Name: Executive Advisor Board Tagline: AI-powered virtual executive advisory board that evaluates business proposals through multiple C-suite perspectives. Current status: Live First commit / project start: No dedicated git repo (product lives in ITI monorepo, first monorepo commit 2026-03-10); plugin file mtime 2026-03-29 [CLAUDE NOTE: inferred from file timestamps]
Executive Advisor Board is a WordPress plugin that simulates a full corporate advisory board using Claude AI. Users submit structured business proposals through a comprehensive 76-field form spanning 12 business categories, and the system sequentially evaluates the proposal through 8 distinct C-suite personas (CEO, CFO, CMO, COO, CTO, CHRO, General Counsel, and Independent Board Member). After all agents deliver individual assessments, a consolidation pass produces a unified executive summary identifying consensus, conflicts, concerns, and an overall recommendation. Users can then engage in follow-up chat to drill deeper into any aspect of the evaluation.
Unlike generic AI business tools that provide a single perspective, Executive Advisor Board delivers structured, multi-perspective governance-style evaluation. Each agent applies role-specific rubrics and decision frameworks — the CFO evaluates ROI and financial risk differently than the CTO assesses technical feasibility or the CHRO examines organizational impact. The consolidation pass then synthesizes genuine tensions between perspectives, surfacing the conflicts that real board deliberations would uncover. This creates a preparation and decision-support experience that generic chatbots cannot replicate.
Platform: WordPress plugin (PHP) Deployment: Self-hosted WordPress (5.8+), single-site Primary interface: Frontend shortcode [executive_advisor] with logged-in user form, progressive agent evaluation display, follow-up chat, and PDF export
Primary user: Directors, managers, and rising leaders preparing business proposals for executive or board review Secondary users: WordPress site administrators deploying the tool for internal use; consultants offering structured proposal evaluation User environment: Corporate or consulting WordPress sites where logged-in users submit proposals and receive AI-generated multi-perspective feedback
Most professionals have limited exposure to how executive teams and boards actually evaluate business proposals. They may get one shot to present and often lack feedback on which dimensions of their proposal are strong or weak. Real advisory boards are expensive, slow, and inaccessible to most mid-level professionals. Executive Advisor Board provides a structured, repeatable rehearsal environment where users can pressure-test proposals against multiple C-suite lenses before committing to real presentations.
| Need | How the product addresses it | Source of evidence |
|---|---|---|
| Multi-perspective evaluation of proposals | 8 distinct C-suite agents each apply role-specific rubrics and decision frameworks | executive-advisor.php agent queue, agents/*.txt prompt files |
| Conflict identification between business functions | Consolidation pass explicitly identifies consensus areas and genuine tensions between agent evaluations | consolidate_results() in executive-advisor.php |
| Structured proposal preparation | 76-field form across 12 business categories forces comprehensive proposal development | get_all_input_fields() in executive-advisor.php |
| Accessible board-level feedback | Available 24/7 at estimated $0.50–$1.00 per evaluation vs. thousands for real advisory engagement | documentation/README.md cost guidance |
| Follow-up exploration | Interactive chat with full evaluation context lets users drill into specific concerns | get_chat_system_prompt() and chat AJAX handlers |
Professionals either presented to real boards with limited rehearsal, sought informal feedback from individual mentors who could only provide their own functional perspective, used generic AI chatbots that lack governance-style structure, or simply went in unprepared for the multi-dimensional scrutiny that executive teams apply.
Primary category: AI-powered business decision support / executive coaching tools Market maturity: Emerging — AI business advisory tools exist but multi-agent board simulation is a niche category Key dynamics: The broader AI assistant market is saturated with general-purpose chatbots, but domain-specific multi-agent evaluation tools remain rare. Enterprise consulting firms charge premium rates for advisory services that this tool partially automates. The WordPress distribution model creates accessibility that SaaS-only competitors lack. [CLAUDE NOTE: inferred from market observation]
| Product / Company | Approach | Strengths | Key gap this project addresses | Source |
|---|---|---|---|---|
| Generic AI chatbots (ChatGPT, Claude.ai) | Single-perspective general assistant | Broad knowledge, conversational | No structured multi-role evaluation; no governance-style rubrics | ⚡ General market knowledge |
| Management consulting firms | Human advisory boards | Deep domain expertise, relationships | Cost ($10K+), slow turnaround, limited accessibility | ⚡ General market knowledge |
| AI business plan generators | Template-based document creation | Structured output, quick | Generate plans, don’t evaluate them critically from multiple perspectives | ⚡ General market knowledge |
Executive Advisor Board occupies a unique niche: structured, multi-perspective AI evaluation of business proposals with governance-style rigor. It sits between expensive human advisory services and shallow AI chatbot interactions, providing the structure and role-specific critique of the former at the speed and cost of the latter. [CLAUDE NOTE: inferred from product architecture]
The plugin’s defensibility lies in its curated agent prompt library (8 shipped + extensible custom agents), its structured 76-field proposal form that forces thorough preparation, and its consolidation logic that synthesizes multi-agent outputs into actionable governance-style summaries. The extended knowledgebase includes additional agent definitions (CRO, CPO, CCO) and templates for creating new board personas. WordPress ecosystem distribution and extensibility via hooks/filters create platform lock-in advantages. [CLAUDE NOTE: inferred from codebase analysis]
Requirements were driven by modeling the real-world executive advisory board process: structured proposal submission, independent role-specific evaluation, conflict-aware synthesis, and deliberative follow-up. The 12-section form structure maps directly to the categories that real C-suite evaluators assess. [CLAUDE NOTE: inferred from form structure and agent design]
Hard constraints:
Explicit non-goals:
| Decision | Alternatives considered | Rationale | Evidence source |
|---|---|---|---|
| Sequential agent processing | Parallel API calls | Cost control, rate limit management, progressive UX feedback | frontend.js agent queue implementation |
| File-based agent prompts (.txt) | Database-only prompts | Version-controllable, portable, readable; custom agents via CPT extend without modifying files | agents/*.txt + ea_agent CPT registration |
| AES-256-CBC encryption for stored proposals | Plain text storage, WordPress encryption | Proposal data may contain sensitive business information; defense-in-depth | encrypt_data/decrypt_data in executive-advisor.php |
| Consolidation as separate LLM pass | Client-side aggregation, manual review | Produces conflict-aware synthesis that mechanical aggregation cannot achieve | consolidate_results() implementation |
| Optional n8n workflow routing | Direct API only | Enables centralized monitoring, logging, and fallback management via ITI infrastructure | ITI_Workflow_Adapter integration |
KB type: File-based agent prompts (.txt) + extended agent specifications + operational templates Location in repo: executive-advisor-plugin/agents/ (runtime), knowledgebase/ and knowledgebase/agents-extended/ (development/extended) Estimated size: 8 runtime agent prompts + 10+ extended agent specifications + 4 operational templates
executive-advisor-plugin/agents/ # Runtime agent prompts (shipped with plugin)
├── ceo.txt
├── cfo.txt
├── chro.txt
├── cmo.txt
├── coo.txt
├── cto.txt
├── gc.txt
└── board.txt
knowledgebase/ # Development & extended knowledge
├── agents-extended/ # Richer agent specs with XML-like sections
│ ├── CEO, CFO, CMO, COO, CTO, CHRO, GC, Board
│ ├── CRO, CPO, CCO # Additional roles
│ ├── Ecclectic variants
│ └── Calling Agents # Cursor invocation patterns
├── Board Role Modifications for Director Proposals
├── Director Proposal to Board Followup Process
├── Initial Director to Board Pitch Template
├── Board Roles Creation Template Prompt
├── embeddings/ # Empty — placeholder
├── guardrails/ # Empty — placeholder
└── disambiguations/ # Empty — placeholder
| Category | Files / format | Purpose | Update frequency |
|---|---|---|---|
| Runtime agent prompts | 8 × .txt files in agents/ | Define role, rubric, and structured output format for each C-suite persona | Per release |
| Extended agent specs | 10+ files in agents-extended/ with XML-like structure | Richer specifications with {{variable}} placeholders |
Development reference |
| Operational templates | 4 × Markdown files at knowledgebase root | Board composition, director proposal templates, follow-up process documentation | As needed |
| Consolidation prompt | Inline in PHP (consolidate_results) | Produces executive summary synthesizing all agent evaluations | Per release |
| Chat system prompt | Inline in PHP (get_chat_system_prompt) | Governs follow-up conversation behavior with full evaluation context | Per release |
The agent prompt library was developed by modeling real C-suite evaluation frameworks. Each agent prompt defines the executive’s role, specific evaluation rubric, and structured output format (e.g., CEO: Decision, Rationale, Strengths, Concerns, Risk Assessment, Next Steps; Board: Recommendation enum, reasoning sections, Boardroom Questions). Extended agent specifications in the knowledgebase add richer context with XML-structured sections for more complex evaluation scenarios. The Board Roles Creation Template provides a framework for defining new virtual board members. [CLAUDE NOTE: inferred from prompt file structure and content]
System prompt approach: Each agent has a dedicated .txt prompt file loaded at runtime. Custom agents can be created as WordPress custom post types (ea_agent) with title, content (prompt), and icon metadata. Resolution order: custom CPT → file-based prompt → embedded fallback. Key behavioural guardrails: Role-specific evaluation rubrics; structured output format enforcement; consolidation prompt requires explicit identification of consensus areas, conflicts between agents, and outstanding concerns. Persona / tone configuration: Each agent adopts its C-suite role’s perspective and communication style (e.g., CFO focuses on financial metrics and ROI; GC focuses on legal and regulatory risk). Tool use / function calling: No tool use — pure prompt-based evaluation with structured output parsing via regex/heuristics (extract_decision function).
Built as a WordPress plugin following the ITI product development pattern: single main class architecture, AJAX/REST endpoints, file-based agent prompts for version control, and optional integration with the ITI n8n workflow infrastructure for centralized monitoring. Development progressed from core form and agent evaluation through streaming, PDF export, and chat features.
| Phase | Approximate timeframe | What was built | Key commits or milestones |
|---|---|---|---|
| v1.0.0 | Late March 2026 [CLAUDE NOTE: inferred from plugin file mtime 2026-03-29] | Core plugin: 76-field form, 8 agents, sequential evaluation, consolidation, streaming, PDF export, chat, GDPR, audit logging | Initial release per plugin header |
Development context references Cursor as the primary IDE with CLAUDE.md providing product context. The knowledgebase/agents-extended/Calling Agents file documents patterns for invoking agent prompts within the Cursor development workflow. The ITI shared library and operations-level agent system provide cross-product development patterns.
| Challenge | How resolved | Evidence |
|---|---|---|
| Sequential multi-agent evaluation UX | Progress UI with agent queue display; each agent result rendered as it completes | frontend.js agentQueue/currentAgentIndex state management |
| Streaming long agent responses | REST endpoint with Server-Sent Events via cURL; separate from non-streaming AJAX path | handle_stream_message and process_agent_streaming in executive-advisor.php |
| Proposal data security | AES-256-CBC encryption using derived key from ea_encryption_key + AUTH_KEY; proposal payloads encrypted at rest | encrypt_data/decrypt_data functions |
| Conflict-aware synthesis | Separate consolidation LLM pass with structured prompt requiring explicit consensus/conflict/concern analysis | consolidate_results() implementation |
| Agent extensibility | WordPress CPT (ea_agent) merged into active agents list; documented filters for prompt customization | get_active_agents() and ea_agent_prompt filter |
| Model / API | Provider | Role in product | Integration method |
|---|---|---|---|
| Claude (default: claude-sonnet-4-20250514) | Anthropic | Multi-agent proposal evaluation, consolidation, follow-up chat | Direct Messages API via wp_remote_post + optional ITI_Workflow_Adapter |
| Tool | Category | Purpose |
|---|---|---|
| Sequential agent queue | Orchestration | Process 8+ agents one at a time with progress feedback |
| Consolidation pass | Synthesis | Second LLM call to synthesize all agent outputs into unified summary |
| ITI_Workflow_Adapter (optional) | Routing | Routes first API attempt through n8n webhook before falling back to direct Anthropic calls |
| Tool | How used in build |
|---|---|
| Cursor IDE | Primary development environment with CLAUDE.md context |
| Claude AI | Agent prompt development and iteration |
| Version / Phase | Date | Summary of changes | Significance |
|---|---|---|---|
| 1.0.0 | Initial release — no dedicated product git history (monorepo); plugin file mtime 2026-03-29 suggests late-March 2026 shipping build [CLAUDE NOTE: inferred from file mtimes] | Initial release: 8 C-suite agents, 76-field structured form (counted in get_all_input_fields()), sequential evaluation with streaming, consolidation, follow-up chat, PDF export, GDPR consent, audit logging, rate limiting, data retention |
Full feature launch |
The knowledgebase contains extended agent specifications (CRO, CPO, CCO, ecclectic variants) that are not wired into the runtime plugin, suggesting a planned expansion of the board composition that has not yet shipped. Widget support is referenced in CLAUDE.md but not implemented.
| Artifact | Path | Type | What it shows |
|---|---|---|---|
| Frontend form template | executive-advisor-plugin/templates/frontend-form.php | PHP template | 12-section structured proposal form UI |
| PDF export template | executive-advisor-plugin/templates/pdf-template.php | PHP template | HTML layout for client-side PDF generation |
| Admin templates | executive-advisor-plugin/templates/admin/ | PHP templates | Dashboard, submissions, settings, audit log views |
| Frontend CSS | executive-advisor-plugin/assets/css/frontend.css | Stylesheet | Form and evaluation display styling |
| Frontend JS | executive-advisor-plugin/assets/js/frontend.js | JavaScript | Agent queue, streaming, chat, PDF export client logic |
| Document | Path | Type | Status |
|---|---|---|---|
| Plugin README | executive-advisor-plugin/README.md | Markdown | Current (v1.0.0) |
| Documentation README | documentation/README.md | Markdown | Current — includes installation, security, support |
| End-user HTML documentation | documentation/*.html | HTML | Complete set: Getting Started, User Manual, Troubleshooting, FAQ, Glossary |
| WordPress-ready HTML pages | documentation/wordpress-pages/*-WP.html | HTML | Ready for paste-into-WordPress with ea-docs-* namespacing |
| WordPress Conversion Summary | documentation/WordPress-Conversion-Summary.md | Markdown | Documents HTML-to-WordPress conversion process |
| Board Roles Template | knowledgebase/Board Roles Creation Template Prompt | Text | Framework for defining new virtual board members |
| Artifact | Path | Description |
|---|---|---|
| Plugin ZIP (v1) | plugin-installs/executive-advisor-plugin.zip | Installable WordPress plugin package |
| Plugin ZIP (v2) | plugin-installs/executive-advisor-plugin-v2.zip | Updated installable package |
The product originated from the observation that most professionals lack access to the multi-perspective scrutiny that executive teams and boards apply when evaluating business proposals. Real advisory board engagements cost thousands of dollars and take weeks; informal mentorship provides only a single functional perspective. AI’s ability to adopt distinct personas and apply structured evaluation rubrics made it possible to simulate the multi-role advisory experience at a fraction of the cost and time. [CLAUDE NOTE: inferred from product design and documentation positioning]
Research approach used: Informal / product-architecture-driven; no formal market research document found in the repo [CLAUDE NOTE: inferred from absence of research files] Key market observations:
What existing products got wrong: They treat business evaluation as a monolithic task rather than a multi-perspective deliberation where different functional leaders genuinely disagree based on their priorities and rubrics. [CLAUDE NOTE: inferred]
If we give professionals access to a structured, multi-agent evaluation process that models how real C-suite teams scrutinize proposals — with genuine role-specific rubrics and conflict-aware synthesis — they will be better prepared for real board presentations and make better business decisions, at 1/100th the cost of human advisory services. [CLAUDE NOTE: inferred from product architecture]
The product started as a core multi-agent evaluation engine and expanded to include streaming for better UX during long evaluations, consolidation for cross-agent synthesis, follow-up chat for interactive exploration, and PDF export for portability. The knowledgebase shows plans to expand beyond the initial 8 agents to include CRO, CPO, CCO, and ecclectic variants, as well as director-level proposal workflows and board follow-up processes. [CLAUDE NOTE: inferred from codebase artifacts]
What works well: Complete end-to-end evaluation pipeline from structured proposal submission through multi-agent assessment, conflict-aware consolidation, interactive chat, and PDF export. Comprehensive admin tools including audit logging, API testing, and data retention management. Extensive documentation including HTML user guides ready for WordPress deployment. Current limitations: Plugin header references “Claude Opus 4.5” while code defaults to Sonnet 4 (marketing/code mismatch). Budget cap setting exists but is not enforced in API paths. Widget support documented but not implemented. Version numbers in various docs may not be synchronized. Duplicate directory structure (root vs “Executive Advisor/” subfolder) creates confusion. Estimated completeness: Beta — core functionality complete, but several documented features are unimplemented and knowledge expansion paths are empty.
_Manual input required — this section cannot be populated automatically._
| File / Path | What it contributed |
|---|---|
| executive-advisor-plugin/executive-advisor.php | Sections 1, 2, 4, 5, 6, 7 — plugin metadata, form fields, agent processing, API integration, encryption, consolidation, chat, streaming, activation defaults |
| executive-advisor-plugin/README.md | Sections 1, 2, 8 — product description, changelog, hooks/filters documentation |
| documentation/README.md | Sections 1, 2 — user positioning, security documentation, cost guidance, support details |
| executive-advisor-plugin/agents/*.txt | Section 5 — agent prompt content, rubric structure, output format specifications |
| knowledgebase/agents-extended/* | Section 5 — extended agent specifications, additional roles (CRO, CPO, CCO) |
| knowledgebase/Board Roles Creation Template Prompt | Section 5 — framework for defining new board personas |
| CLAUDE.md | Sections 1, 4, 6 — product positioning, technical stack, ITI shared library references |
| documentation/WordPress-Conversion-Summary.md | Section 9 — documentation artifact details |
| executive-advisor-plugin/assets/js/frontend.js | Section 6 — frontend architecture, agent queue state management |
The multi-agent AI advisory space has gone from an empty niche to an active competitive category in under six months. When Executive Advisor Board shipped v1.0.0 in March 2026, the concept of simulating a full C-suite board deliberation through distinct AI personas was genuinely novel. By April 2026, Consensus AI has launched a direct boardroom simulator with voting mechanics and debate, OpenClaw offers multi-agent council workflows with persistent memory, and McKinsey’s Lilli has scaled to 60,000 internal agents. ChatGPT’s Projects feature now enables any user to create a DIY advisory board with persistent company context for free.
The vibe coding explosion accelerates this convergence. With 82% of developers using AI coding tools and platforms like Bolt.new enabling non-technical users to build full-stack apps, the barrier to creating a “multi-agent evaluation tool” is collapsing. A competent prompt engineer can now replicate Executive Advisor’s basic architecture — sequential agent evaluation with consolidation — in a weekend using CrewAI, AutoGen, or a ChatGPT Projects setup. The commodity here is the pattern. The defensible value is in the specificity: the 76-field structured form that forces rigorous preparation, the role-specific rubrics refined through consulting experience, the conflict-aware consolidation that surfaces real tensions, and the self-hosted WordPress deployment that keeps sensitive business proposals off third-party servers.
For ITI’s consulting portfolio, Executive Advisor Board demonstrates something specific about AI product development: multi-agent orchestration is a pattern anyone can implement, but multi-perspective evaluation that produces genuinely useful governance-style feedback requires deep understanding of how real boards operate. The competitive response is not to race on agent count or model variety — it is to deepen the evaluation quality and add features that require judgment about what makes board feedback actionable.
| Competitor | Category | Threat Level | Key Capability |
|---|---|---|---|
| Consensus AI (boardconsensus.ai) | Direct boardroom simulator | High | C-suite role assignment, debate simulation, conflict flagging with voting, strategic briefs |
| OpenClaw Multi-Agent Councils | Framework/SaaS | Medium | CFO/CMO/CTO/COO council workflows, parallel monitoring, persistent memory across sessions |
| Verve Intelligence | Startup validation | Medium | Investor-grade due diligence in 30 minutes; “kill vector” analysis |
| Deloitte Zora AI / C-Suite AI | Enterprise | Low | Ready-to-deploy agents for finance, HR, supply chain; CFO-specific 10-dimension insights |
| ChatGPT Projects (DIY boards) | Substitute | Medium | Free; any user can build persistent advisory boards with company context |
| Feature | Who Has It | Executive Advisor Status |
|---|---|---|
| Multi-model support (GPT-4o, Claude, Gemini per agent) | Consensus AI, OpenClaw | Single model (Claude) only |
| Voting/polling mechanics for agent disagreements | Consensus AI | Consolidation pass only — no explicit voting |
| Persistent organizational memory across sessions | OpenClaw, ChatGPT Projects | No persistence — each evaluation is independent |
| Agent-to-agent observable debate | Consensus AI, CrewAI, AutoGen | Sequential evaluation only — no inter-agent dialogue |
| Mobile app (iOS) | Consensus AI | WordPress responsive only |
| Second/third-order effect analysis | Consensus AI | Not explicitly structured |
| Feature | Erosion Level | What Remains |
|---|---|---|
| Multi-perspective C-suite evaluation | Significant — Consensus AI, OpenClaw, and ChatGPT Projects all offer this | Our 76-field form and 8 shipped agents (11 specified) remain most comprehensive |
| Conflict identification between agents | Significant — Consensus AI adds voting resolution | Our consolidation pass is architecturally sound but lacks observable debate |
| Structured proposal input | Partial — Verve Intelligence has a 7-phase framework | Our 12-section, 76-field form is still the most rigorous structured input |
| Self-hosted WordPress deployment | Maintained | Only multi-agent board simulator that runs on customer infrastructure |
| Enterprise data handling (encryption, GDPR, audit) | Maintained | No competitor in this niche offers AES-256 encryption at rest |
The roadmap prioritizes completing what was already designed (CRO/CPO/CCO agents that exist in the knowledgebase), then building features that deepen evaluation quality rather than chasing competitor features like voting mechanics.
Tier 1 — Critical (Next Build Cycle)
Tier 2 — High Value (Near-Term)
Tier 3 — Strategic (Medium-Term)
Prioritization rationale: The version comparison feature (Tier 1) represents the highest-value white-space opportunity — no competitor offers before/after delta analysis showing how revisions improved scores. Persistent organizational context (Tier 2) addresses the #1 user complaint about AI tools (context loss across sessions) in a way that self-hosted WordPress makes uniquely defensible. Agent deliberation (Tier 2) responds to Consensus AI’s debate mechanics without copying their voting approach — we show the reasoning chain instead.
| Skill | What It Enables |
|---|---|
multi-agent-deliberation-design |
Design patterns for agent-to-agent debate, voting mechanics, conflict resolution strategies, and consensus synthesis. Directly supports the Tier 2 agent deliberation display and informs architectural decisions about sequential vs. parallel pipelines. |
business-proposal-evaluation |
Structured executive rubrics covering financial viability, strategic alignment, operational feasibility, legal/compliance risk, and organizational readiness. Used when writing or refining agent prompts and building industry-specific evaluation templates. |
proposal-evaluation |
The broader eight-perspective evaluation framework that underpins the Executive Advisor concept. Covers strategic, financial, operational, market, people, technical, legal, and governance lenses. |
agentic-task-execution |
Patterns for AI agents performing real-world actions with confirmation flows and audit logging. Supports the Tier 3 action plan pipeline where board recommendations become executable project plans. |
Strengths:
Gaps we’re honest about:
What we’re watching:
Portfolio context: Executive Advisor Board demonstrates ITI’s ability to design multi-agent AI systems where the orchestration pattern (sequential evaluation with conflict-aware consolidation) and the domain knowledge (governance-style rubrics from real C-suite evaluation frameworks) matter more than the underlying model. The product makes a specific claim: structured multi-perspective evaluation produces better decision-support than single-perspective AI chat. That claim is testable and the product architecture backs it up.