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Engagements

Ways to bring
me in.

Each track is productized, scoped, and finite. I do not run a fractional-CTO treadmill. Engagements have a beginning, a deliverable, and an end. If we work together longer, it is because the next problem warrants a new engagement, not because the meter keeps running.

Pricing is set after a short intro call. Engagements are calibrated to the target, the portfolio, and the deliverable.

Pre-acquisition

Technical Diligence Sprint

Duration
2 weeks+
Cadence
Fixed scope. Single deliverable. Extends if the target warrants it.

A code-first read of the target. I open the repos. I walk the architecture. I talk to the people. I produce a document the investment committee can act on, not a deck the CEO would have shown you anyway.

For

  • PE Operating Partners on bake-off shortlists
  • Investment teams confirming the technical thesis
  • Acquirers wanting an independent second opinion before LOI

Deliverables

  • → Architecture and codebase truth assessment, not vibes
  • → Engineering org map, key-person concentration, bus factor
  • → AI readiness scorecard scored against where the category is going
  • → Risk surface with remediation cost and timeline estimates
  • → One executive narrative, one technical appendix

What this is not

  • × A slide deck of generic best practices
  • × A vendor security questionnaire
  • × A CIO checklist exercise
Inquire about Technical Diligence Sprint →

Post-close

AI-Native Value Creation

Duration
90 days+
Cadence
Embedded operator. Weekly portfolio-partner sync. Extends by mutual agreement.

I land inside the portfolio company as the temporary AI-Native CTO. Install the execution intelligence layer. Stand up the agent operating model. Ship cost takeout while raising velocity. Hand it off to the in-seat CTO with a 90-day playbook.

For

  • PE-backed software companies post-close
  • Portfolio CTOs who want a peer not a consultant
  • Operating Partners running a value-creation thesis on engineering

Deliverables

  • → Execution intelligence layer installed across code, strategy, and finance
  • → Agent-team operating model designed and rolled out
  • → Engineering ROI baseline, then a 90-day delta the board can see
  • → Handoff playbook for the in-seat CTO
  • → Architecture decisions documented as system invariants

What this is not

  • × A fractional CTO subscription that never ends
  • × A coaching engagement
  • × A roadmap document with no execution
Inquire about AI-Native Value Creation →

Team enablement

AI Coaching for Engineering Teams

Duration
4 weeks+
Cadence
Embedded with the team. Working sessions plus async review. Extends with team size and scope.

Most teams "adopt AI" by handing engineers a Cursor license. That gets you 1.2x at best and a lot of mediocre code. The actual unlock lives at the boundary between product and engineering, and it lives in the repository, not in Confluence. I install the exact operating discipline I run inside InteliG: every feature gets three files (prd.md for intent, log.md for decisions and timeline, README.md for navigation). Active work lives in a workitem/ folder next to the code, sized to match the work (action-items only for fixes; action-items plus design plus frontend plus backend for new entities and services). One backlog across the whole repo. Code is the source of truth. Architecture diagrams get generated on demand, not stored as stale artifacts. Ship the work item, delete the folder, git remembers. This is the discipline I started pushing on the PE-backed company before I left. It is non-negotiable for AI-native development.

For

  • CTOs whose devs are using Cursor but shipping the same amount
  • Engineering leaders moving from human-only to human-plus-agent teams
  • Product orgs where PRDs live in Confluence and the code says something different
  • PE Operating Partners installing AI uplift across a portfolio

Deliverables

  • → Per-feature scaffolding installed: prd.md (intent), log.md (decisions and timeline), README.md (navigation)
  • → workitem/ folder pattern adopted: action-items.md always, plus design.md / frontend.md / backend.md sized to the work
  • → Single repo-wide backlog.md grouped by feature, replacing Jira for engineering coordination
  • → PMs onboarded to push specs and PRDs the same way engineers push code
  • → Coding agent harnesses installed (Claude, Cursor, Codex) and the team trained on the harness, not the prompt
  • → Vertical-slice and feature-first DDD patterns enforced so AI can reason inside a bounded context
  • → Architecture-as-prompt discipline: overviews generated from the codebase on demand, not maintained as stale docs
  • → Concern-based separation rolled in: minimal cognitive collision, lean by default, zero conditional files at feature level

What this is not

  • × A Cursor tutorial or LLM prompt-engineering workshop
  • × A generic "AI for engineering teams" lunch-and-learn
  • × A pep talk about why AI is important
Inquire about AI Coaching for Engineering Teams →

Pre-sale or rescue

Exit Readiness & System Rescue

Duration
4 weeks+
Cadence
Diagnostic phase, then targeted remediation. Extends with the remediation surface.

Two shapes. Pre-sale: clean the codebase story for the next buyer so diligence does not surface ugly findings. Rescue: a SaaS platform is bending under scale or bad decisions, and the founder needs DDD/CQRS strategy to unblock the next phase without burning it all down.

For

  • PE firms 6 to 18 months from exit
  • Founders watching the architecture break under growth
  • Boards inheriting a legacy system that cannot scale

Deliverables

  • → Architectural diagnosis with prioritized fix list
  • → Pre-diligence remediation plan with timing
  • → Documented system invariants and known risks
  • → Founder or board-ready narrative for the next buyer
  • → Optional: hands-on execution of top-priority fixes

What this is not

  • × A burn-it-down rewrite proposal
  • × A microservices migration kickoff
  • × A platform team capacity plan
Inquire about Exit Readiness & System Rescue →

Bespoke

Custom Engagement

Duration
Scoped to fit
Cadence
Defined together on a discovery call.

Your situation does not fit the three tracks above. That happens. The fix is not to force-fit your problem into a productized box. We talk, scope a fixed deliverable together, and run it under the same operating principles: scoped, finite, single named outcome, no rolling retainer.

For

  • Founders or operators with a specific problem outside the standard tracks
  • PE Operating Partners who need a one-off second opinion on a portfolio question
  • Boards or CEOs who need an architecture-grade voice on a non-standard decision

Deliverables

  • → Scope and timeline locked on a 30-minute discovery call
  • → Single fixed deliverable, agreed in writing before kickoff
  • → Same operating principles as the standard tracks
  • → Same finite end-point. If a second engagement is needed, it gets its own scope

What this is not

  • × A fractional-CTO retainer
  • × An open-ended advisor seat
  • × A scope that drifts after kickoff
Inquire about Custom Engagement →

Not sure which fits?

Twenty minute intro call. Tell me the situation. I will tell you which track applies, or that none of them do. Both answers are useful.

Book the intro call →