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For Enterprises

Onboard New Team Members in Minutes

Problem: A new developer joins. It takes weeks to understand the codebase, architecture decisions, and domain knowledge. AI agents start from zero for every new team member.

Solution: Commit .fcontext/ to your repo. New members get instant context:

git clone your-project.git
cd your-project

# .fcontext/ is already there — AI reads it automatically
# New developer's AI immediately understands:
#   - Project architecture and conventions
#   - Key decisions and their rationale
#   - Domain-specific knowledge
#   - Current requirements and progress
graph LR subgraph "Senior Dev" S1["Work + Accumulate Knowledge"] S2[".fcontext/ committed"] end subgraph "New Member" N1["git clone"] N2["AI reads .fcontext/"] N3["Productive from Day 1"] end S2 -->|git push| N1 N1 --> N2 --> N3

Share Domain Knowledge Across Projects

Problem: Your organization has domain expertise scattered across teams. Each project reinvents understanding of the same domain concepts.

Solution: Create and distribute experience packs:

# Team A: Export domain knowledge
cd project-a
fcontext export git@github.com:your-org/payment-domain.git

# Team B, C, D: Import the same knowledge
cd project-b
fcontext experience import git@github.com:your-org/payment-domain.git

# When domain knowledge evolves
fcontext experience update
graph TD subgraph "Domain Expert Team" DE["Curate Domain Knowledge"] EP["Experience Pack<br/>(Git repo)"] DE --> EP end subgraph "Product Teams" T1["Team Alpha<br/>fcontext experience import"] T2["Team Beta<br/>fcontext experience import"] T3["Team Gamma<br/>fcontext experience import"] end EP --> T1 EP --> T2 EP --> T3

Example: organization-wide packs

Pack Purpose Teams
payment-domain Payment processing rules, compliance Checkout, Billing, Finance
security-standards Security patterns, audit requirements All engineering teams
api-conventions API design standards, error handling Backend teams

Standardize AI Delivery Quality

Problem: Different developers get different quality from AI agents. No consistent standard for AI-assisted development.

Solution: fcontext instructions enforce consistent AI behavior:

  • AI always reads project context before answering
  • AI always checks requirements before implementing
  • AI always persists discoveries for future sessions
  • AI never modifies imported experience packs
  • AI uses structured format for requirements and topics

These rules are embedded in the generated instruction files for every agent. Every developer, regardless of experience, gets the same high-quality AI behavior.

Security & Compliance

Concern fcontext approach
Data residency All data in local .fcontext/ directory — no cloud upload
Sensitive documents Indexed files stay on-disk, never sent to external services
Audit trail Requirements track author, source, creation time, status changes
Access control Standard Git permissions apply to .fcontext/
No vendor lock-in Plain Markdown/YAML files, no proprietary format