Executive Advisor Board — Updated Product Roadmap

Date: April 14, 2026 Previous roadmap date: None — first roadmap Based on: Competitive analysis of 10 competitors + user needs research from Reddit, Indie Hackers, and startup validation communities

Current Product State

What’s Built and Shipped (v1.0.0)

Capability	Status	Notes
8 C-suite agent personas (CEO, CFO, CTO, CMO, COO, CHRO, GC, Board)	Shipped	File-based prompts in agents/*.txt
76-field structured proposal form (12 sections)	Shipped	Most comprehensive input form in category
Sequential agent evaluation with streaming	Shipped	Progressive UI with agent queue display
Conflict-aware consolidation pass	Shipped	Separate LLM call synthesizing consensus/conflicts/concerns
Follow-up chat with full evaluation context	Shipped	Interactive exploration of any evaluation aspect
PDF export	Shipped	Client-side generation
AES-256-CBC encryption at rest	Shipped	Proposal data security
GDPR consent mechanism	Shipped	Required before submission
Audit trail logging	Shipped	All submissions and evaluations tracked
Rate limiting + data retention	Shipped	Configurable via admin settings
Custom agent CPT (ea_agent)	Shipped	Extensible via WordPress custom post types
n8n workflow adapter (optional)	Shipped	Routes through n8n for centralized monitoring

Known Gaps from v1.0.0

Item	Status
CRO, CPO, CCO agent specifications	Written in knowledgebase/agents-extended/ but NOT wired into runtime
Budget cap enforcement	Admin setting exists but not enforced in API call paths
Widget support	Referenced in CLAUDE.md but not implemented
Embeddings/guardrails/disambiguations	Directory placeholders exist but are empty
Model reference mismatch	Plugin header says “Claude Opus 4.5” but code defaults to Sonnet 4

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Competitive Landscape Changes (Since Last Review)

New Competitor Entrants

Competitor	Type	What They Do	Threat Level
Consensus AI (boardconsensus.ai)	SaaS	Direct boardroom simulator — assigns LLMs to C-suite roles, simulates debate with conflict flagging and voting, produces strategic briefs	HIGH — most direct competitor
OpenClaw Multi-Agent Councils	Framework/SaaS	Multi-agent council workflows with CFO/CMO/CTO/COO personas, parallel monitoring, persistent memory across sessions	MEDIUM — framework-oriented, not turnkey
Verve Intelligence	SaaS	AI startup validation platform delivering investor-grade due diligence in 30 minutes with “kill vector” analysis	MEDIUM — overlaps on proposal evaluation
Deloitte Zora AI	Enterprise	Ready-to-deploy agents for finance, HR, supply chain, procurement, sales, marketing	LOW — enterprise-only, not self-hosted
Deloitte C-Suite AI for CFOs	Enterprise	CFO-specific insights across 10 dimensions (IR, risk, M&A, cost optimization, ESG, talent)	LOW — single-role, enterprise pricing

Features Competitors Have Added

Feature	Who Has It	Our 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	No voting — consolidation pass only
Persistent organizational memory across sessions	OpenClaw, ChatGPT Projects	No persistence — each evaluation is independent
Mobile app (iOS)	Consensus AI (App Store listing)	WordPress responsive only
Second/third-order effect analysis	Consensus AI	Not explicitly structured
Agent-to-agent debate (observable back-and-forth)	Consensus AI, CrewAI, AutoGen	Sequential evaluation — no inter-agent dialogue

Eroded Differentiators

Previously Unique Feature	Competitor Matching It	Erosion Level
Multi-perspective C-suite evaluation	Consensus AI (5 agents), OpenClaw councils, ChatGPT Projects advisory boards	Significant — no longer unique concept
Structured proposal input form	Verve Intelligence (7-phase validation framework)	Partial — our 76-field form remains most structured
Conflict identification between agents	Consensus AI (conflict flagging + voting)	Significant — Consensus adds voting resolution

What Remains Differentiated

Feature	Why It’s Still Unique
76-field, 12-section structured proposal form	Most comprehensive structured input in category — forces rigorous preparation
Self-hosted WordPress deployment	Only multi-agent board simulator that runs on customer’s own infrastructure
8 shipped agents (11 specified)	Broadest C-suite coverage including CHRO, GC, Board
GDPR/encryption/audit trail built in	Enterprise-grade data handling in a self-hosted plugin
Extensible via WordPress CPT + hooks/filters	No-code agent customization for WordPress users

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Updated Gap Analysis

Parity Gaps (Must-Have to Compete)

#	Feature	Who Has It	Priority	Effort
P1	Wire CRO, CPO, CCO agents into runtime	Consensus (5 agents), OpenClaw (4+)	Critical	S — specs exist, need runtime integration
P2	Budget cap enforcement in API paths	Table stakes for production use	Critical	S — setting exists, enforce in call path
P3	Multi-model support (at least Claude + GPT-4o)	Consensus, OpenClaw, AI Agent Hub WP	High	M — abstract model provider in shared Claude API client
P4	Model reference cleanup (header vs runtime)	Internal quality	Critical	S — trivial text fix

White-Space Opportunities (Differentiation)

#	Opportunity	Why It’s Unique	User Need Evidence	Priority
W1	Proposal version comparison (“v1 vs v2” re-evaluation)	No competitor offers before/after delta analysis showing how revisions improved scores	Users on Reddit report needing iterative feedback loops, not one-shot evaluation	High
W2	Persistent organizational context across evaluations	Self-hosted WordPress stores org context locally — competitors can’t match data sovereignty	#1 Reddit complaint: AI “forgets everything every conversation” costing 91+ hours/year	High
W3	“Boardroom Questions” preparation drill	Generate likely tough questions each agent would ask in a live board meeting, with coaching on answers	Users say the tool should teach them to “anticipate questions from different perspectives” (from docs)	High
W4	Industry-specific evaluation templates (SaaS, healthcare, manufacturing, nonprofit)	Pre-configured proposal templates + agent rubric adjustments per industry vertical	Verve Intelligence does vertical validation; no board simulator does industry-tuned evaluation	Medium
W5	Agent personality spectrum (conservative ↔ aggressive risk tolerance)	Let users dial agent risk appetite to simulate different board compositions	No competitor offers tunable agent personalities — all use fixed personas	Medium

AI-Native Opportunities

#	Opportunity	How Claude/AI Enables It	Competitor Status
A1	Proactive weakness detection before full board evaluation	Pre-scan proposal for obvious gaps using lightweight Claude call, suggest improvements before costly 8-agent run	No competitor offers pre-evaluation coaching
A2	Agent-to-agent deliberation (observable debate)	Extended thinking + multi-turn agent exchange where CFO challenges CTO’s cost assumptions, etc.	Consensus has debate mechanics; ours could show the reasoning chain
A3	Executive summary → action items → project plan pipeline	Post-evaluation, generate a concrete implementation plan from the board’s recommendations	All competitors stop at advisory output — none generate actionable project plans
A4	Tavily-powered real-time market context injection	Agents cite current market data, competitor info, and industry benchmarks during evaluation	No competitor injects live web research into agent evaluations
A5	RAG knowledge base per organization	Embed company documents (financials, org charts, strategy docs) for context-aware evaluation	OpenClaw has persistent memory; WordPress + Pinecone enables private, self-hosted RAG

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Updated Feature Roadmap

Tier 1 — Critical (Next Build Cycle)

• [ ] Wire CRO, CPO, CCO agents into runtime — Specifications exist in knowledgebase/agents-extended/; register as default agents in get_active_agents(), add .txt prompt files to agents/ — S
• [ ] Enforce budget cap in API call paths — Check ea_budget_cap setting before each Claude API call, return user-friendly error when exceeded — S
• [ ] Fix model reference mismatch — Update plugin header description to match runtime default (claude-sonnet-4-20250514); add admin setting for model selection — S
• [ ] Proposal version comparison — Store evaluation results with version numbers; add “Revise & Resubmit” flow that pre-fills previous proposal data; generate delta report showing score changes per agent — M
• [ ] Pre-evaluation proposal scan — Lightweight Claude call (~500 tokens) that identifies missing sections, weak areas, and obvious gaps before running full 8-11 agent evaluation; saves users money on incomplete proposals — M

Tier 2 — High Value (Near-Term)

• [ ] Persistent organizational context — New DB table storing org profile (industry, size, strategy docs summary, previous evaluations); auto-inject into agent prompts; accumulates across evaluations — L
• [ ] Boardroom Questions drill mode — Post-evaluation feature generating 5-10 tough questions per agent with coaching on how to answer; exportable as preparation worksheet — M
• [ ] Agent-to-agent deliberation display — After individual evaluations, run a second pass where agents with conflicting assessments exchange one rebuttal each; display as observable debate thread — L
• [ ] Multi-model provider support — Abstract model selection in shared Claude API client; support Claude, GPT-4o, and Gemini; per-agent model assignment in admin — M
• [ ] Industry-specific evaluation templates — 4 starter templates (SaaS/Tech, Healthcare, Manufacturing, Nonprofit) with pre-configured form defaults and adjusted agent rubrics — M

Tier 3 — Strategic (Medium-Term)

• [ ] Tavily-powered market context injection — Before agent evaluation, run Tavily search for industry/competitor data; inject as context alongside proposal; agents cite real market data — L
• [ ] RAG knowledge base per organization — Pinecone integration using shared library client; users upload company docs (org chart, financials, strategy deck); agents reference during evaluation — L
• [ ] Agent personality tuning — Admin slider for each agent (conservative ↔ aggressive risk tolerance); adjusts prompt language and evaluation thresholds — M
• [ ] Executive summary → action plan pipeline — Post-consolidation feature generating a structured implementation plan with owners, timelines, milestones, and dependencies from board recommendations — M
• [ ] Evaluation history dashboard — User-facing dashboard showing all past evaluations, score trends, and improvement tracking across proposal versions — M

Tier 4 — Exploratory (Future Consideration)

• [ ] Parallel agent processing — Run agents concurrently (3-4 at a time) for faster evaluation; requires rate limit management and UI redesign for non-sequential display
• [ ] Mobile-optimized evaluation view — Dedicated mobile layout for reviewing results and chat on phone/tablet (form submission remains desktop-recommended)
• [ ] WordPress Multisite support — Shared agent library with per-site customization; centralized billing/usage tracking across network
• [ ] SaaS distribution option — Hosted version for users without WordPress; would require full rewrite of auth/storage layer
• [ ] Board composition presets — Named board configurations (e.g., “Growth Board” emphasizes CMO/CRO/CPO; “Risk Board” emphasizes CFO/GC/COO) with one-click selection
• [ ] Webhook/Zapier integration — Post-evaluation webhook firing to external systems for workflow integration (Slack notifications, CRM updates, project management tools)

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Removed / Deprioritized Items

Item	Disposition	Rationale
Widget support	Removed	Referenced in CLAUDE.md but the shortcode approach is sufficient; widgets add complexity with no clear user value for a full-page evaluation tool
Ecclectic advisor variants	Deprioritized to Tier 4	Creative/non-standard advisors (from knowledgebase) are interesting but dilute the core professional advisory positioning; revisit after core agents are complete

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Cross-Product Opportunities

Opportunity	Products Involved	Description
Multi-model provider abstraction	Executive Advisor, Career Coach, all Claude-powered plugins	Abstract model selection out of individual plugins into shared library ITI Claude API client; support Claude, GPT-4o, Gemini with per-plugin configuration
Persistent user context pattern	Executive Advisor, Career Coach, Estate Manager	WordPress-based organizational/user profile that accumulates across sessions; shared DB schema and injection pattern
Tavily market research integration	Executive Advisor, SEO Assistant, AEO Optimizer, Factchecker	Shared pattern for injecting real-time web research into agent prompts; already in shared library (class-iti-tavily-api.php) but needs agent-integration pattern
PDF export improvements	Executive Advisor, Career Coach, Journey Mapper	Shared PDF generation with consistent branding, better formatting, and server-side rendering option
Pre-evaluation input validation	Executive Advisor, Career Coach	Lightweight AI scan of user inputs before expensive multi-agent processing; shared pattern for “is this input ready?” checks

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New Skills Identified

1. multi-agent-deliberation-design

• Category: AI architecture
• Description: Design multi-agent deliberation workflows including agent-to-agent debate, voting mechanics, conflict resolution strategies, and consensus synthesis. Use when building products where multiple AI agents must evaluate the same input from different perspectives and resolve disagreements.
• Trigger scenarios:

1. Designing agent-to-agent debate features for Executive Advisor
2. Building any product requiring structured AI disagreement and resolution
3. Evaluating CrewAI vs AutoGen vs custom orchestration for deliberation
4. Designing voting/polling mechanics for multi-agent outputs
5. Optimizing token costs in multi-agent sequential vs parallel pipelines

• Products that need it: Executive Advisor (primary), any future multi-agent ITI product
• Source justification: Consensus AI’s voting mechanics, CrewAI/AutoGen benchmark showing 42-86% decision accuracy variance by framework, OpenClaw council architecture — deliberation design is a methodology gap in the current Skills library

2. business-proposal-evaluation

• Category: Business consulting
• Description: Evaluate business proposals through structured executive rubrics covering financial viability, strategic alignment, operational feasibility, legal/compliance risk, and organizational readiness. Use when building or refining AI agents that assess business proposals from specific C-suite perspectives.
• Trigger scenarios:

1. Writing or refining Executive Advisor agent prompts
2. Building evaluation rubrics for new C-suite personas
3. Creating industry-specific evaluation templates
4. Designing proposal scoring and decision frameworks
5. Coaching users on proposal preparation and weakness identification

• Products that need it: Executive Advisor (primary), potentially Career Coach (for career proposal evaluation)
• Source justification: The existing executive-* Skills (CEO, CFO, etc.) cover individual perspectives but no Skill covers the meta-methodology of structured multi-perspective proposal evaluation as a discipline

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Sources

Competitors Analyzed

Competitor	Category	Source
Consensus AI (boardconsensus.ai)	Direct — AI boardroom simulator	Web search, product page
OpenClaw Multi-Agent Councils	Direct — multi-agent advisory workflows	Web search, product page (launchmyopenclaw.com)
McKinsey Lilli	Adjacent — enterprise AI advisor platform	Web search, mckinsey.com
Deloitte Zora AI	Adjacent — enterprise agentic AI	Web search, deloitte.com press release
Deloitte C-Suite AI for CFOs	Adjacent — role-specific executive AI	Web search, deloitte.com
Deloitte Enterprise AI Navigator	Adjacent — multi-perspective AI strategy	Web search, deloitte.com press release
ChatGPT Projects (advisory board pattern)	Substitute — DIY advisory boards	Web search, flexos.work, newcfo.ai
Verve Intelligence	Adjacent — AI startup validation	Web search, marketminute.com
CrewAI / AutoGen frameworks	Platform — multi-agent orchestration	Web search, dev.to, benchmarks
WordPress AI Agent Hub plugin	Platform — WP multi-agent	Web search, wordpress.org

User Needs Sources

Source	Key Insight
Indie Hackers analysis of 500 Reddit AI complaints	#1 frustration is memory/context loss (91+ hrs/year wasted), not hallucination
r/AiForSmallBusiness (Marblism review)	Users want $39-100/month tools saving 21+ hrs/week; 70% draft quality is acceptable with human refinement
r/smallbusiness thread	Users frustrated by overhyped AI tools that “don’t live up to what the AI gurus make you believe”
r/SaaS thread	Gap between “glorified chatbots” and enterprise-only ($1K+/month) platforms
r/AiForSmallBusiness (40+ tools review)	Real value comes from combining 2-4 specialized tools; consistency and reproducibility matter more than raw capability

Search Queries Used

1. “AI business advisor consultant tools multi-agent personas 2026 competitors”
2. “AI executive advisory tool multi-perspective business analysis features 2026”
3. “Reddit r/consulting r/startups r/smallbusiness AI business advisor tool complaints 2026”
4. “ChatGPT custom GPTs business advisor board of directors multi-agent simulation 2026”
5. “AI multi-agent debate deliberation business decisions startup tools 2026 CrewAI AutoGen”
6. “Reddit AI business proposal evaluation feedback tool startups consulting 2026”
7. “Consensus AI boardroom simulator features pricing 2026”
8. “WordPress AI consultant advisor plugin multi-agent 2026”