PKG: Rapid Business Case Builder
One-time discovery engagement
Feed: exec transcripts, market data → Deliver: structured business case
- EBITDA impact modeling (we did: 40%→80% margin shift)
- Headcount leverage analysis (we did: 2,800 analyst baseline)
- Revenue opportunity sizing with go/no-go recommendation
- Competitive landscape positioning
📄 Deliverable: Business case document with financial projections — delivered in hours
PKG: Product Strategy & Market Sizing
Always-on market intelligence
Recurring: product council inputs → continuous market fit analysis
- Continuous TAM/SAM refinement as market data changes
- Feature-to-revenue attribution modeling
- Competitive positioning updates per release cycle
- Portfolio opportunity scoring across product lines
🔄 Deliverable: Living product strategy dashboard — updates every cycle
PKG: AI Agent Requirements Engineering
Extract specs from stakeholders
Feed: recordings, docs, interviews → Deliver: agent-ready specs
- Transcript-to-requirements extraction (we did: May 7 Krishna session)
- Pre-filled questionnaires from existing context (we did: A.6 Vitals)
- Gap analysis against target capabilities
- 30-min validation replaces weeks of BA workshops
📄 Deliverable: Structured requirements spec + domain questionnaire
PKG: Product Definition & Prioritization
Decide what to build next and why
Recurring: user feedback, usage data, strategy → prioritized backlog
- Feature-level revenue impact scoring (we did: A.6-A.12 ranking)
- Requirements extraction from customer interviews at scale
- Cross-product dependency mapping for sequencing
- Prioritization framework that compounds — not one-time ranking
🔄 Deliverable: Prioritized feature backlog with revenue justification — per sprint
PKG: Platform Architecture Assessment
Evaluate reuse, estimate effort
Feed: codebase + target requirements → Deliver: reuse matrix + LOE
- Code reuse analysis by layer (we did: Mythos 80% arch / 10% data / 0% domain = 40%)
- Integration gap mapping against status (we did: TEK/APO inventory)
- LOE breakdown by resource type (we did: AI vs. human SME vs. platform eng)
- Risk-rated pre-build blocker analysis per deliverable
📄 Deliverable: Architecture assessment + reuse matrix + effort estimate
PKG: Platform Economics & Build/Buy Analysis
Shape platform vs. bespoke decisions
Per decision: platform state + target → build/buy/extend recommendation
- Platform-vs-bespoke economics per feature (not just "can we reuse code?")
- Integration investment analysis — which connectors unlock the most value?
- Technical debt quantification tied to product velocity
- Resource model that informs hiring, not just project staffing
🔄 Deliverable: Platform investment thesis — updated per product decision
PKG: Sprint Planning & Roadmap Generation
From backlog to execution plan
Feed: backlog + constraints → Deliver: release roadmap + sprint backlogs
- Multi-track GANTT with dependencies (we did: 28 tasks, 4 teams, live dashboard)
- Critical path analysis per sprint (we did: TEK-154 → TEK-95 ∥ TEK-106)
- Resource constraint identification + mitigation plans
- Cross-team dependency mapping with escalation triggers
📄 Deliverable: Release plan + sprint backlogs + live GANTT dashboard — in minutes
PKG: Capacity Optimization & Sprint Intelligence
Maximize value per engineering sprint
Continuous: capacity + priorities → optimal allocation each cycle
- Sprint-over-sprint capacity allocation optimization
- "Are we building the right thing?" analysis — not just "will we hit the date?"
- Velocity trending + bottleneck detection across teams
- Scenario modeling: what ships if we add/remove a resource?
🔄 Deliverable: Sprint intelligence brief — auto-generated every cycle
PKG: Managed Delivery Intelligence
Continuous program tracking to completion
Ongoing: status updates, tickets, comms → Deliver: program view with change detection
- Multi-source status aggregation (we did: PDF + Slack + GitHub + screenshots)
- Change detection: "3 new items, 1 blocker resolved, critical path shifted"
- Stakeholder briefing prep with positioning guidance
- Blocker escalation with mitigation options
📄 Deliverable: Continuously updated program dashboard + weekly executive brief
PKG: Product Operations & Portfolio Intelligence
Run the product office, not just the project
Continuous: all product signals → portfolio health + trajectory
- Cross-product portfolio health monitoring
- Release readiness scoring — not just "tests pass" but "market-ready?"
- Stakeholder communication automation for recurring updates
- Product lifecycle intelligence: when to invest, sunset, or pivot
🔄 Deliverable: Product operations dashboard + automated stakeholder updates
Phases 5–6: Build, Test & Deploy — Not in AIPMO scope (yet)
~20% of SDLC effort. This is where coding agents, QA automation, and CI/CD live. AIPMO deliberately stops before build — because that's the commodity layer now. The 80% before build is where humans were spending months and millions. That's what we compress to days.
In a Product Development lens, this maps to Engineering Execution (build sprints) and Release & GTM (deployment, launch, adoption). Both are increasingly automated — and increasingly decoupled from the planning intelligence above.
SDLC Pitch
"We deliver Phases 0–4 in days. You only staff Phase 5 (build) and Phase 6 (deploy). That's 80% of the SDLC compressed by 100x."
Sells to: Deloitte, Accenture, KPMG, enterprise PMOs, SIs
Product Dev Pitch
"We make your product team 10x faster at deciding what to build, how to resource it, and whether it's working. Every sprint. Not a one-time engagement."
Sells to: SaaS companies, platform companies, internal product orgs, VCs evaluating portfolios