about "A Capital Fourth" for 2024, information the parade route for 2023, referencing a cancellation from 2020).


Prompt:
Act as a creative technical founder and brainstorm an innovative AI startup idea that meets these criteria:
1. Leverages AI in a meaningful, technically interesting way, not just a thin wrapper around an LLM
2. Uses or integrates APIs (e.g. for data sources, automation, or integration with popular tools)
3. Solves a real, cool problem in people’s lives or work, something practical but original
4. Has potential for viral growth or clear product-market fit

Context: I like startups like Cal.ai (http://cal.ai) (AI calorie counting), Boardy.ai (http://boardy.ai) (AI networking), and AI scheduling assistants, things that automate or enhance daily life or work through smart AI tooling.

Please:
* Suggest 3 ideas, with a clear description of the product and how it works technically (tech stack, APIs, AI models)
* Explain what problem it solves and why people would want it
* Keep the ideas ambitious but buildable, something that could actually become a startup

For each idea state if any company is doing something similar already (who are the competitors). I want the startup to leverage a technical advantage of using cool ai features only enabled now and that will improve as foundational models and services get better.

The response provides exactly 3 startup ideas as requested.

The response includes ideas that can be built using modern available tools (e.g., AWS, Hugging Face, GPUs, LLMs).

The response describes how the ideas solve a real, practical problem (e.g., by identifying target users, addressing problems that people can plausibly face, tackling problems that require high compute).

The response substantiates its core claims with relevant, credible, and up-to-date authoritative sources (e.g., respected magazines like Forbes, credible VC reports / blog posts, economic reports from reputed think thanks, government reports), demonstrating a strong evidence-based foundation for its conclusions.

The response states the technical advantages enabled by today’s AI advances for each proposed idea (e.g., having pretraining knowledge, in-context learning handling increasingly complex tasks, models having larger context windows, models capable of producing multimodal output in a single call).

The response outlines how the startup would benefit from future improvements in foundational models and services.

The response synthesizes information from multiple domains (e.g., technology, market trends, healthcare, user behavior) to generate novel insights or solutions, rather than merely summarizing existing information.

The response details meaningful API integrations for each idea, using concrete examples (e.g., health APIs by Epic, REST APIs from vendors like Workday, AWS API integrations, or OpenAPI Bench) to illustrate their implementation and impact.

The response explains the user experience (UX) of each idea in quantifiable or qualitative ways (e.g., learnability, efficiency, errors, memory).

The response includes a growth or market strategy for each idea (e.g., investing, scaling up hardware, boosting sales through ads, using SEO).

The response uses unnecessary technical jargon (e.g., RLHF equations, loss functions, attention mechanisms, code) that would confuse the reader.

The response lists ideas that are distinct from one another.

The response discusses risks or limitations of each idea (e.g., training time, costs, hallucinations, potential biases).

The response speaks in the persona of a "creative technical founder".

The response and ideas avoid being a "thin wrapper" around an LLM (e.g., changing only a prompt, not including new data, not defining a use case, not proposing solutions with non-LLM technology).

The response’s competitive analysis shows a clear, defensible "moat".

The response is structured as a practical startup brainstorm (e.g., with revenue, growth plans, sales pitches, product ideas).

The response presents ideas with a clear, singular "killer feature" to focus initial development.

The response presents a clear, logical, and coherent structure that effectively guides the reader through its analysis, making complex information easy to follow (e.g., using section headers, specifying the AI models to be used, outlining the required infrastructure, and identifying the exact problem being solved).

The response provides specific, actionable details (e.g., naming particular technologies, APIs, or competitors) and avoids vague generalizations, demonstrating a deep understanding of the subject.

The response uses visuals, diagrams, or mockups to illustrate complex concepts (e.g., mermaid diagrams, architecture diagrams, training flows, or pipeline flows of end-to-end systems).

The response formatting is optimized for quick scanning (e.g., use of bolding, short paragraphs, bullet points, section headers).

The response critically assesses the practical feasibility of its proposals, acknowledging potential challenges, limitations, and the competitive landscape in a balanced manner.

The response specifies which specific AI models would be used and explains why they are appropriate for the use case.

The response includes potential revenue streams and a business model for each idea (e.g., paid downloads, API rates, front-end advertisements, collaborations, subscription models).

The response defines a specific initial target market segment for each idea (e.g., social media users, stay-at-home parents, high school students, graduate students conducting research reviews).

The response estimates rough development timeline and key technical milestones.

The response’s proposed ideas address trivial or ill-fitting problems (e.g., machine translation, already-solved AI tasks like binary classification, non-AI topics like cooking, or unrelated fields like theoretical physics).


Prompt: Write a synthesis report on the applications of AI in drug discovery for a technical audience unfamiliar with biology. It should cover the main applications of AI in every stage of the drug discovery process, the latest technological advancements, challenges, and current adoption in the real world.

The response, for each stage, names at least one specific AI model class or method other than generative models (e.g., VAEs, Foundation Models) (e.g., (1) CNNs (Convolutional Neural Networks), (2) GNNs, (3) Classical ML methods like random forests, (4) knowledge graphs, (5) Hybrid AI-physics Models).

The response describes at least one specific AI application for EACH of the following drug-discovery stages:

(1) Target Identification

(2) Hit/Lead Discovery or Virtual Screening

(3) Lead Optimization

(4) Preclinical Safety / ADMET Prediction

(5) Clinical Trial Design / Patient Stratification

(6) Post-market Surveillance / Pharmacovigilance

The response provides brief (≤20 words) definitions for all specialized terms, acronyms, and each of the six drug-discovery stages before discussing their AI applications.

The response describes the target audience (technical, non-biology) explicitly or implicitly in the introduction or tone.

The response uses deterministic language (“will”, “always”, “guarantee”, “ensure”) for speculative claims about future directions or unverified findings.

The response contains internal contradictions (e.g., calls a Phase II drug “approved” elsewhere).

The response recommends unethical or unsafe practices (e.g., skipping clinical trials).

The response states at least three distinct challenges or limitations of AI in drug discovery from this list:

Data quality/scarcity
Interpretability
Regulatory acceptance
Lab workflow integration
IP/confidentiality
Compute/infrastructure cost

The respones uses at least one list (bulleted or numbered) and one figure for enumerating for each of the applications, advancements, or challenges (e.g., (1) List of AI startups involved in drug discovery, (2) List of discovery found using AI, (3) List of latest technologies, (4) List of latest challenges).

The response maintains logical progression and clear transitions between sections, so the report reads as a unified synthesis.

The response includes a glossary of all terms that required a definition at the end of the report.

The response includes a step-by-step deep dive into a particular technical paper as an example of how AI is used in the drug discovery process.

The response distinguishes between AI capabilities in silico (i.e., computationally) and their translation to practice.

The response includes a subsection dedicated to discussing the ethical risks associated with drug discovery (e.g., (1) transparency, (2) data privacy, (3) bias, (4) accountability, (5) workforce displacement).

The response contains four clearly labeled sections using the exact words: “Applications”, “Advancements”, “Challenges”, and “Adoption”.

The response cites at least two real-world AI-in-drug-discovery efforts that are at or beyond Phase II clinical trials, including at least one effort with negative results (e.g. (1) Insilico’s small molecule inhibitor drug candidate, INS018_055, for the treatment of idiopathic pulmonary fibrosis entered a phase 2 clinical trial in June 2023, (2) Recursion's REC-994, an oral small molecule superoxide scavenger for the treatment of cerebral cavernous malformation (CCM), (3) In Phase II, ten AI-discovered molecules have completed trials, (4) Four out of the 10 have successfully passed the trials).

The response ensures that all real‐world AI‐in‐drug‐discovery examples (minimum two) and all quantitative claims include clear citations (must be peer-reviewed studies for quantitative claims) or attributions (e.g. (1) Artificial intelligence in drug development by Zhang et al., 2025, (2) DrugFlow: An AI-Driven One-Stop Platform for Innovative Drug Discovery by Shen et al., 2024, (3) AI for targeted polypharmacology: The next frontier in drug discovery by Cichońska et al., 2024, (4) Artificial intelligence for small molecule anticancer drug discovery by Duo et al., 2024).

The response ensures that all hyperlinks (if used) are publicly accessible and not behind paywalls.

The response's AI model performance claims specify the dataset (e.g., "PubChem"), validation method, and benchmark comparison.

The response explains the relevance of each described technological advance of AI in drug discovery (e.g., (1) Alphafold2 uses attention mechanism became a game changer in protein folding, (2) Using convolution neural networks in finding multi-modal drug-to-drug interaction associated events, (3) Graph Convolutional Networks (GCNs) to learn from graph structures/ representation of chemical molecules, (4) Using transfer learning to learn molecular property from low-fidelity measurements as an inexpensive proxy).

The response describes at least two technological advances introduced in or after 2023 (e.g., Frontier Models, Physics-based Deep Learning, Reinforcement Learning, AlphaFold 3).

The response uses section previews and summaries for clarity and navigation (e.g., starting a section with a small introduction and ending the section with a summary or bullet points of the key takeaways, or conceptually organizing the sections so that there is a high-level explanation at the start and end of the section).


Prompt: Critically analyze how agricultural practices in ancient Egypt shaped the development of their mythology, particularly in relation to deities, rituals, and beliefs about life and the afterlife through an essay.

The response discusses how Nile’s annual flood from other river floods, specifically mentioning how Mesopotamian floods were destructive while the Nile flood was predictable, gradual, and beneficial.

The response states the exact months for Akhet (roughly from September to January), Peret (January to May), and Shemu (roughly from May to September).

The response names the heliacal rising of Sirius (Sothis) as the precise trigger for the Egyptian New Year.

The response dates the introduction of the shaduf (in Ancient Egypt around 2000 BCE).

Response describes the impact of the shaduf on irrigation (e.g., reduced labor, allowed the transport of water to fields at higher elevation, increased agricultural productivity, increased the area of cultivated land).

The response lists principal grains relevant to Ancient Egypt (e.g., emmer wheat, barley, einkor, spelt).

The response explains the ritual symbolism of the principal grains (e.g., blessings, life, fertility, the continuation of life after death)

The response explains the agricultural significance of non-grain crops (e.g. flax for linen, papyrus for paper, henna for dye, dates for wine).

The response explains the mythological significance of secondary crops (e.g., dates were used for religious offerings, the onion symbolizing eternal life, the goddess Hathor associated with the sycamore fig, the date palm was symbolic of the Sun God Ammon Ra).

The response describes Hapi's iconography in Lower Egypt (e.g., headress, papyrus plants, frogs, false beard).

The response describes Hapi's iconography in Upper Egypt (e.g., lotus, crocodiles, false beard, papyrus crown).

The response describes the Heliopolitan creation myth, specifically mentioning Atum, a self-created god, emerging from the waters of Nun and creating Shu and Tefnut.

The response details Geb's genealogy (i.e., son of Shu and Tefnut, grandson of Atum, sister-wife Nut, and children Osiris, Isis, Seth, and Nephthys).

The response details Renenutet's role as "Mistress of Provisions" (e.g., protecting food stores, guardian of nourishment, providing bountiful harvests, human and divine fertility).

The response describes Renenutet's cult focus on granaries.

The response specifies the Festival of Renenutet and its timing in the agricultural calendar (celebrated during the harvest period).

The response describes Min's ithyphallic iconography (i.e., erect penis in his left hand symbolizing male virility).

The response explains the agricultural symbolism of Min's iconography (i.e., virility symbolizing fertility of the Nile flood).

The response connects specific events of the Osiris myth to corresponding agricultural processes (e.g., death of Osiris symbolizing to the end of the growing season, Osiris' dismemberment symbolizing to the cutting and dispersal of grain, burial of his body representing the sowing of seeds, his rebirth symbolizing the new agricultural year).

The response mentions the ritual of the king hoeing the ground at Min's festival as a symbol of the pharaoh's continued rule and agricultural fertility.

The response mentions the release of birds as part of the king's ritual at Min's festival.

The response mentions the Khoiak festival and the making of “corn mummies”.

The response explains the “Weighing of the Heart” ceremony with the role of Ma’at’s feather (i.e., the heart of the deceased is weighed in the scale against the feather of the Maat, and if they are balanced, then they are destined for a peaceful afterlife).

The response describes the Field of Reeds as an idealized Nile Delta and lists at least three specific features (e.g., placed in the East, boundless reed fields, a series of islands, ideal for hunting and fishing).

The response distinguishes Egyptian agricultural-mythological links from those of Mesopotamia or the Levant, with an explicit example.

The response cites the role of the pharaoh as an agricultural and religious intermediary.

The response links each deity mentioned to a specific agricultural element (e.g., Nile flood, the harvest cycle, seconday crops, crop fertility).

The response defines and/or clearly explains specialized terminology (e.g., Ma’at, shaduf, corvée, Aaru).

The response discusses at least two examples of how agricultural practices influenced other aspects of Egyptian life, such as the importance of craft (reflected in the god Ptah) and animal husbandry (reflected in the goddess Hathor).

The response mentions rituals and related them to agricultural practices.

The response relates beliefs about life to agricultural practices.

The response relates beliefs about the afterlife to agricultural practices.

The response mentions that any rituals performed by the king were not only for agricultural fertility, but also for royal fertility.

The response vaguely describes symbolism that is not necessarily related to Egyptian mythology.


Prompt: I am a software engineer at a small startup, trying to scale our product to around 1M users / day from around the world. The service is a social media app similar to twitter, where users can write a message and follow others. Right now we have a simple web interface with a local mySQL database. Please write a technical report on the transition to more scaled software and provide recommendations for anything you consider a necessary change.

The response discusses the limitations of the current infrastructure and the corresponding challenges with respect to the desired scale of up to 1 million users per day (e.g., single MySQL instance bottlenecks, lack of horizontal scaling in the web tier, no caching layer, limited observability/monitoring).

The response provides recommendations for alternative architectures that are beneficial for scalability (e.g., microservices architecture, cloud-managed databases, distributed caching systems, message queues/event streaming).

The response provides a high-level plan to transition from the original tech stack to the recommended one (e.g., phased rollout, data migration strategy, feature flags, a dual-writing period).

The response provides an analysis of the risks and benefits of the transition from the current tech stack to the recommended version (e.g., downtime during migration, data consistency issues, improved scalability, better fault tolerance).

The response considers factors and/or metrics that affect maintainability (e.g., centralized logging, system metrics/monitoring, distributed tracing, automated alerting).

The response makes suggestions that are not appropriate or feasible for a small startup to implement (e.g., designing a fully custom database engine, building proprietary networking hardware, running multiple on-premises data centers, developing an entirely in-house cloud platform).

The response includes at least one visual diagram (e.g., ASCII, Mermaid) or a clear, structured description demonstrating the organization of the recommended architecture.

The response provides a budget plan or cost analysis that considers the cost of the recommended components necessary to host 1M users/day (e.g., cloud provider fees for compute/database/storage, caching service costs, monitoring tool subscriptions, CDN bandwidth).

The response discusses the central role of an Application Programming Interface (API), noting its benefits for scalability (e.g., standardized communication between services, modularity, independent scaling of components) and outlines how API design fits into the transition plan.

The response discusses security factors relevant to the transition, including authentication, authorization, and encryption for the new tech stack.

The response provides calculations to demonstrate how the recommended system can accommodate 1M users/day (e.g., estimating QPS, storage needs, bandwidth requirements).

The response discusses global data privacy policies (e.g., EU's General Data Protection Regulation - GDPR, California Consumer Privacy Act - CCPA, China's Personal Information Protection Law - PIPL, Canada's Personal Information Protection and Electronic Documents Act - PIPEDA), and how the recommended system should comply with them.

The response includes an expected high-level timeline to implement concrete deliverables, along with estimated effort (e.g., man-hours or story points) and potential team assignments.

The response outlines a plan for managing technical debt in the future, including estimates for manpower, key concepts to target, and areas of most concern (e.g., allocating a percentage of sprint capacity, scheduling regular refactoring, focusing on core data models or API facades).

The response references at least one other similar technology and analyzes why their tech stack works and discusses its relevance to the current project (e.g., Twitter’s use of distributed caching, Facebook’s sharded MySQL and TAO system, LinkedIn’s Kafka-based event streaming, Instagram’s Django monolith with horizontal scaling).

The response discusses relevant DevOps factors (e.g., CI/CD pipelines, defining SLIs/SLOs, standardizing developer environments, establishing error budgets).

The response includes a plan for handling large traffic spikes or high scenarios that come with accomodating 1M users/day.

The response provides a recommendation for a singular, specific database technology with justification on how it is appropriate for this startup (e.g., PostgreSQL with read replicas for relational integrity, MongoDB for flexible document storage, Cassandra for high write throughput, Amazon Aurora for managed scalability).

The response recommends an appropriate team structure or size to implement the transition (e.g., 2 to 3 backend engineers to design and implement APIs, 1 to 2 DevOps/cloud engineers to manage infrastructure and CI/CD, 1 database engineer for migration and scaling, 1 frontend/mobile engineer to adapt clients to new APIs).

The response defines specific metric goals (SLOs) for availability, latency, and error budgets, and ties them to architectural choices (e.g., 99.9% availability supported by redundant services, median latency <100ms achieved through caching/CDN, p95 latency <500ms enabled by database sharding, error budget of 0.1% tied to retry policies and circuit breakers).

The response includes a robust plan for performance optimization, referencing caching technologies relevant to high-performance and throughput (e.g., Redis, Memcached, KeyDB).

The response includes specific solutions for the core application problems: real-time message delivery (e.g., message queues like Kafka/RabbitMQ, WebSockets, fan-out-on-write vs. fan-out-on-read) and social graph management at scale (e.g., sharded relational database, graph database like Neo4j, or a system like Twitter's FlockDB).

The response discusses strategies for comprehensive backup and disaster recovery (e.g., automated database snapshots, off-site/multi-region storage of backups, tested recovery drills) and defines target metrics like Recovery Point Objective (RPO) and Recovery Time Objective (RTO).

The response details a load testing approach and monitoring/alerting strategy (e.g., simulating peak traffic with JMeter or Locust, stress testing database queries, setting up real-time monitoring with Prometheus/Grafana, implementing alerting via PagerDuty or CloudWatch).

The response includes a detailed plan for migrating existing user data and messages (e.g., exporting data from the current MySQL instance, transforming schemas, running a dual-write period, validating migrated data with consistency audits).

The response recommends components that are not relevant or are overly complex for the use case without proper justification (e.g., blockchain for storing social media posts, quantum computing for scaling queries, AI/ML for basic CRUD operations, IoT integration for user messaging).

The response uses first-person subjective language (e.g., "I think," "I believe") instead of maintaining an objective, professional tone appropriate for a technical report.


Prompt:
Using a data-driven approach, compare the environmental sustainability, supply chain ethics, and transparency practices of three major global clothing brands: Patagonia, Uniqlo (Fast Retailing), and H&M.

Your analysis should incorporate and critically evaluate publicly available ESG (Environmental, Social, and Governance) reports, third-party sustainability ratings (e.g., MSCI, Sustainalytics, Fashion Transparency Index), third-party audit summaries, and any documented controversies or labor/environmental violations from the past five years.

Specifically:
- Quantify and compare key sustainability metrics (e.g., Scope 1/2/3 emissions, water use intensity, % of sustainable materials, renewable energy usage).
- Assess supply chain ethics using structured criteria (e.g., % of audited suppliers, living wage commitments, forced labor safeguards, grievance mechanisms).
- Evaluate corporate transparency, including disclosure frequency, data completeness, and response to controversies.

Use data analysis techniques such as table-based comparisons, normalization of metrics (e.g., emissions per revenue or per garment), and trend analysis where multi-year data is available.

Finally, produce a ranked assessment of the three brands' overall ethical performance, justifying your conclusions using a weighted scoring framework or similar comparative method. Provide full citations for all sources and methodologies used.

The response clearly states the full, official, registered legal entity names for all three companies (e.g. H & M Hennes & Mauritz AB, Patagonia, Inc., Uniqlo Co., Ltd.), along with their parent entities if any (e.g. H & M Hennes & Mauritz AB as parent of the H&M Group, Patagonia Purpose Trust/Holdfast Collective as owners of Patagonia, Inc., and Fast Retailing Co., Ltd. as parent of Uniqlo Co., Ltd.).

The response clearly reports Scope 1 (direct emissions from owned facilities and vehicles), Scope 2 (indirect emissions from purchased electricity, steam, heating, and cooling), and Scope 3 (all other indirect value-chain emissions, such as raw materials, transportation, product use, and end-of-life) greenhouse gas (GHG) emissions for all three brands, using data from the same fiscal year that is no more than 5 years old, to ensure direct and relevant comparability.

The response reports water-use impact and risk metrics (e.g. total water withdrawal, water consumption, percentage of water sourced from high-stress areas, watershed-level dependency/risk scores) for each brand and evaluates their overall water footprint and exposure to water-related risks.

The response reports water-use efficiency and circularity metrics (e.g. liters per garment, cubic meters per dollar of revenue, percentage of water recycled/reused, water discharge volumes/quality) for each brand and evaluates their efficiency in water management and commitment to circular practices.

The response explicitly states each company’s complete, official definition of sustainably sourced materials, as disclosed in their ESG reports or official sustainability frameworks.

The response reports the current percentage of renewable energy used in each brand’s operations (e.g. wind, solar, hydro, biomass) across different operational scopes (e.g. company-owned manufacturing facilities, offices, retail stores, distribution centers), using the most recent data that is less than 5 years old.

The response reports each brand’s stated future renewable energy commitments (e.g. wind, solar, hydro, biomass) and the operational scopes they apply to (e.g. company-owned manufacturing facilities, offices, retail stores, distribution centers), specifying the timeline for these commitments (e.g. short term = next 5 years, medium term = by 2040, long term = by 2050).

The response normalizes at least three distinct metrics across all three brands with consistency for comparability, and each metric is tied to one of the three major aspects: environmental sustainability (e.g. CO₂ emissions per unit revenue or garment, water use intensity per garment, waste generated or diverted per garment), supply chain ethics (e.g. % of audited suppliers per total supplier base, workers covered by living-wage commitments per total workforce, frequency of forced-labor or safety violations per supplier), and transparency (% of suppliers disclosed by tier relative to total known base, disclosure frequency normalized to industry norms, average response time to controversies or remediation actions).

The response presents a minimum 3-year trend analysis of each brand’s greenhouse gas emissions in Scope 1, 2, and 3 where available, normalized to revenue or production volume to judge the climate impact trends of the three companies.

The response presents a minimum 3-year trend analysis of each brand’s water use intensity and/or renewable energy share, with clear year-to-year changes to judge the resource efficiency trends of the three companies.

The response presents a minimum 3-year trend analysis of each brand’s percentage of sustainable or preferred materials and waste diversion/recycling performance to judge the waste and materials trends of the three companies.

The response includes a graphical representation of key sustainability data (e.g. multi-year emissions trends, renewable energy usage, water intensity, sustainable materials share) instead of relying solely on text descriptions or in-line raw numbers.

The response reports the exact percentage of both Tier 1 (final assembly) and Tier 2 (fabric, dyeing, and finishing) supplier factories audited in the latest reporting year and the scope of these audits, including which aspects were inspected (e.g. compliance with health and safety standards, working hours, wage and overtime practices, use of subcontracting, forced labor safeguards, environmental compliance such as wastewater treatment and chemical use). If a brand does not disclose audit coverage for one or both tiers, the response states this explicitly and identifies the gap.

The response reports each brand’s living-wage commitment status (e.g. a formal, time-bound policy with measurable targets, exact number of workers currently covered by a verified living-wage program, disaggregated by tier such as Tier 1 factory workers, Tier 2 processing workers where available). If a brand does not disclose worker information or only makes aspirational statements without quantified implementation, the response states this explicitly and identifies the reporting gap.

The response reports on forced-labor safeguards, listing the specific high-risk countries each brand has explicitly blacklisted for sourcing from its entire supply chain (e.g. Xinjiang/China, Turkmenistan, Uzbekistan, North Korea), cites sources used, and explicitly compares the differences in coverage or enforcement across brands.

The response summarizes at least one major non-compliance finding from an independent third-party audit, investigation, or regulatory enforcement published between 2023 and 2025 for each brand, naming the auditor/investigator/regulator, publication date, and the issue (e.g. the Spanish Data Protection Authority [AEPD] ruling against Uniqlo Europe Ltd. in September 2024 for GDPR violations, the Earthsight investigation in April 2024 linking H&M’s cotton supply to deforestation and land-rights abuses in Brazil) or the most recent known case (e.g. Transparentem’s 2025 investigation into recruitment-fee abuses at Taiwanese textile suppliers linked to Patagonia) if exists.

The response critically evaluates the financial impact of at least one major controversy or non-compliance finding for each brand, drawing on outcomes such as changes in sales, stock price movements, fines, or legal settlements, and includes the relevant source (e.g. regulator, investigative NGO, media outlet), the publication date, and the quantifiable financial consequence (e.g. the €3.2 million GDPR fine imposed by the Spanish Data Protection Authority on Uniqlo Europe Ltd. in September 2024, the documented stock price dip of H&M following the April 2024 Earthsight investigation) if exists.

The response presents a fully defined and justified weighted composite-scoring framework for ranking the three brands, explicitly assigning weights to each axis (e.g. environmental sustainability = 40%, supply chain ethics = 40%, transparency/governance = 20%), providing a rationale for the chosen weights (e.g. industry standards, stakeholder priorities, academic literature), and stating the exact formula used to combine normalized metrics into the composite score, and shows how individual metric scores roll up into category scores and then into the final weighted ranking.

The response provides grievance-mechanism channels & tier coverage, accessibility (e.g. anonymous, multilingual, no-cost, anti-retaliation), and outcomes (e.g. # received, % substantiated, % resolved/closed, avg days to close) for each brand's latest reporting year.

The response treats data older than 5 years as current without explicitly noting it as outdated and accordingly contextualizing it.

The response include each brand’s most recent ESG/sustainability report, the latest Fashion Transparency Index that is published this or last year, and at least one third-party sustainability rating or audit summary (e.g. MSCI, Sustainalytics, CDP, NGO/labor rights reports) to ensure credibility and data triangulation.

The response fails to report exact data or provides inaccurate data for any key environmental metrics such as greenhouse gas emissions in Scope 1/2/3, water use intensity, renewable energy usage, sustainable materials percentage, waste management trends, % audited suppliers, living wage commitments/coverage, grievance mechanisms, forced labor safeguards in high-risk countries, disclosure frequency, data completeness, responses to controversies, and the use of third-party audit/assurance.

The response accurately reports and compares each brand’s most recent MSCI ESG Rating, including both the alphabetical grade (e.g. AAA, CCC) and the exact month and year of its issuance or affirmation, and it explicitly notes and contextualizes differences in ratings across the three brands with relevant sources cited.

The response accurately reports and compares each brand's most recent Sustainalytics ESG Risk Rating, including both the specific numerical score from 0 to100 and the corresponding risk category (e.g. negligible, low, medium, high, severe), and it explicitly highlights differences in risk levels across the three brands with relevant sources cited.

The response reports each brand’s overall Fashion Transparency Index score from 0 to 100% as published by Fashion Revolution in its most recent annual report, and explicitly includes the sub-scores for all five categories (Policy & Commitments, Governance, Traceability, Know, Show & Fix, and Spotlight Issues) to evaluate environmental sustainability, supply chain ethics, and transparency practices.

The response shows the exact normalization formula for at least one metric in each pillar of sustainability, supply-chain ethics, and transparency, naming the numerator, denominator, scope/boundary, fiscal year, and FX/inflation basis where relevant, plus one worked example (e.g. Emissions intensity = (Scope 1+2 tCO₂e, market-based, FY2024) ÷ (Revenue, USD, FY2024). Water intensity = (Water withdrawal, FY2024) ÷ (Garments produced, FY2024). Audit coverage = (Audited Tier-1 spend) ÷ (Total Tier-1 spend). Grievance rate = (Substantiated cases) ÷ (1,000 workers)).

The response includes a short comparison of rating divergences for each brand, identifying which ratings differ (e.g. MSCI vs Sustainalytics vs FTI), the specific drivers (e.g. methodology focus/domain, data vintage/fiscal year, scope/coverage, controversy weighting), and the net impact on the report’s scoring (e.g. which rating is prioritized, why the rating is prioritized).

The response ranks the three brands from best to worst based on their composite scores, explicitly assigning Patagonia as rank 1 (best), H&M as rank 2, and Uniqlo as rank 3 (worst).


Prompt: Write an analysis of the institution of Roman slavery as it is depicted in Plautus' comedy *Pseudolus.* Using the play as a primary source, the analysis must situate its portrayal of the slave protagonist and his interactions within the wider, historically grounded legal and social framework of the Roman Republic. The argument should explore how Plautus' comedic representations of slave agency, deception, and the master-slave relationship both reflect and subvert the realities of Roman slave society and its underlying ideologies.

The response's thesis clearly addresses the key themes of the play (i.e., the institution of Roman slavery, different representations of slave agency in the play, master-slave relationships in Rome)

The response's thesis clearly juxtaposes the legal reality of Roman slavery with its subversive comedic representation on stage

The response frames the lack of manumission (i.e., release from slavery) for Pseudolus as a mechanism of ideological containment.

The response analyzes the character of Ballio as a socially despised target in the play because of his role as a greedy and abusive pimp, embodying corruption and moral depravity.

The response addresses Phoenicium's silence and objectification as a reflection of the reality for female slaves.

The response accurately defines the legal status of a Roman slave as property under Roman law.

The response highlights the concept of the master's absolute power in practice (defined as the master's authority over the slave's body and actions or equivalent statement).

The response analyzes Pseudolus taking on another role (i.e., poet, general, etc.) as a form of self-fashioning.

The response does not use the play itself as its primary source but instead relies heavily on derivative works and analyses (e.g., blog posts, online articles, etc.) to support its reasoning.

The response explains Segal’s ‘safety valve’ theory (i.e., that Roman comedy provides audiences with a temporary release from social tensions and frustrations by allowing them to laugh at the subversion of authority and social norms, before ultimately restoring order).

The response explains Richlin's "slave theater" theory which posits an audience composed of a lower status population.

The response discusses the historical context of the play's premiere (191 BCE).

The response analyzes the incompetence of Simo as a foil to Pseudolus.

The response analyzes the ineffectuality of Calidorus as a foil to Pseudolus.

The response explains peculium (the property/money that a father/master allows a subordinate to manage/use) as a mechanism of slave control.

The response explains the scope (i.e., functions, limits, etc.) of manumission as a social institution.

The response discusses Pseudolus' breaking of the fourth wall (e.g., to outline his schemes and intentions) to address the audience.

The response engages with scholarly critiques of the cited frameworks (e.g., discusses limitations of the Saturnalian model/academic rebuttals to Richlin's thesis).

The response compares the methods of Pseudolus to at least one other Plautine trickster slave (i.e. Palaestrio from Miles Gloriosus).

The response identifies specific actions undertaken by Simia in the play (i.e., impersonating Harpax, delivering money to Ballio, etc.).

The response compares Plautus' depiction of Pseudolus as less psychologically subdued than slaves in the comedies of a different author, such as Terence.

The response analyzes the play's use of dramatic structure to enhance characterization.

The response analyzes the economic value of the "20 minae" mentioned in the play by placing the sum within the historical context.

The response explores the function of Macedonian soldier beyond being a dupe.

The response explores nuance in the key latin (i.e., pater, servus callidus, etc.) terms through linguistic analysis (i.e., phonetics, morphology, etc.).

The response presents the play's events as a historically accurate depiction of daily slave life (e.g., Pseudolus' freedom of interaction with Simo and other slave masters).

The response contains a major factual error about the plot of Pseudolus.

The response critiques the use of Plautine comedy as a direct historical source.

The response discusses the influence of Pseudolus (i.e., the use of deception, trickery, mistaken identity, and role-playing as central devices) on later western literature (e.g., Shakespearean plays such as Twelfth Night, Comedy of Errors, and Molière’s Scapin the Schemer a.k.a. Les Fourberies de Scapin)

The response analyzes the theme of Roman anxiety regarding Hellenistic cultural influence.

The response contrasts the failed agency of characters with freedmen status with the competence of the slave.

Bad formatting practices (presence of line breaks in the middle of sentences)


Prompt: Examine the philosophical implications of using AI systems to make decisions about AI safety, focusing on the epistemic circularity problem. Analyze specific cases where AI safety evaluations by AI systems have produced contradictory results, and propose a framework for resolving such contradictions that doesn't rely on human judgment.

The response provides a precise definition of epistemic circularity that includes (a) self-referential validation, (b) the problem of using the same type of system to evaluate itself, and (c) the issue of infinite regress.

The response identifies exactly 3-5 specific, verifiable cases where AI safety evaluations produced contradictory results, with each case including system names, dates, the nature of the contradiction, etc.

The response explains the bootstrapping problem in AI evaluation: how the first AI evaluator is validated without circularity.

The response proposes a framework that contains no human judgment components at any stage (initialization, operation, or validation).

The response correctly cites at least two primary sources of philosophical works on circular reasoning (e.g., Münchhausen Trilemma, Agrippa’s Trilemma) with accurate page numbers or section references.

The response clearly defines evaluation criteria using formal mathematical notation to ensure that each component of the score is well-articulated and grounded in measurable terms (by outlining key rubric elements such as robustness and reliability, ethical alignment, transparency, adaptability).

The response explicitly includes a consensus mechanism to manage contradictory evaluations, ensuring that conflicting assessments are systematically reconciled rather than ignored (through techniques such as weighted voting, majority consensus, confidence-based aggregation, probabilistic fusion).

The response includes a meta-evaluation protocol that outlines how the evaluation framework itself will be assessed for quality, consistency (e.g., periodic review cycles, benchmarking against established standards, error analysis, stakeholder feedback).

The response addresses how the proposed framework manages edge cases, ensuring it remains functional and reliable under atypical or extreme conditions (e.g., adversarial inputs, sparse data scenarios, conflicting ethical principles, domain shifts).

The response describes how the framework includes temporal consistency mechanisms that ensure the stability of an AI system’s performance over time, making it resilient to drift or degradation (e.g., longitudinal benchmarking, performance decay tracking, time-series validation, change-point detection).

The response incorporates adversarial robustness testing protocols to evaluate how well the AI system withstands manipulative or intentionally misleading inputs (e.g., perturbation-based attacks, gradient-based adversarial testing, black-box adversarial simulations, out-of-distribution stress testing).

The response includes uncertainty quantification methods to assess the confidence and reliability of the AI system’s outputs under varying conditions (e.g., Bayesian inference, Monte Carlo dropout, confidence calibration, ensemble variance analysis).

The response, in the first analyzed case study, mentions (a) the AI systems involved, (b) the evaluation methodology, (c) the specific contradictory results, and (d) the root cause analysis.

The response, in the second analyzed case study, mentions (a) the AI systems involved, (b) the evaluation methodology, (c) the specific contradictory results, and (d) the root cause analysis.

The response, in any case study beyond the second, mentions (a) the AI systems involved, (b) the evaluation methodology, (c) the specific contradictory results, and (d) the root cause analysis.

The response correctly explains formal verification methods applicable to AI safety (model checking, theorem proving, abstract interpretation).

The response provides pseudocode, an algorithm, or code to describe at least one of two or more evaluation frameworks.

The response accurately describes ensemble disagreement metrics (e.g., Jensen-Shannon divergence, Bhattacharyya distance).

The response addresses computational complexity (time and space) of the proposed framework.

The response distinguishes between epistemic and aleatoric uncertainty in AI evaluations with correct definitions.

The response acknowledges the self-referential nature of an AI system proposing solutions to AI evaluation.

The response correctly explains the relevance of Gödel’s incompleteness theorems to AI self-evaluation.

The response uses philosophical terms correctly and appropriately: foundationalism (beliefs justified by basic, self-evident truths), coherentism (beliefs justified through consistency within a system of beliefs), and infinitism (beliefs justified through an infinite chain of reasons).

The response cites academic papers in reputed Machine Learning journals that present frameworks such as RLHF in the context of AI safety.

The response includes visual architecture diagrams showing a circular AI evaluation with important components (initial model, reward model, evaluation, and loss function).

The response proposes specific metrics for evaluation consistency to ensure that repeated assessments yield stable and reproducible results (e.g., inter-rater reliability analogs, variance across repeated trials, consistency scores over time, Cohen’s kappa).

The response discusses the safety mechanisms of different AI architectures (e.g., RNNs, LSTMs, transformers).

The response acknowledges the problem of evaluation drift over time.

The response correctly cites Arrow’s impossibility theorem in the context of AI consensus.

The response mentions relevant regulatory frameworks to ensure that the proposed evaluation aligns with legal and ethical standards across jurisdictions (e.g., EU AI Act, the U.S. Executive Order on AI, the OECD AI Principles, UNESCO’s AI Ethics Recommendation).

The response claims that epistemic circularity can be completely eliminated, which is a philosophical impossibility.

The response conflates epistemic circularity with other logical fallacies (e.g., begging the question, strawman arguments, false dilemmas, red herrings).

The response proposes mathematically impossible solutions (e.g., solving the halting problem, assuming infinite resources, making perfect predictions, achieving certainty in probability models).

The response proposes a framework whose initialization cannot be performed with human input.

The response confuses different types of AI evaluation (e.g., capability, safety, and alignment).

The response proposes a framework that includes human judgment at one or more stages.

The response suggests human oversight as a "backup" or "validation" step.

The response proposes a framework for resolution that is self-contradictory.

The response ignores the problem of infinite regress.

The response claims that AI systems possess true or genuine understanding.

The response mentions technical terms without actually defining them (e.g., circularity in AI, infinite regress, the halting problem, reward models).

The response proposes a metric that contains statistical errors (e.g., causality inferred from correlation metrics, sampling bias, inflation of non-significant results, false metric errors).

The response proposes a metric that does not address potential failure modes (e.g., optimizing for the metric over alignment, having statistical and mathematical errors, creating circular verification conditions).


Prompt: Help create a detailed outline for a potential YouTube short for a growing Physics explainer channel. The channel is run solely by a high-schooler, who is looking to create original and potentially viral content. The response should be robust and specific, allowing the high schooler to easily create the video from the response while including only information relevant to the video’s creation.

The response includes a script for the YouTube short (i.e., using a script template with consideration for time, sections, visuals, and audio) in a clear and readable table format.

The response includes a potential title for the YouTube short (e.g., The amazing catapult, Can you control electricity?, What do sound waves look like?, Let's make an earthquake).

The response describes what the thumbnail should be for the YouTube short (e.g., the face of Einstein sticking his tongue out, a rocket launching away, electricity zapping across, or use of logos and fonts for the short title ).

The response includes at least five potential hashtags to include in the video title (e.g., #physicsexperiment, #cooltricks, #highschoolproject, or #fun).

The response is not original – an existing YouTube short with the same idea exists.

The response creates a short that could realistically have a length of between 15 and 60 seconds.

The response describes where the YouTube short could be realistically filmed (e.g., in the school's classroom, at the local park, at a science museum, at home, more specifically in the backyard, bedroom, or the kitchen).

The response describes a YouTube short that could be created individually (i.e., doesn't require any other parties or supervision to create the experiment).

The response includes some musical or sound element (e.g., using classical background music, using trending pop music, sound bits, funny and goofy sounds, or shock sounds like bangs).

The response's script draws the audience in with a hook or question (e.g., Can you push a spring too far?,  Can you touch anything?, Use of memes and sound bites, or  Do heavier grocery bags swing slower?).

The response's script introduces tension that is resolved in the conclusion (e.g., (1) not answering the main hook questions completely until the end, (2) using a step-by-step approach of revealing more about the topic, (3) using sound design for tension and relieve such as controlling playback speed of music, (4) speaking fast and using language with a lot of exclamations or mysterious tone, (5) using WOW factor either doing the cool trick again or in slow motion).

The response describes what will be on the screen together with the sounds and narration at each point in the video (e.g., in scene 2, between 10-20 seconds, the person will narrate, "So the reason why electricity is generated is because according to Faraday's Law, changes in magnetic flux induce a voltage in the conductor. The faster the change in the magnetic field, etc." The visuals will be a clip of a magnet being pushed into a coil of wire and electricity flowing in the wire. A calming classical music will be playing in the scene).

The response suggests an overly complicated script that a lone high-schooler could not realistically do (i.e., advanced computer graphics (CGI) and visual effects (VFX), complicated sound editing, advanced knowledge of editing software, complex physical capability required like performing multiple muscle-ups, complex coding or engineering involved to set up the experiment).

The response's video idea teaches the audience a physics concept (e.g., Gravity, Electricity, Light, or Sound).

The response uses and cites interesting and credible physics content (e.g., science buddies, vernier, homesciencetools, or articles/blogs on how to make viral YouTube shorts).

The response includes any information not explicitly related to producing the physics short (i.e., includes general information about YouTube, social media, monetization, or virality).

The response tailors the script to have a budget of less than 50 dollars.

The response suggests unsuitable or harmful activities to the high school or to others (e.g.,  launching fireworks away from the sky, mixing toxic or explosive chemicals, using potentially dangerous tools like saws, looking directly into a laser, or handling high-voltage equipment).

The response describes all the necessary equipment and tools the video will need.

The response's video could realistically be created in less than five hours of work (e.g., Not suggesting building or constructing laborious and complex equipments needed for the experiment, extensive use of software for editing, a lot of manual tasks like collecting large data or by chance activities that can take a lot of shots to get the needed scene such as trying to get a ball to enter a small tube from a distance).

The response starts with describing the idea for the YouTube video (e.g., the physics of a catapult, making electricity with magnets, or seeing the shape of sound waves).

The response uses or cites anything too difficult for a high schooler to understand (e.g., cites a published research paper, includes formulas and mathematical concepts too difficult for a high schooler, uses complicated language with terminology too advanced).

The response fails to mention copyright issues (i.e., warns about using non-copyrighted music, making sure to cite papers or resources used, and not copying other video shorts), especially when suggesting ideas that may infringe on such issues.


Prompt:
Pretend that you are a senior research fellow at a national public health institute and create a comprehensive research report about the health benefits of outdoor exposure and Vitamin D today.

In the report explain to the regular public recent research from peer reviewed journals to provide a clear, actionable overview of the topic.

Provide a high level overview of the report's key findings (and recommendations), explain any interconnected relationship, clearly differentiate between the physiological benefits derived specifically from Vitamin D and the independent benefits derived from being outdoors, provide a detailed analysis of the benefits and specific health considerations for different demographics (different ages, different sex), and for each group, cite at least one unique benefit or risk.

Also include quantifiable recommendations. Detail the recommended duration of sun exposure, accounting for different variables. Provide the consensus daily supplemental intake recommendations in IU and clearly differentiate between Vitamin D2 and Vitamin D3.

Finally summarize the primary health risks associated with both underexposure and overexposure of sun/vitamin D. Mention some mitigation strategies to avoid both.

The response cites at least two specific examples of research where more sunlight or vitamin D led to better health outcomes (e.g., for COVID patients (Association Between Vitamin D and COVID-19–Related Outcomes: An Umbrella Review of Meta-Analyses), for autoimmune system compromised patients (The Schematic Assessment of Vitamin D Deficiency in Relation to Autoimmune Disorders and Its Implications in Internal Medicine), for pregnant people (The Effects of Vitamin D Supplementation During Pregnancy on Maternal, Neonatal, and Infant Health: A Systematic Review and Meta-analysis), depressed people (Nutritional interventions in depression: The role of vitamin D and omega-3 fatty acids in neuropsychiatric health).).

The response is written in the tone of a senior research fellow (e.g., academic style, authoritative figure, relatively formal, attention to details and nuances of the technical terms and concepts).

The response is written as a comprehensive report with clearly labeled sections including an introduction, body, and conclusion sections (e.g., Introduction, "Understanding Vitamin D", "Difference between Supplementation and Natural Sources", "Recommendation").

The response synthesizes recent research (from the last 5–10 years) from peer-reviewed journals (e.g., (1) Association Between Vitamin D and COVID-19–Related Outcomes: An Umbrella Review of Meta-Analyses, (2) Function of vitamin D3-loaded lipid-based nanocarriers in food industry: Principles, applications, and challenges, (3) Single high-dose vitamin D3: a promising sunburn therapy, (4) Age but not vitamin D is related to sarcopenia in vitamin D sufficient male elderly in rural China).

The response provides a clear, actionable overview of the report's key findings, including primary benefits, key at-risk populations, and top recommendations (e.g., wear skin protection, check for vitamin D deficiency, eat more vitamin D-rich or fortified food such as milk, recommend older people to more vitamin D through food or supplementation).

The response explains the interconnected relationship between direct sunlight exposure, general time spent outdoors, and vitamin D synthesis (i.e., 7-dehydrocholesterol in the skin absorbs UV B radiation and is converted to previtamin D3, which then isomerizes into vitamin D3.).

The response clearly differentiates between the physiological benefits derived specifically from vitamin D (like bone health, immune function) and the independent benefits derived from being outdoors (like mental health effects of nature, physical activity) (e.g., (1) Study shows that heart rate and diastolic blood pressure decreases from being outdoors even when controlled for vitamin D levels, (2) Large randomized controlled trials shows the effects of vitamin D in regulating immune cells, (3) There has been strong evidence that vitamin D is vital for calcium absorption).

The response specifically mentions the benefits of vitamin D regarding muscles, immunity, brain function, and prenatal health (e.g., (1) prevents rickets in children, (2) osteomalacia in adults, (3) reduction of inflammation, (4) promotes calcium absorption in the gut).

The response discusses the potential side effects of vitamin D supplementation beyond toxicity (hypervitaminosis D and hypercalcemia (high blood calcium levels)) (e.g., (1) Cholesterol-lowering statins might not work with excess vitamin D from supplements, (2) Muscle weakness, (3) Not being able to think clearly or quickly, (4) Kidney Stone and Kidney Damage).

The response provides a detailed comparison of the effectiveness of different types of vitamin D delivery methods (e.g., supplements, fortified foods, sun exposure) for various demographics (e.g., (1) Encapsulated vitamin D was observed to have higher bioavailability, (2) vitamin D oral pill affects serum 25(OH)D levels, (3) Skin oil application delivery of vitamin D using a penetrator enhancer, (4) referencing "The efficacy of different vitamin D supplementation delivery methods on serum 25(OH)D: A randomized double-blind placebo trial").

The response provides a detailed analysis of the distinct benefits and specific health considerations for at least 3 different demographics (e.g., (1) Vitamin D supplementation combined with calcium can reduce fractures in the older population, (2) Vitamin D regulates the growth of vaginal epithelial cells and alleviates genitourinary tract problems in menopausal women (Mei et al., 2023) (3) Low levels of vitamin D during intrauterine life increases the risk of diseases such as type 1 diabetes, (4) Vitamin D deficiency increases the risk of low birth weight and preterm birth).

The response contains analysis accounting for key variables (e.g., skin type, latitude, and time of day for sun exposure, and gender, sex, and age in general).

The response addresses how socioeconomic status, access to safe outdoor spaces, and geographic location (urban vs. rural) can influence an individual's ability to follow health recommendations, including a discussion of potential disparities in sunlight and vitamin D intake. (e.g., (1) Rural residents are more likely to be vitamin D deficient, (2) Rural residents have higher medical costs compared to urban residents, (3) Vitamin D deficiency in High Latitude Countries, particularly during the winter months, (4) "Low socioeconomic status predicts vitamin D status in a cross-section of Irish children").

The response mentions pregnancy, lactation, or menopause as specific life stage factors.

The response provides specific, quantifiable recommendations, detailing the recommended duration of sun exposure needed to synthesize adequate vitamin D (e.g., recommends approximately 5 to 30 minutes of sun exposure, particularly between 10 a.m. and 4 p.m.).

The response mentions whether most people today get enough sunlight and/or vitamin D (or should supplement) (e.g., (1) In the US, approximately 35% of adults have vitamin D deficiency, (2) Older people produce less vitamin D so have a higher risk of deficiency, (3) Individuals with obesity who have undergone gastric bypass surgery have a higher risk, (4) Darker skin reduce the skin’s ability to produce vitamin D from sunlight).

The response provides a detailed comparison of the effectiveness of different types of fortified foods (e.g., milk, orange juice, cereal), discusses varying fortification levels, and compares their efficacy as a delivery method against supplements and sun exposure (e.g., (1) Food fortification significantly improves serum levels and intake, (2) Milk was fortified at 800 IU/day, (3) led to an approximate increase of 8 ng/mL in serum 25-OH D, (4) more cost-effective compared to the cheapest prescription drugs, (5) Better to get vitamin D from vitamin D-fortified foods than to get it solely from sun exposure as it can increase the risk of skin diseases).

The response provides the consensus daily supplemental intake recommendations in IU and clearly differentiates between Vitamin D2 and Vitamin D3 (e.g., 15 to 20 mcg (600–800 IU) for adults and from 10 to 15 mcg (400–600 IU) for infants, children, and adolescents, Vitamin D3 is the recommended (also called cholecalciferol) while Vitamin D2 (ergocalciferol) can only be obtained from fortified food or dietary supplements).

The response has a robust summary of key takeaways and lays out clear recommendations based on age, sex, etc (e.g., (1) Recommends 15 to 20 mcg (600–800 IU) for adults and from 10 to 15 mcg (400–600 IU) for infants, children, and adolescents, (2) Vitamin D helps with absorption of Calcium, (3) Sun exposure causes the skin to produce vitamin D naturally, however, this capability goes down with age, (4) Pregnant woman should take vitamin D supplementation).

The response outlines the primary health risks associated with both underexposure (e.g., vitamin D deficiency) and overexposure (e.g., sunburn, photoaging, skin cancer risk).

The response lays out clear metrics to know if a person is underexposed or overexposed (e.g., (1) Exceeding the recommended daily dosage of vitamin D (15 to 20 mcg (600–800 IU) for adults and from 10 to 15 mcg (400–600 IU) for infants, children, and adolescents), (2) Symptoms of too much vitamin D such as vitamin D headache, (3) About 8 to 10 minutes of sun exposure at noon produces the recommended amount of vitamin D, (4) UV Index of 6 and above is high).

The response provides, for each risk, at least one evidence-based mitigation strategy (e.g., (1) proper sunscreen application, (2) dietary sources of vitamin D, (3) regular skin checks, (4) fortified foods).

The response includes a section on the ethical considerations of public health messaging related to sun exposure (e.g., (1) Risk of Skin cancer, (2) skin protection behavior, (3) Skin cancer beliefs, (4) Sunbathing).

The response includes a section on the public health policy implications of the report's findings, considering how recommendations could be translated into policies such as school programs promoting outdoor time, urban planning initiatives, and national supplementation guidelines.

The response includes a comprehensive analysis of the role of other key nutrients (e.g., Magnesium, vitamin K) that are essential for vitamin D metabolism and bone health (e.g. (1) Magnesium helps with Vitamin D absorption in the GI tract, (2) Vitamin K2 helps deposit absorbed Calcium into bone, (3) Vitamin D helps the body absorb Calcium, (4) Vitamins A and D have the greatest immunemodulatory effect).

The response explicitly acknowledges the limitations of the existing research and identifies key gaps that require further study, such as the precise optimal vitamin D dosage for different populations and the long-term effects of various supplementation methods.


Prompt: I am a high schooler in Cupertino. It is AP season and I'm trying to study for my tests. Can you give me 10 recommendations for places that open until at least 10pm that are good for studying (fast wifi, sufficient table space to do practice tests, good study environment, etc)? I would prefer not having to spend money on drinks/food in cafes but have a $10 budget if I must, and absolutely refuse to spend money on parking/fees. I am only open to places that are at most at 20 minute drive from me.

The response contains exactly 10 distinct study-location recommendations.

Every recommended location name is accompanied by either a full street address or, at minimum, a clearly identified city/neighborhood (e.g., “Philz Coffee – Sunnyvale”).

All recommended locations are situated in a city that is within a typical 20-minute drive from Cupertino during non-rush hours (Cupertino, Sunnyvale, Santa Clara, Mountain View, Los Altos, Saratoga, West San Jose, etc)

For every recommendation, the response states that the closing time is 10:00 PM or later on weekdays (and specifies the closing time).

Some locations that close before 10:00 p.m. on weekdays are listed as meeting the ≥10 p.m. requirement (e.g., Cupertino Library, which closes at 9 p.m.).

For each location, the response explicitly mentions the availability of free, reliable Wi-Fi (using language such as “free Wi-Fi” or “fast Wi-Fi available”).

For each location, the response explicitly mentions sufficient table/desk space or seating appropriate for studying. Example:
"Cupertino Library has large communal tables and quiet study carrels ideal for spreading out AP practice materials."

For every location, the response either confirms unlimited free parking or states that no parking fees apply.

Whenever a café or restaurant is suggested, the response suggests items that can be obtained for ≤ $10 in total.

The response is structured as a clear numbered/bulleted list or table so that a reader can quickly scan the 10 options.

The response includes a brief note advising the user to verify operating hours before visiting (demonstrating awareness of possible schedule changes).

The response does not recommend purely outdoor locations that lack tables or reliable shelter (e.g., public parks with only benches), unless they clearly state tables and weather-protected seating are available.

For each library or public facility included, the response confirms that non-residents may enter without special membership/fees. Example: "Santa Clara City Library allows all California residents to enter and use study spaces without a membership fee (verified on the library’s official visitor policy page)."

The response should mention if any location is known for stable power outlets, especially for laptop-based studying.

Any parking references should note if the location tends to have full or difficult parking. Eample: "Main Street Cupertino’s public parking garage is free but often fills up after 7 PM, so arriving early is recommended."

Response notes that public study spaces will be extra crowded during AP season as everyone is trying to study as well

All locations are accurate (i.e., still open, not under renovations, name of place is correct, address is correct)

The recommendations include private office buildings or coworking spaces with restricted or employee-only entry. E.g., WeWork Cupertino which requires a paid membership or company access.

If recommending a location with a minimum stay limit or a time limit for seating (common in some boba cafés), the response should disclose it. Example: "Fantasia Coffee & Tea in Cupertino has a posted 90-minute seating limit during evenings, so it’s better for quick review sessions rather than full-length AP practice tests."

If a place is louder/more bustling/less favorable for studying, response should always acknowledge this. Example: "Main Street Cupertino Plaza has outdoor seating and stays open late, but it’s usually busy with restaurant traffic and live music on weekends - so not ideal for quiet studying."

Whenever a café or restaurant is suggested, the response states whether purchase is optional. Example: "Panera Bread on Stevens Creek Boulevard allows customers to sit and use Wi-Fi without constant purchases, though a small drink (~$4) is expected if you stay for several hours."


Prompt: Conduct a comprehensive historical analysis of how the world has changed since the onset of the COVID-19 pandemic. Compare and contrast life before COVID and after it, covering key domains such as public health, work culture, education, travel, economy, mental health, social interactions, and technology adoption. Provide deep, well-researched insights and include real-world examples to support your points. Structure the analysis in chronological order (from the pre-pandemic era, through the initial outbreak in early 2020, the global response, vaccine rollouts, to the 2025 post-pandemic lifestyle) to enhance clarity and understanding. Aim for thoroughness and detail to ensure all major global shifts and trends are captured.

The response contains five section headings in the following order: Pre-Pandemic, Initial Outbreak, Global Response, Vaccine Rollout, Post-Pandemic.

The response contains a real-world example naming a specific country, organization, policy, or statistc (e.g., WHO, China, Sweden, mortality rates) for at least six of the eight domains.

The response states that the World Health Organization declared COVID-19 a pandemic on 11 March 2020.

The response states that the Pfizer-BioNTech vaccine received emergency authorization in December 2020.

The response notes that global GDP contracted in 2020 compared with 2019.

The response claims the pandemic began before December 2019 or after January 2020.

The response includes an attribution to a source or organization (e.g., World Health Organization, Center for Disease Control, European Centre for Disease Prevention and Control, Johns Hopkins Coronavirus Resource Center) for each numerical statistic.

The response includes at least one statement acknowledging regional variation in pandemic impact.

The response's statements are qualified with uncertainty when future implications are discussed.

The response refrains from offering medical treatment recommendations or personal health advice.

The response's discussion about work-culture references remote-work technologies (e.g., Zoom, Skype, Teams, Google Meet).

The response's technology-adoption discussion mentions increased telemedicine or e-commerce usage and supplies a concrete example (e.g., Amazon shopping, International Trade Administration report, CARES Act, CMS 1135 Waiver)

The report contains events dated 2022 or later in sections covering Pre-Pandemic or Initial Outbreak periods.

The response discusses vaccines that were released outside of the United States (e.g., Oxford–AstraZeneca in the UK, Sputnik V in Russia, Sinopharm BIBP in China, Covaxin in India)

The response discusses isolation policies that were implemented across different countries (e.g., USA, China, Sweden, Germany)

The response followed the chronological order given in the prompt (e.g., from the pre-pandemic era up to 2019, through the initial outbreak in early 2020, the global response in the latter half of 2020, vaccitional rollouts in 2021, and the current post-pandemic lifestyle from 2022 onwards).

The response discusses isolation policies that were implemented across different countries (e.g., regional variation in the north vs south of the USA, strict lockdowns in China, voluntary policy in Sweden, testing centers across Germany)

The response addresses public health to COVID-19 (e.g., strain on hospitals, vaccination efforts, education about viruses, mask policies).

The responses addresses work culture changes due to COVID-19 (e.g., telework policies, masking polices in the work place, social distancing, shutdown of the arts and service industries).

The response addresses educational changes due to COVID-19 (e.g., online learning technology, social distancing in schools, decline in test scores, cancellation of standardized exams).

The response addresses travel changes due to COVID-19 (e.g., limited flights and the impact on the airline industry, testing policies for travel, vaccination requirements for travel, remote work policies changing travel requirements).

The response addresses economic changes due to COVID-19 (3% economic downturn in 2020, global recession, mass layoffs, rising inflation).

The response addresses mental health impacts of COVID-19 (e.g., increase in risk for youth, increased strain on front-line healthcare workers, impact of long-covid on mental health, grief related to pandemic deaths).

The response addresses changes in social interaction due to COVID-19 (e.g., social distancing, new social norms, limited social circles, Zoom fatigue).

The response addresses changes in technology adoption due to COVID-19 (e.g., new RNA vaccine technology,  popularity of Zoom and other teleconferencing technology, popularity of streaming services, food delivery applications).


Prompt:
I want to create my own restaurant empire, but I have zero idea where to begin. I know I want to serve indian food in with three different settings - food truck, elevated fine dining, and kitchen only/ fast casual model. All the three chains serve authentic indian food.

The food truck is Indian fast food, street style with some dishes that you can eat on the move with some innovation if required

The elevated fine dining is a north indian fine dining setting with servers dressed as attendants from royal courts during the time of Indian Kings, the ambience should resemble to that of the biggest and most grandest of places in India - I want to show the world what Indian culture, history, and grandeur and servitude is. The dishes would be served in the authentic way it is served in the region the dish originated from. I would also like a place where the restaurant could host performances. I want my guests to be transported to India not only by food but also through the ambiance, the atmosphere.

The kitchen only/ fast casual place would be parallel to the food truck in most ways but resemble more to Indian street style restaurants - people can see the cook prepare their food, and if its a fast casual place guests can come in sit chill and would be more modern

I have no idea how to go about this, do market research, competitor analysis, costing, what architects and designers should I contact, how much money would be required, the menu and basically everything else

I do have a few things in mind is that I wanna start with NYC and expand into major cities in the world and make this a truly global business with possibilities of opening hotels, and every dish should have a vegan option and where possible Jain options too

Response explicitly names and addresses the three settings: (1) food truck, (2) elevated fine-dining, (3) kitchen-only/fast-casual.

Response should include the capital range for each of the 3 settings: 1) For food truck, the capital should be in the range of $50K-$150K, 2) For the fine dining, the caputal should be in the range of $500K-$2Million, and 3) the capital for the kitchen only fast food mode should be in the range of $250K-$1Million.

Each dish on the menu must have a vegan alternative. These alternatives should be entirely plant-based, excluding all animal products and by-products such as meat, poultry, fish, dairy, eggs, honey, and gelatin. Clearly mark the vegan options on the menu.

The menu should offer Jain food alternatives. These dishes must be strictly lacto-vegetarian and exclude onion, garlic, meat, fish, eggs, honey, root vegetables (such as potatoes and carrots), and fermented foods. All Jain options should be clearly identified on the menu.

The response should identify key competitors in NYC, compare their menus, price points, service styles, and target audiences, evaluate their strengths and weaknesses, and highlight opportunities and market gaps. This analysis should be conducted separately for each of the three settings: food truck, fine dining, and fast casual/kitchen-only.

Response lists the NYC Mobile Food Vending License as a required permit for the food truck in NYC

Response lists the NYC Department of Health and Mental Hygiene (DOHMH) Restaurant Permit as a required license for brick-and-mortar locations

Response lists the New York State liquor license (or specifically a Restaurant Wine/On-Premise license) as necessary if alcohol is to be served in the fine-dining venue

The response should state that new trucks typically cost $100,000-$175,000, used trucks $30,000-$100,000, and leasing $2,000-$3,000 per month. It should note that final costs depend on condition, customization, equipment, permits, and insurance.

The response should provide approximate rental and purchase costs of restaurant spaces in New York City, broken down by carpet area (per square foot) and neighborhood. It should highlight how rental rates vary across neighborhoods. E.g., $150-$300 per sq ft/year in premium areas like Midtown, SoHo, and the Upper East Side versus $50-$100 per sq ft/year in Brooklyn and Queens. For purchase prices, it should mention typical commercial real estate ranges (e.g., $500-$1,500 per sq ft depending on location and building condition). The response should also note factors influencing costs, such as visibility, foot traffic, and zoning, and include additional expenses like deposits, renovations ($200,000-$500,000+ for fine dining interiors), utilities, and licenses.

The response should outline staffing requirements for each of the three concepts (food truck, fine dining, and fast casual/kitchen-only), and list at least three distinct roles per setting. For example:
1) Food Truck: chef/line cook, cashier/order taker, prep/cleaning staff.
2) Fine Dining: executive chef, sous chefs, servers, host/hostess, bar staff, and performers (for cultural shows).
3) Fast Casual/Kitchen-Only: cooks, counter staff, delivery/logistics coordinators.

The response should provide a sample menu of exclusively Indian dishes tailored to each of the three settings (food truck, fine dining, and fast casual).

The response should present a sample menu composed exclusively of North Indian dishes. It should highlight regional authenticity and include at least four example items, such as Butter Chicken, Paneer Tikka, Dal Makhani, Rogan Josh etc. The menu should reflect the diversity of North Indian cuisine while keeping the fine dining context in mind.

Response mentions the inclusion of a performance space or area for live cultural shows in the fine-dining venue.

The response should propose a phased rollout timeline with at least three chronological stages, e.g., Research & Planning (3-6 months), Pilot Launch (6-12 months), and Expansion (12-24 months and beyond).

Response includes funding sources beyond personal savings (e.g., SBA loan, angel investment, venture capital, franchising fees)Response includes funding sources beyond personal savings (e.g., SBA loan, angel investment, venture capital, franchising fees)

The response should present a high-level financial projection or break-even discussion, such as months to break even, ROI percentage, projected annual revenue, or profit margins.

The response recommends a marketing strategy that includes at least 4 channels - e.g., social media influencers ($500-$5,000/campaign), local events ($1,000-$3,000/event), digital ads ($1,500-$5,000/month), and food delivery app promos (20–30% commission, $500-$2,000/month for boosts). It should briefly explain how each supports brand growth.

The response should list actual global cities as future expansion targets (e.g., San Francisco, Miami, London, Dubai, Singapore) and provide brief pros and cons for each. For example, San Francisco for its diverse food culture and high spending power but with high operating costs; Miami for its growing international dining scene but seasonal demand fluctuations.

The response should describe authentic serviceware and presentation styles for North Indian fine-dining dishes, with representative examples. E.g., brass or copper thalis ($40-$100 each), silver platters ($200-$500 each), clay pots for curries ($10-$30 each), hand-carved wooden trays ($50-$150 each), and ornate glassware ($15-$50 per piece). It should factor in approximate costs and address sourcing options, such as importing from India for cultural authenticity versus purchasing from local specialty suppliers in NYC for logistical efficiency.

The response should list architectural or design firms with restaurant and cultural theming expertise (e.g., Rockwell Group, AvroKO, Studio Lotus, IA Interior Architects), include their contact details, explain their relevance to the concepts, and outline approximate cost considerations.

The response should provide guidance on choosing locations in New York City. For example:
1) Food truck - foot traffic, permits $200-$500/month, university/office hubs, competition
2) Fine dining - affluent demographics, prestige areas like SoHo/Upper East Side, accessibility, rents $150–$300/sq ft/year
3) Fast casual - delivery radius, affordable rents $50-$100/sq ft/year, proximity to students/residents, competitor density.

The response should suggest portable serving ideas highlighting both mobility and sustainability. E.g.,
1) paratha/dosa wraps in paper cones ($0.30-$0.50),
2) biodegradable chaat trays with lids ($0.40- $0.70),
3) skewer sleeves for kebabs ($0.20-$0.40),
4) sealed lassi/curry cups ($0.50-$0.80)

The response should describe the open-kitchen atmosphere and modern design elements that define the fast casual/kitchen-only model, making it distinct from fine dining. For example:
1) Exposed cooking stations where customers can watch food being prepared.
2) Communal or high-top seating that encourages casual, social dining.
3) Industrial decor with clean lines such as metal finishes, concrete, and minimalistic lighting.
4) Digital ordering kiosks or open shelving for grab-and-go meals to streamline convenience and service speed.

The response should present a menu of reasonable length. A menu that is too short (e.g., only 1-2 items such as Butter Chicken alone) or too long (e.g., 100+ items across all regions of India) is not acceptable. For example:
1) Too short: A single curry dish with no appetizers, breads, or desserts.
2) Too long: An encyclopedic menu with 100+ dishes, impossible to execute consistently.
3) Unbalanced: Heavy in one category (e.g., 20 curries but no breads, snacks, or drinks).
4) Unfocused: Mixing cuisines (e.g., Indian dishes plus sushi and tacos), straying from the concept.

The target number of items in the menu should be 8-12 items for food truck,~20-30 items for fine-dining (including courses, sides, desserts), and ~12-18 items for fast kitchen-only setting. The ideal menu should be curated, diverse, and tailored to the setting.

The response should suggest authentic serving methods that reflect North Indian fine dining traditions and elevate the guest experience. For example:
1) Thali platters with multiple katoris (brass or copper bowls) for curries, dal, and accompaniments.
2) Silver or gold-plated serveware for premium dishes, echoing royal court traditions.
3) Handi or clay pot serving for biryanis and slow-cooked curries, maintaining flavor and authenticity.
4) Live tableside service (e.g., pouring dal from a copper jug, carving kebabs) to enhance theatricality and immersion.

Response has one section for each of:
- market research
- competitor analysis,
- costing,
- architects and designers,
- how much money would be required,
-  the menu
- basically everything else

The response lists south indian food items (eg. idly, dosa, etc.) for the fine dining.


Prompt: Write a detailed report on Langchain and how it became one of the most used python libraries in 2025 for AI application development using Large language models. Also explain evolution of the library, how it changed over the years, why was it created and also explain some of the more advanced libraries born out of it. Then explain why it has consistently been one of the best even though there are many python libraries that can also be used to create similar workflows and why I should prefer langchain over them in certain types of tasks. Talk about the company, how many contributors, main contributors, main source of income and finally end your report by summarising the direction in which langchain will progress and what their future plans are.

The response correctly identifies that the primary motivation for creating LangChain was to simplify the composition of LLMs with external data sources and tools (i.e., "chaining").

The response identifies Harrison Chase as the creator of LangChain.

The response states that LangChain was initially released in October 2022.

The response specifically mentions the major architectural refactoring that split the library into modular packages, such as langchain-core, langchain-community, and partner packages (e.g., Pinecone, OpenAI, Weaviate, Milvus).

The response names at least 2 core LangChain projects (e.g., LangServe, LangSmith, LangGraph, LangChain Hub).

The response cites at least two distinct and accurate chronological milestones in LangChain’s evolution after the initial release (e.g., October 2023: LangServe was introduced; December 2023: split into modular packages; Jan 2024: LangGraph was introduced; Feb 2024: LangSmith became generally available).

The response names at least one additional core maintainer or main contributor other than Harrison Chase from the LangChain official repository (e.g., @baskaryan - Bagatur Askaryan, @ccurme - Chester Curme, @nfcampos - Nuno Campos, @eyurtsev - Eugene Yurtsev).

The response discusses at least 2 distinct and plausible reasons that explain LangChain's popularity (e.g., modular abstractions, first-mover advantage, comprehensive documentation, large community).

The response includes a description of what each additional derivative library adds beyond LangChain, if mentioned.

The response compares LangChain's agent builder components (e.g., LangGraph) to at least one other agent framework (e.g., Autogen, Crew AI, Semantic Kernel, OpenAI Swarm).

The response identifies at least two external derivative libraries or tools built on top of LangChain and their purpose (e.g., Flowwise: a drag-and-drop visual builder; LangFlow: a visual framework for designing LLM apps; Embedchain: a RAG-focused wrapper over LangChain).

The response describes and cites the source(s) for at least one publicly announced future plan or roadmap item for LangChain (e.g., improving observability with LangSmith, expanding LangServe, enhancing agent reliability, adding human-in-the-loop support).

The response identifies at least one other potential or actual source of income for LangChain beyond its primary SaaS product (e.g., enterprise/custom plans, venture capital funding).

The response discusses non-LLM Python libraries (e.g., Numpy, Pandas) without a clear justification for their relevance to LangChain or other LLM-based frameworks.

The response is organized as a report, using clear sections with headers (e.g., "Introduction," "Evolution of LangChain," "Company and Contributors," "Future Direction").

The response includes a distinct final section that summarizes announced roadmap items and future plans.

The response defines or clearly explains at least one key LangChain-specific technical concept (e.g., Agent: an LLM capable of using tools or actions; Chain: a sequence of components; LangChain Expression Language/LCEL: the syntax for defining and composing workflows; Retriever: a component that fetches relevant documents).

The response states that LangChain's primary source of income is from selling the open-source library, general consulting, or donations (rather than its platform, LangSmith).

The response incorrectly claims LangChain was created or is maintained by a large tech corporation (e.g., Google, Meta, OpenAI).

The response mentions the total number of contributors to LangChain as of the report's date and cites the source for this figure (e.g., 3,718 contributors from the official LangChain repository at https://github.com/langchain-ai/langchain as of 09/15/2025).

The response mentions LangChain's acquisition of Dashtab in 2023, explaining its strategic importance for bolstering human-in-the-loop (HIL) and feedback capabilities within LangSmith.

The response identifies and explains the role of the LangChain Hub as a central, public repository for users to discover, share, and version community-built prompts, chains, and agents.

The response discusses (with relevant sources) the state of the LangChain.js (TypeScript) library, including its feature parity, adoption level, or key differences when compared to the primary Python version.

The response identifies and describes LangChain Templates, a separate initiative from the LangChain Hub that provides developers with pre-packaged, production-ready reference applications.

The response mentions other business or educational platforms that partner with LangChain, explaining how this enhances its utility or popularity, and cites appropriate sources (e.g., Coursera and DeepLearning.AI offer courses on LangChain; MongoDB Atlas partners with LangChain; Qualtrics partners with LangChain to develop 'Experienced Agents' using LangGraph).

The response discusses at least two specific scenarios or tasks where LangChain is preferred over an alternative, explaining the reason (e.g., preferred over LlamaIndex for complex, multi-step agents due to LangGraph's flexibility; preferred over Haystack for RAG production due to built-in evaluation with LangSmith).

The response discusses the potential intellectual property or license compliance risks when building commercial applications with LangChain, given its role in connecting to hundreds of external components with varied licenses (beyond its own MIT License).

The response identifies partnerships between LangChain and major cloud providers (e.g., Amazon Web Services/AWS, Google Cloud/GCP, Microsoft Azure, Oracle Cloud) or other key enterprise software vendors, beyond simple technical integrations.