AI can write your code.
It can't run your project.

  • 30+ years building software and leading development teams.
  • I help your team — the people and the AI — get stuck or at-risk projects delivered.
  • New products: I help your company spec, develop, test and launch the product.
  • I run my own projects with an AI engineering team, and the gates that make its work safe to ship.

Let's talk — 20 minutes

Read my writing

Robert Guida, smiling, in a grey jacket and light-blue open-collar shirt, against a dark blue background.

ROBERT GUIDA

Fractional CTO & Solutions Architect

Focus Areas

For founders, COOs with a software budget, agency and dev-shop principals, and engineering leaders.

Stalled or late projects

  • Diagnosis: the real cause is usually architecture, scope, or decisions no one owns.
  • Outcome: the project delivered.

Architecture capacity for agencies and dev shops

  • Senior architect for work you have won but cannot staff.
  • Under your brand (white-label) or mine.
  • Flexible on contract structure.
  • No client solicitation.

Review process for AI-written code

  • AI governance: setting up and leading how your team uses AI in delivery.

Engagement Options

Which option fits is decided after we discuss the problem.

Fractional CTO Retainer

  • Ongoing senior technical direction.
  • No executive added to payroll.

Architecture & Solution Design

  • System design, data architecture, cloud, build-vs-buy.
  • Tradeoffs and a recommendation. You own the decision.

Delivery & Project Rescue

  • Stalled or over-budget projects.
  • An honest assessment, then a realistic schedule.

Selected Work

Client names are confidential. Records from my own projects are available on request.

My own projects — AI-governed delivery, running daily

  • A governed AI development process, run daily on real projects.
  • Each morning, the day's work is checked against the written plan before it starts.
  • I run a quantitative retrospective every day: Time Variance (estimate versus actual) for every ticket, in work hours and elapsed time, with the root cause of any miss.
  • The retrospective includes a review of my own prompts: what worked, what caused rework, and a better wording.
  • Repeat defects are logged; the third time one shows up, it becomes a ticket to replace the written rule with a mechanical guard.

Web applications for a public-sector client in a regulated environment — 5+ years and ongoing

  • The applications handle sensitive personal data.
  • Designed the API and data layer.
  • Every change I ship passes a sensitive-data scan before it leaves my machine.

Core stack

AWS · SQL · Node.js · GraphQL ·
React · Python · PHP · Rust

How an Engagement Works

How an engagement runs:

  1. You describe the problem.
  2. I review what exists.
  3. You get findings and options ranked.
  4. You own the decision.
  5. I lead your team through the build and delivery.

Delivery safeguards:

Scope: requirements, project plan, build, testing, threat modeling, code review, deployment.

Spec-driven development: written requirements, then a project plan, before any code.

My AI engineering team runs on a written rulebook. Every ticket is estimated before work starts. Nothing merges until it passes these quality gates:

  • Code review
  • Testing
  • Security and compliance check

AI output: treated as a draft until it passes these checks.

Most rules were written after something broke, and each one carries the date and the reason behind it.

Guardrails: automated checks that block a step, or force one.

Multi-agent orchestration: my AI agents work in defined roles and departments, coordinated as one team.

Dynamic model routing: each task is sized, then sent to a model that fits.

Purpose: less rework and less lost context — not fewer developers.

Continuity: plans, decisions and lessons are written down and kept with the project, not in my head.

Persistent memory: the AI reads that record first, when work starts.

Entry engagement

Architecture & Delivery Assessment

$7,500 fixed.
Two weeks.

Purpose: find the real cause before any fix is proposed.

Included:

  • • Up to six interviews with your team
  • • A review of one codebase and how work actually flows through it, including how your team is using AI-written code
  • • One written findings document with a prioritized plan
  • • One 60-minute readout

Work beyond this scope is quoted separately.

Read the full agreement

The findings document is yours to keep, whether or not the engagement continues.

Fit, Limits, Availability

  • Best fit: teams under ~15 engineers.
  • Schedule: two fixed days a week.
  • Terms: month-to-month, 30 days' notice.
  • Working model: remote and async-first, with overlap with US business hours every working day.
  • Response time: same business day.
  • Regulated work: every change I ship passes a sensitive-data scan before it leaves my machine.
Robert Guida standing full length in a navy jacket and grey trousers, hands in pockets, against a dark blue background.

About

  • Robert Guida.
  • Experience: 30+ years building software and leading development teams.
  • Community: volunteer coach to non-technical founders building software with AI. I ask the questions that make them think through requirements, how data is used and shared, and SaaS architecture.
  • Method: agentic engineering, an AI engineering process run daily on real projects.
  • What experience adds: the ability to plan, execute and deploy projects, leading an AI agent team set up like a small software development company.
  • What the process adds: executing the plan and developing the code, gated by checks and balances.
  • Next: a RAG layer over my written plans, decisions and lessons. Keyword search first, then hybrid search.
  • Approach: proven methods over the newest framework.
  • Human-in-the-loop: the final call is mine, on every plan and every release.

Book a Call

  • Free 20-minute call.
  • You describe the problem. I ask questions.
  • Then we discuss what might solve it.
  • You decide whether it is a fit.

Let's talk — 20 minutes