Laguna by Poolside vs TheySaid 3.0: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Laguna by Poolside and TheySaid 3.0 — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Laguna by Poolside
Poolside
Poolside's family of open Mixture-of-Experts foundation models for agentic coding — XS.2 runs locally, M.1 reaches 72.5% on SWE-bench Verified.
Key features
- Two Model Sizes: Laguna XS.2 (33B total / 3B active) and Laguna M.1 (225B total / 23B active) target different latency and capability needs.
- Mixture-of-Experts Architecture: Routes each token through a subset of experts for efficiency at large scale.
- Local Deployment: XS.2 is small enough to run on a Mac with 36 GB of RAM via Ollama under an Apache 2.0 license.
- Strong SWE-bench Results: XS.2 hits 68.2% and M.1 reaches 72.5% on SWE-bench Verified.
- Bundled Coding Agent: Ships 'pool,' a lightweight terminal-based coding agent.
- Agent Client Protocol: Includes a dual ACP client-server used internally for agent RL training and evaluation.
Best for
- Local Agentic Coding: Running XS.2 on a laptop for private, offline code generation and editing.
- High-Capability Code Tasks: Using M.1 for harder, long-horizon software engineering work.
- Self-Hosted Deployments: Building on open weights to avoid third-party API dependencies.
- Research & Fine-Tuning: Adapting permissively licensed weights for custom coding workflows.
- Benchmarking: Evaluating agentic coding performance against SWE-bench Verified and Pro.
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TheySaid 3.0
TheySaid
Turn single-question surveys into real-time conversational surveys to boost engagement and surface richer insights.
Key features
- Conversational Survey Conversion: Transforms single-question surveys into AI-driven multi-turn conversations that probe respondents with contextual follow-ups to gather richer qualitative data.
- Real-time Engagement: Dynamically adapts follow-up prompts based on answers to keep respondents engaged and reduce drop-off during the survey experience.
- Automated Insight Extraction: Aggregates and summarizes responses, surfaces recurring themes and sentiment, and highlights actionable findings for faster analysis.
- Intelligent Question Generation: Generates clarifying and targeted follow-up questions tailored to each respondent’s answers to obtain deeper context and reasons.
- Response Analytics Dashboard: Provides aggregated views, filters, and breakdowns (e.g., sentiment and themes) to help teams interpret results quickly.
- Export & Integration: Enables exporting response data and integrating survey outputs with downstream analytics or research workflows for further analysis.
- Conversational AI Surveys that adapt follow-up questions based on responses
- AI Interviews to automate in-depth user interviews
- AI Pulses and Polls for single-question feedback and follow-ups
- Question recommendation and auto-generation from website content
- Embedding and delivery via existing channels
- AI-driven summarization of responses and insights
- Convert single-question surveys into interactive, AI-driven conversations
- Real-time capture of conversational survey responses
- Smart conversational survey design to boost respondent engagement
- Automated analysis and extraction of insights from conversational responses
- Web-based survey creation and results dashboard
Best for
- Converting NPS/CSAT single-question prompts into conversational flows to collect reasons, suggestions, and context behind scores for better actionability.
- Market research that requires scalable qualitative feedback by turning short surveys into richer interviews to surface customer needs and motivations.
- Customer support and feedback collection that triages issues via guided conversation and captures exact user language and sentiment for product teams.
- Employee pulse and HR surveys that solicit candid explanations and suggestions while maintaining higher completion rates through conversational engagement.
- Product discovery and usability testing to gather in-depth user reactions, feature requests, and pain points from compact, conversational surveys.
- Collecting product and UX feedback via conversational surveys
- Automating user interviews to surface deeper insights
- Running NPS/CSAT/CES pulses with follow-up probing
- Embedding surveys across websites and apps to increase engagement
- Conducting user tests and polls with AI follow-ups to understand reasons
- Customer feedback collection with richer qualitative responses
- Market research using conversational probes to uncover insights
- Product feedback and user experience surveys
- NPS and satisfaction measurement with follow-up conversational context
- Employee engagement and pulse surveys