MeshMesh
Core Concepts

Artifacts

Artifacts capture AI discoveries, insights, reports, and decisions during task execution - building a searchable knowledge base for your team.

Artifacts: Capturing AI Discoveries

Artifacts are documents created by your AI assistant during task execution to capture important discoveries, insights, reports, challenges, questions, and decisions.

Think of artifacts as the AI's way of taking notes about what it learned while working on your task.

Why Artifacts Matter

As your AI works through tasks, it discovers valuable information that goes beyond just completing the task. Artifacts preserve this knowledge so you can:

  • Learn from the AI: Understand what it discovered and why
  • Build Knowledge: Create a searchable repository of insights
  • Make Decisions: Review documented options and recommendations
  • Track Progress: See how challenges were overcome
  • Share Insights: Distribute findings across your team

Types of Artifacts

💡 Insights

Document important discoveries or learnings uncovered during task execution.

Examples:

  • Customers who abandoned carts are 3x more likely to convert when sent a reminder within 2 hours
  • Your most successful emails have subject lines under 40 characters
  • Weekend campaigns generate 40% higher open rates for this audience

Contains:

  • The insight itself
  • Supporting data or evidence
  • Implications for your business
  • Recommended actions

📊 Reports

Present structured analysis and data summaries compiled by the AI.

Examples:

  • Campaign performance comparison across quarters
  • Customer segment analysis with demographics
  • Email template usage statistics

Contains:

  • Data tables and visualizations
  • Key metrics and KPIs
  • Trend analysis
  • Summary conclusions

⚠️ Challenges

Document obstacles, blockers, or limitations encountered during execution.

Examples:

  • Data source connection intermittent - implemented retry logic
  • Customer email list has 15% invalid addresses - created filter
  • Journey automation limit reached - simplified workflow

Contains:

  • Description of the challenge
  • Impact on the task
  • Workaround or solution applied
  • Future recommendations

❓ Questions

Flag decisions that need human input or clarification.

Examples:

  • Should this campaign exclude recent purchasers or include everyone?
  • Multiple brand kit templates found - which is preferred for this campaign?
  • Data shows conflicting customer preferences - how should we prioritize?

Contains:

  • The question being asked
  • Context and background
  • Available options
  • Implications of each choice

🎯 Decisions

Document key decisions made during task execution.

Examples:

  • Chose email over SMS for initial outreach based on higher engagement rates
  • Selected segmentation based on purchase history vs. browsing behavior
  • Implemented gradual rollout instead of immediate launch to test performance

Contains:

  • The decision made
  • Rationale and reasoning
  • Alternatives considered
  • Expected outcomes

Artifact Components

Every artifact includes:

Category Badge

Visual indicator of artifact type (Insight, Report, Challenge, Question, Decision)

Title & Summary

Clear, descriptive name with 1-2 sentence overview of key information

Detailed Content

Full information, analysis, or data with optional visualizations

Metadata

Created date/time, associated task, related platforms, priority level, and tags

Working with Artifacts

Artifact Visualizations

Artifacts can include rich visualizations to make data immediately understandable:

  • Bar charts: Compare metrics across categories
  • Line charts: Show trends over time
  • Pie charts: Display proportions and percentages
  • Structured data display
  • Sortable columns
  • Filterable rows
  • Large, prominent numbers
  • Comparison to benchmarks
  • Trend indicators (up/down)
  • Important warnings and success indicators

Building Your Knowledge Base

Maximize Value

As you complete tasks, artifacts accumulate into a valuable knowledge base for your entire organization.

Pattern Recognition

Identify successful approaches, spot common challenges, and learn what works best

Team Learning

Share insights across organization, build on each other's discoveries, and create organizational memory

Decision Support

Reference past decisions, learn from outcomes, and make data-informed choices

Automatic Documentation

No manual note-taking required - always searchable and accessible

Best Practices

Act on Artifacts

Don't just complete tasks - review what was learned and respond to questions promptly.

Review Regularly

  • High-priority artifacts deserve immediate attention
  • Question artifacts may need your response
  • Review findings to improve future tasks

Share Insights

  • Export and share valuable insights with team
  • Use artifacts in presentations and reports
  • Build institutional knowledge

Address Challenges

  • Update processes based on learnings
  • Prevent future issues
  • Document workarounds for team reference

Tag and Organize

  • Add custom tags for your organization
  • Create meaningful categories
  • Build searchable knowledge structure

Privacy & Security

Artifacts respect your data governance:

Access Control

Only visible to authorized users

Compliance

Follow same rules as underlying data

Retention

Configurable retention policies

Audit

Track who viewed or exported artifacts

Tips & Tricks

  • Answer Questions Promptly: Guidance improves future AI performance and builds better outcomes over time
  • Link Related Artifacts: Connect artifacts across tasks to build knowledge graphs and see relationships
  • Track Analytics: Measure which types are most valuable and optimize AI learning
  • Use Templates: Define what information to capture and ensure consistency across team

Next Steps