The short answer: open Genspark in your browser, click into the search field, press ⌃+⌥+R (Mac) or Ctrl+Alt+R (Windows/Linux), speak your detailed research query for 45-90 seconds including context and constraints, and AICHE inserts the comprehensive search request.

Typing detailed research queries with specific constraints, multiple sub-questions, and context requirements takes 10-15 minutes and often results in abbreviated searches that miss important nuances.

Open genspark.ai in your browser.
Click into the main search/query field.
Press your AICHE hotkey to start recording.
Speak your complete research question with context and constraints.
Press the hotkey again - AICHE transcribes and inserts the query.
Execute the search and review Genspark's AI-generated research.

Technical Research Queries

Framework Comparison Analysis

Comprehensive research needs detailed specifications. Example: "research and compare Next.js 14 with app router versus Remix for building a production e-commerce platform, focus areas include server-side rendering performance with large product catalogs testing at 10000 plus SKUs, static site generation capabilities for product pages and category listings, incremental static regeneration for inventory updates without full rebuilds, API route performance for checkout and payment processing, SEO capabilities including meta tags structured data and dynamic sitemaps, developer experience covering TypeScript support testing frameworks and debugging tools, deployment options comparing Vercel Edge Functions versus traditional Node servers, cost analysis for hosting 100000 monthly active users with 500000 page views, bundle size impact on mobile users in regions with slow network connections, provide code examples showing authentication implementation in both frameworks, include performance benchmarks from real world production applications if available, cite recent blog posts from 2024 and 2025 not outdated comparisons from 2022, highlight breaking changes and migration complexity if moving from Pages Router to App Router in Next.js, consider total cost of ownership including hosting developer time and third party service integrations".

Detailed queries produce actionable research instead of surface-level comparisons.

Security Vulnerability Research

Security research requires specific technical depth. Example: "research latest OAuth 2.0 security vulnerabilities discovered in 2024 and 2025 particularly affecting single page applications using authorization code flow with PKCE, identify common implementation mistakes that lead to token leakage or authorization bypass, explain how attackers exploit misconfigured redirect URIs to steal authorization codes, detail the impact of using state parameter incorrectly or omitting it entirely, provide specific code examples in JavaScript showing vulnerable implementations versus secure patterns, include recent CVEs related to popular OAuth libraries like Passport.js NextAuth and Auth0 SDKs, explain mitigation strategies including proper token storage using httpOnly cookies versus localStorage, describe how to implement token refresh securely without exposing refresh tokens to JavaScript, cover best practices for handling CORS in authentication flows, include links to OWASP guidelines and security advisories from major OAuth providers Google Microsoft and GitHub, provide testing methodology to audit existing OAuth implementations for vulnerabilities, cite specific penetration testing tools and techniques used to identify OAuth misconfiguration".

Comprehensive security queries help identify and prevent actual vulnerabilities rather than generic advice.

Development Research

Architecture Decision Research

Complex technical decisions need thorough analysis. Example: "research microservices versus modular monolith architecture for a growing SaaS application currently serving 5000 users planning to scale to 50000 users within 12 months, team size is 8 engineers with moderate DevOps experience, current pain points include slow deployment cycles due to coupled codebase and difficulty testing features in isolation, evaluate deployment complexity comparing Docker containers with Kubernetes versus single server deployment with PM2, analyze database strategies including separate databases per service versus shared schema with row level security, consider development velocity impact when adding new features that span multiple business domains, examine debugging and monitoring challenges comparing distributed tracing with OpenTelemetry versus centralized logging, cost analysis including infrastructure cloud services and developer productivity, provide case studies from companies that migrated from monolith to microservices including Pinterest Shopify and Segment, discuss when to start with monolith versus microservices based on team size and product maturity, include migration strategies if starting with modular monolith and transitioning to microservices later, evaluate trade-offs in consistency guarantees using saga pattern versus distributed transactions, cite recent conference talks or technical blog posts from 2024 to 2025 about real world experiences".

Thorough architectural research prevents costly technical decisions based on incomplete information.

Tool Selection Research

Technology choices benefit from comprehensive evaluation. Example: "research best observability platform for Node.js microservices comparing Datadog New Relic Grafana Cloud and self hosted Prometheus with Grafana, requirements include distributed tracing to follow requests across 12 services, application performance monitoring showing slow database queries and API call latencies, log aggregation with full text search and retention for 30 days, custom metrics for business KPIs like checkout completion rate and API error rates, alerting with PagerDuty integration and smart thresholds using machine learning to reduce false positives, evaluation criteria include cost for 20 services generating 500GB logs monthly with 50000 spans per minute, query performance when analyzing traces from past 7 days, dashboard usability for both engineers and non-technical stakeholders, integration ease with existing Express apps using OpenTelemetry, team collaboration features like shared dashboards and alert ownership, provide pricing comparison including hidden costs like data egress and retention, include setup complexity and time to first value, cite user reviews from engineering blogs and G2 ratings from 2024 to 2025, discuss vendor lock-in risks and data export capabilities if switching providers later".

Detailed tool evaluations lead to informed decisions that align with actual requirements and constraints.

Research Synthesis

Market Trend Analysis

Business research needs current data and analysis. Example: "analyze current trends in AI coding assistant adoption for 2024 and 2025 including market size growth rate and revenue projections, identify key players comparing GitHub Copilot Cursor Tabnine Cody and Amazon CodeWhisperer by market share pricing and feature differentiation, research enterprise adoption barriers including security concerns data privacy regulations and ROI justification, examine developer productivity metrics from published case studies showing actual time savings and code quality improvements, analyze pricing models from per seat licensing to usage based billing and their impact on adoption at different company sizes, investigate integration capabilities with existing development workflows including CI/CD pipelines code review processes and testing frameworks, research competitive moats and differentiation strategies like model quality IDE integration developer experience and enterprise features, include data on programming language support and framework coverage for popular technologies, cite recent analyst reports from Gartner Forrester and industry surveys from Stack Overflow and JetBrains, project future trends including AI pair programming evolution regulatory impacts and consolidation predictions, provide actionable insights for product teams building developer tools or companies evaluating AI coding assistant purchases".

Comprehensive market research provides strategic context for business and product decisions.

Result: typing detailed Genspark research queries with specific constraints and multiple dimensions that takes 12 minutes becomes 3 minutes of dictation, and speaking queries helps structure complex research questions more clearly than abbreviated typed searches.

Do this now: open Genspark, click into the search field, press your hotkey, and dictate one complex technical research question including all the context, constraints, and specific areas of comparison you actually need answered, not just a surface-level query.

AICHE +GGenspark Integration