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Business Analyst · Project Manager · Program Manager · Portfolio Manager

20 years mastering how the work gets done. Now rebuilding it with AI.

AI multiplies the work; the judgment stays mine.

I have operated across every altitude of technology delivery—from understanding the problem to allocating enterprise investment—and now apply that full range as a founder.

See How I Deliver See What I'm Building

1Understand

2Deliver

3Coordinate

4Allocate

The accountability climb

The same rigor, applied at increasing levels of consequence.

Business Analyst

Understanding the problem

Closest to the work. Translating organizational ambiguity into precise specification. If the analyst gets this wrong, everything built downstream is wrong.

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Synthesis

Turning scattered, contradictory human input into a coherent, structured picture.

Credibility anchors

Requirements across five business lines
75% reduction in documentation cycle time
15% improvement in claims processing efficiency

Human inputs

Stakeholder interviews
Existing documentation
Conflicting priorities

AI-assisted synthesis

Cluster
Compare
Clarify

Structured outputs

Structured requirements
Traceability matrix
Process and options analysis

Before

Weeks of manual reconciliation

Multiplied

Days with structured AI support

Still human

The call about what actually matters

Activity 1

Requirements Elicitation & Synthesis

Pre-AI

Interview stakeholders across five business lines. Hand-capture notes, manually cluster themes, reconcile where executives contradict each other, draft the BRD, circulate it, absorb feedback, and manage versions. Weeks of cycle time before a single requirement is validated.

AI-multiplied

Auto-transcribe every session. AI clusters themes across all interviews, surfaces where stakeholders want incompatible things, drafts the structured BRD into a standard template, and flags ambiguities and gaps before anything circulates. Days, not weeks—same rigor, compressed.

Activity 2

Documentation & Traceability

Pre-AI

Build the requirements traceability matrix by hand. Write functional specifications, map every requirement to acceptance criteria and test cases manually, then keep it all synchronized whenever scope changes.

AI-multiplied

Generate the traceability matrix, first-pass acceptance criteria, and test cases directly from the requirements. When a requirement changes, AI propagates the downstream impact and flags what is now out of sync—no silent gaps.

Activity 3

Process Analysis & Solution Definition

Pre-AI

Map the current-state process through workshops and diagrams, identify inefficiencies by inspection, hand-model the future state, and build the case for the solution.

AI-multiplied

AI drafts current- and future-state process maps from interview transcripts and existing documentation, quantifies the improvement opportunity, and generates the options analysis for stakeholder review.

What stays human

Deciding which requirements actually matter to the business—and reading the room when two executives want incompatible things. AI organizes the inputs. The analyst owns the judgment call about what's real.

Project Manager

Delivering the work

Owns a single delivery end to end — scope, schedule, risk, commitment.

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Foresight

Credibility anchors

Cross-functional teams of 8+
Delivery inside complex, multi-project program environments
Agile and hybrid sprint execution
Led onshore and offshore test teams and leads through a major platform migration
99.5% accuracy
40% testing-efficiency gains

Signals

Task slippage
Velocity decline
Open issue patterns

AI-supported foresight

Detect
Forecast
Recommend

PM decisions

Re-sequence work
Escalate risk
Protect scope

Reactive

Risk discovered in status meetings

Multiplied

Risk surfaced before impact

Still human

The commitment and escalation call

Activity 1

Planning & Scheduling

Pre-AI

Build the WBS, sequence tasks, estimate durations, construct and level the schedule by hand. Re-baseline manually every time reality moves.

AI-multiplied

AI drafts the WBS and first-pass schedule from the scope, proposes dependencies and estimates from comparable past projects, and re-forecasts the timeline automatically the moment a task slips.

Activity 2

Status Reporting & Stakeholder Communication

Pre-AI

Chase the team for updates. Hand-assemble the weekly status deck. Re-translate the same update into different formats for executives versus the working team.

AI-multiplied

AI compiles status directly from the task tracker, drafts both the executive summary and the detailed team version from one source of truth, and tunes tone per audience. The PM reviews and sends — minutes, not hours.

Activity 3

Risk & Issue Management

Pre-AI

Maintain the RAID log by hand. Rely on experience to sense emerging risk. Escalate reactively, usually after it has already surfaced in a meeting.

AI-multiplied

AI scans status trends, velocity, and open-issue patterns to flag risks before they escalate, drafts mitigation options, and keeps the RAID log current directly from project activity.

Activity 4

Distributed Team & Quality Leadership

Pre-AI

Coordinate onshore and offshore testers and test leads by hand across time zones — allocate work, chase test coverage, reconcile defect reports, and hold the quality bar through a high-stakes migration by sheer vigilance.

AI-multiplied

AI drafts test coverage from requirements, clusters and de-duplicates defect reports across distributed teams, summarizes overnight offshore progress for the morning handoff, and flags coverage gaps before a release — so the lead manages exceptions, not spreadsheets.

What stays human

Owning the commitment. When to escalate, when to absorb, when to hold the line on scope, and when to have the hard conversation. That accountability does not delegate to a model.

Program Manager

Coordinating at scale

Orchestrates many interdependent projects toward a single enterprise outcome. Success is measured across the whole, not any one part.

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Coordination

Credibility anchors

30–40 interrelated projects
SVP-level governance and prioritization
Executive dashboards in Power BI and Smartsheet

Project network signals

Schedule changes
Cross-project dependencies
Competing resource demands

AI-supported coordination

Map
Detect collisions
Cascade impact

Program decisions

Reconcile timelines
Sequence dependencies
Align owners

Fragmented

Status held across separate project plans

Multiplied

Dependency collisions surfaced early

Still human

The negotiation and coalition-building

Activity 1

Cross-Project Dependency Management

Pre-AI

Manually map dependencies across dozens of projects, chase project managers for status, reconcile conflicting timelines, and hold the collision map in your head or in a sprawling spreadsheet.

AI-multiplied

AI ingests every project plan, maps the full dependency network, and flags where a slip in one project cascades into three others — surfacing the collision weeks before it lands.

Activity 2

Executive Dashboards & Program Health

Pre-AI

Pull data from every project, build the Power BI or Smartsheet dashboard by hand, refresh it each cycle, and write the narrative interpretation for SVP leadership.

AI-multiplied

AI aggregates program data continuously, drafts the health narrative — what is green, what is red, and why — and generates the executive read-out on demand, not once per reporting cycle.

Activity 3

Governance & Prioritization Facilitation

Pre-AI

Prepare governance materials, frame trade-offs for SVP-level sessions, capture decisions live, then manually cascade them back into every affected project.

AI-multiplied

AI prepares the trade-off analysis and scenario comparisons before the session, captures decisions in real time, and drafts the cascade of updates to each impacted project.

What stays human

Holding the line between competing project owners and executives — the negotiation, coalition-building, and judgment about which outcome the program actually exists to serve. AI coordinates the information. The program manager coordinates the people.

Portfolio Manager

Allocating the investment

Decides where finite capital and capacity go across the enterprise. The call carries real money and real consequence.

AI-leverage signature

Decision support

Credibility anchors

$2M+ portfolio
20–30 concurrent initiatives
Governance enhancements that cut project delays by 25%
Influenced multi-million-dollar C-suite decisions

Portfolio inputs

Business cases
Capacity constraints
Strategic priorities

AI-supported decision analysis

Normalize
Compare scenarios
Expose trade-offs

Portfolio decisions

Fund
Defer
Stop

Manual

Weeks to rebuild the prioritization view

Multiplied

Scenario impact surfaced on demand

Still human

The capital allocation call

Activity 1

Investment Prioritization & Portfolio Selection

Pre-AI

Gather business cases, score initiatives against criteria by hand, build the prioritization model, and construct the C-suite recommendation over weeks.

AI-multiplied

AI structures every business case into a consistent scoring model, runs scenario comparisons such as funding one initiative versus another under specific constraints, and drafts the ranked recommendation with the reasoning exposed so it can be challenged, not simply accepted.

Activity 2

Capacity Planning & Resource Allocation

Pre-AI

Manually reconcile demand against capacity across 20–30 initiatives, model what fits, find the bottleneck, and rebuild the whole picture whenever priorities shift.

AI-multiplied

AI models demand versus capacity continuously, simulates the impact of adding or cutting an initiative, and flags the constraint before it becomes a delay.

Activity 3

Executive Reporting & Portfolio Governance

Pre-AI

Consolidate portfolio performance, build the C-suite deck, translate delivery data into investment language, and prepare for the hard questions by hand.

AI-multiplied

AI consolidates performance into the investment narrative, anticipates the C-suite’s likely questions and drafts the answers, and keeps the governance view current between meetings, not only for them.

What stays human

The allocation call itself. Which bets the enterprise makes with finite capital, when to kill a sunk-cost initiative, and standing behind a multi-million-dollar recommendation in front of the C-suite. AI sharpens the decision. The portfolio leader owns it.

Founder capstone

Building the whole thing.

The four roles show how I operate across increasing levels of accountability. The founder story shows what happens when I apply that full range to something I am building myself.

A separate movement after the climb — not a fifth rung, but all four altitudes operating at once.

Pre-AI build

CareVizor

A digital childcare marketplace founded and taken from concept to market. Badou owned the whole arc alone at the helm: product strategy, requirements and specifications, vendor and developer coordination, roadmap, budget, and launch.

Every function that AI now accelerates — synthesis, drafting, coordination, and analysis — was done by hand, by one founder directing a small team.

AI-multiplied build

TopCloserR

A live multi-sided marketplace, materially more ambitious in scope and architecture than what one founder could reasonably have shipped solo a decade earlier.

The same founder instinct, now multiplied: AI compresses the synthesis, drafting, and coordination that once capped a solo builder's reach, allowing one operator to direct work at a scale that previously required a larger team.

Same founder instinct. Different era. Dramatically different leverage.

CareVizor

Product strategy
Requirements
Vendor coordination
Roadmap
Budget
Launch

AI multiplier

Synthesis
Drafting
Coordination
Analysis

TopCloserR

Multi-sided marketplace
Broader operating scope
AI-directed build process
Ongoing product evolution

Then

One founder directing a small team

Now

One founder directing AI across the operation

Constant

Vision, judgment, and accountability

What stays human

The vision, the judgment about what to build and why, and the accountability for the whole. AI multiplies a founder's reach; it does not decide what the company should be. That call — then and now — is Badou's.

The constant

The work changes. The accountability does not.

Across every altitude, AI increases speed, scale, and reach. The human responsibility rises with the stakes.

Define what is real

Decide which requirements actually matter.

Own the commitment

Escalate, absorb, and hold the line on scope.

Coordinate the people

Align competing owners around the outcome.

Stand behind the investment call

Choose where finite capital and capacity go.

All 4

Founder application

Own the whole venture

Decide what should be built and why.

AI multiplies the work. It does not inherit the judgment or the accountability.

Contact

Start a conversation.

Whether the need is understanding the problem, delivering the work, coordinating at scale, allocating investment, or building something new, start with the challenge in front of you.

Submissions will notify me by email so I can respond promptly.