Brainforge Knowledge

agents-template

4 min read

[Project Name] - Agent Guide

Last Updated: [YYYY-MM-DD]
Project Duration: [Start Date] - [End Date or Ongoing]
Status: [Active/Discovery/Planning] - [Phase Description]

Project Overview

[Brief description of the project, client, and Brainforge’s role. 2-3 sentences explaining what we are building or discovering.]

Key Stakeholders

Client Team:

NameRoleResponsibilities
[Name][Title][Key responsibilities]
[Name][Title][Key responsibilities]

Brainforge Team:

NameRoleResponsibilities
Uttam KumaranManaging LeadClient POC, project strategy
[Name][Role][Responsibilities]

External Vendors:

VendorServiceStatusNotes
[Vendor Name][Service][Active/Transition][Key details]

How to Use This Repo

For AI Agents and LLMs

When interacting with this repository, you should:

  1. Understand context first

    • Review this file (agents.md) to understand project goals
    • Check /meeting_agendas/ for stakeholder discussions
    • Read DISCOVERY_WIKI.md for consolidated project knowledge
    • Review /meeting_transcripts/ for detailed context

  2. Follow the [principle name] principle

    • [Key principle 1: e.g., “Discovery before prescription”]
    • [Key principle 2: e.g., “Document everything as we learn”]
    • [Key principle 3: e.g., “Respect existing workflows”]

  3. Respect the project context

    • [Context item 1: e.g., “Client operates in [industry]”]
    • [Context item 2: e.g., “Team has [X] technical depth”]
    • [Context item 3: e.g., “Avoid [specific constraints]”]

  4. Support meeting preparation

    • Generate discovery questions tailored to each stakeholder
    • Summarize previous meeting notes before new stakeholder calls
    • Track action items and follow-ups

  5. Assist with technical decision-making

    • Reference existing architecture and conventions
    • Consider client team capabilities
    • Provide pros and cons for architectural decisions

For Human Team Members

This repo serves as the single source of truth for:

  • Project Planning: SOW, timelines, milestones
  • Meeting Documentation: Agendas, transcripts, notes
  • Stakeholder Intelligence: Pain points, workflows, data sources
  • Knowledge Base: Discovery Wiki synthesizes all learnings

Repository Structure

[project-folder]/
  agents.md                          # This file - project guide for AI and humans
  README.md                          # Project overview
  DISCOVERY_WIKI.md                  # Central knowledge base
  MEETING_WORKFLOW_GUIDE.md          # How to document meetings
  meeting_agendas/                   # Individual meeting prep and summaries
    README.md
    MEETING_TEMPLATE.md              # Copy this for new meetings
    [dated meeting agendas]
  meeting_transcripts/               # Raw conversation transcripts
    [dated transcripts]
  meeting_notes/                     # Legacy or supplemental notes
    README.md
  resources/                         # Reference materials and planning docs
    README.md
    [SOW, overview docs, etc.]

Project Goals

Primary Objectives

  1. [Objective 1]

    • [Key deliverable]
    • [Success criteria]

  2. [Objective 2]

    • [Key deliverable]
    • [Success criteria]

  3. [Objective 3]

    • [Key deliverable]
    • [Success criteria]

Success Metrics

MetricTargetHow Measured
[Metric 1][Target value][Measurement method]
[Metric 2][Target value][Measurement method]
[Metric 3][Target value][Measurement method]

Business Context

Client Overview

  • Business Model: [Description]
  • Market: [Description]
  • Team Size: [Number]
  • Key Challenges: [Description]

Key Pain Points

  1. [Pain Point 1]

    • [Details and impact]

  2. [Pain Point 2]

    • [Details and impact]

  3. [Pain Point 3]

    • [Details and impact]

Project Timeline

Phase 1: [Phase Name] ([Duration])

Target: [Date range]

Key Deliverables:

  • [Deliverable 1]
  • [Deliverable 2]
  • [Deliverable 3]

Success Criteria:

  • [Criteria 1]
  • [Criteria 2]

Phase 2: [Phase Name] ([Duration])

Target: [Date range]

Key Deliverables:

  • [Deliverable 1]
  • [Deliverable 2]

Discovery Framework

Key Questions for Stakeholders

For [Role/Team]:

  1. [Question 1]
  2. [Question 2]
  3. [Question 3]

For [Role/Team]:

  1. [Question 1]
  2. [Question 2]

Technical Approach

Current Stack

CategoryTool/TechnologyStatusNotes
[Category][Tool][Active/Planned][Notes]
[Category][Tool][Active/Planned][Notes]

Data Sources

SourceTypeOwnerAccess Status
[Source 1][Type][Owner][Status]
[Source 2][Type][Owner][Status]

Proposed Approach

[Description of technical approach, architecture decisions, and key considerations.]

Operating Principles

  1. [Principle 1]

    • [Details]

  2. [Principle 2]

    • [Details]

  3. [Principle 3]

    • [Details]

  4. [Principle 4]

    • [Details]

How AI Agents Can Help

1. Meeting Preparation

  • Generate discovery questions tailored to each stakeholder
  • Summarize previous meeting findings for context
  • Identify knowledge gaps to address

2. Data Analysis

  • Analyze existing systems and patterns
  • Identify issues and opportunities
  • Calculate relevant metrics

3. Knowledge Capture

  • Document existing processes and business logic
  • Create knowledge transfer documents
  • Identify documentation gaps

4. Pattern Recognition

  • Find commonalities across stakeholder pain points
  • Identify systemic issues versus isolated problems
  • Spot quick win opportunities

5. Development Support

  • Assist with technical implementation
  • Help with testing and validation
  • Support optimization efforts

Key Insights from Discovery So Far

What is Working

  • [Positive finding 1]
  • [Positive finding 2]
  • [Positive finding 3]

What is Challenging

  • [Challenge 1]
  • [Challenge 2]
  • [Challenge 3]

Quick Wins to Target

  1. [Quick win 1] - [Brief description]
  2. [Quick win 2] - [Brief description]
  3. [Quick win 3] - [Brief description]

Risks and Mitigations

RiskImpactMitigation
[Risk 1][Impact level][Mitigation strategy]
[Risk 2][Impact level][Mitigation strategy]
[Risk 3][Impact level][Mitigation strategy]

Additional Resources

Project Documents

Meeting Documentation

Questions or Gaps

If you are an AI agent or team member and something is unclear:

  1. Check existing docs first: Meeting agendas, Discovery Wiki, transcripts
  2. Search for related context: Use semantic search across the repo
  3. Flag the gap: Note what is missing in your response
  4. Suggest next steps: Who to ask, what to research

Remember: Acknowledging unknowns explicitly is valuable.

Document Change Log

DateAuthorChange
[YYYY-MM-DD][Author]Initial repository structure creation

For questions or updates to this guide, contact:

Graph View