Technical leadership for regulated and complex environments

Make AI-assisted software delivery easier to verify and own.

Rule26 helps engineering leaders in regulated and complex environments design AI-enabled engineering processes, clarify where human decisions belong, and measure what reaches production.

Discuss Your Project See the Six-Week Pilot

One coding-agent change, start to finish

  1. 1 · Request and specification

    Start with a change someone can check.

    The request says what should change, how the change will be checked, and which client owner decides whether it is ready.

  2. 2 · Implementation

    Let the coding agent work inside clear boundaries.

    The team agrees what a coding agent may change on its own and what needs a person first, so the boundary is set before the change is written.

  3. 3 · Checks

    Run the checks this change needs.

    Agreed tests and checks run on every agent-assisted change, and their results are kept as evidence for the people who decide.

  4. 4 · Client-owner review

    A named client owner reviews and approves.

    The change and its evidence are set out so they are easy to review. The approval decision stays with the client’s named owner.

  5. 5 · Release

    Release is a decision, not a side effect.

    The client’s named owner approves the release and accepts any residual risk. Rule26 helps make that decision clear; it does not make it.

  6. 6 · Production follow-up

    Follow the change into production.

    After release, the team looks at what the change actually did, so the next request starts from evidence rather than assumption.

    See the Six-Week Pilot

Illustrative workflow, not client data

30+ years in software engineeringLed engineering in HIPAA-regulated healthcare (2020⁠–⁠2024)CIPP/USAIGPFounder of GhostCite

Bring in Rule26 when AI changes how your software gets built.

For engineering leaders in regulated and complex environments, where changes must be specified, reviewed, released and owned in ways that hold up later.

  1. Coding agents are in use, but the workflow has not caught up

    Engineers are using coding agents and AI assistants, but many teams’ specification, review, testing, and release practices have not yet adapted to agent-assisted changes.

  2. Human decisions need to stay clear

    When an agent produces a change, the team needs to know who specified it, who reviewed it, who approved its release, and which named client owner accepted any residual risk.

  3. Leaders need to see what reaches production

    Usage and output counts alone don’t show what reached production, whether customers used it, what was reworked, or what failed. Leaders need to connect shipped changes to customer use and production outcomes.

  4. An AI feature is heading toward production

    A product that includes AI needs sound architecture, evaluation, testing, and production readiness. In regulated or high-stakes settings, reviewers may also need evidence they can examine.

Regulated-system experience

Engineering leadership shaped in a real healthcare environment.

From 2020 to 2024, Salma Saad led a ten-person engineering organization at the American College of Surgeons. She improved development tools, delivery processes, operational efficiency and security while guiding complex work involving enterprise architecture, interoperability and cross-functional stakeholders.

Rule26 brings that operating perspective to AI-assisted engineering and to AI built into products. Privacy, security, reliability and accountability are treated as delivery requirements, not documentation added after the work ships.

  • Regulated enterprise and architecture

    “Salma and her team worked with my team to complete several complex projects. She is mindful of important security, interoperability, and enterprise architecture considerations.”

    Jack King, MBA

    Chief Information Officer, American College of Surgeons

    View recommendation on LinkedIn ↗

  • Sustained change leadership

    “She not only recommended changes but guided us throughout the transition.”

    Jeff Gravely

    Engineer who reported to Salma for four and a half years at the American College of Surgeons

  • Founder and technical advisory

    “She assisted me in the recruitment of my initial tech team and provided the needed time estimates, tech stack selection, and laid out the initial AWS architecture.”

    Tal Moise

    Startup founder and former client

  • Candid technical judgment

    “Her analysis skills are a layer or two deeper than most… Salma will tell me what I need to hear, whether I want to hear it or not.”

    Brian Barthelt

    Former manager; Chief Technology and Innovation Officer

The American College of Surgeons is a former employer, not a Rule26 client. Each recommendation is attributed to its author. Experience and credentials.

Two kinds of AI work, with different questions.

AI your teams use to build software and AI built into the products you ship raise different engineering questions. Rule26 keeps them distinct, so each gets the checks, review and evidence it actually needs.

AI used to build software

  • Coding agents and AI-assisted engineering workflows
  • Practical boundaries and checks from specification to release
  • Client-owner review, release approval and residual-risk acceptance
  • Measuring what reaches production

AI built into products

  • Architecture, integrations and data boundaries
  • Evaluation and testing of AI behavior
  • Production readiness and operations
  • Evidence for internal and external reviewers

CIPP/US and AIGP knowledge informs the work. Rule26 does not replace legal counsel, clinical specialists, security assessors or formal compliance professionals.

Flagship engagement

Six-Week Agentic Engineering Workflow Pilot.

Rule26 works with one team on one live workflow, from request and specification through implementation, checks, client-owner review, release, and production follow-up.

  1. Request and specification
  2. Implementation
  3. Checks
  4. Client-owner review
  5. Release
  6. Production follow‑up

  • Map the current process

    How work actually moves through the workflow today, where agents are involved, and where decisions and checks happen.

  • Design practical boundaries and checks

    What agents may do, what must be checked, what the client’s named owner reviews and approves, and what is followed up after release.

  • Start using the improved workflow

    Help the team put the improved workflow into use on real work during the pilot, and record what changes.

Early findings are pilot evidence from one team and one workflow over six weeks. They are not proven ROI and are not a forecast for the wider organization. Throughout the pilot, your named owners retain approval, release, and residual-risk acceptance decisions. Rule26 advises and supports the work; it does not make those decisions.

Discuss a Pilot

Rule26 also supports AI built into products, including architecture, evaluation and testing, and production readiness. See Services.

What changes when agents help write the code.

  • Review becomes the constraint

    Agents can produce changes faster than existing review and testing practices were designed to absorb.

  • Ownership can blur

    It becomes harder to say who specified a change, who checked it, and who accepted the risk of releasing it.

  • Activity is not outcome

    More generated code does not show whether more working software reached production.

The principles are reflected in GhostCite.

GhostCite is a functioning legal citation and quotation verification system. It separates probabilistic extraction from deterministic checks against public court records, records the supporting evidence, and states its limitations explicitly.

  1. Citation submitted
  2. Court record located
  3. Citation or quotation assessed
  4. Result and evidence recorded

Rule-based checks against CourtListener public data. A generative model does not decide the result. GhostCite does not determine whether authority is still good law, and does not replace KeyCite, Shepard’s, primary-source review or professional judgment.

Try GhostCite

Not ready for the pilot?

Accountability and Evidence Map

A lower-commitment first step for teams not yet ready for the pilot. Rule26 helps you document the responsibilities, decision points, checks, and evidence in one engineering workflow.

  • The decisions made in one engineering workflow
  • The evidence each decision needs
  • A named client owner for each decision

Your named owners retain approval, release, and residual-risk acceptance decisions. The map records who decides and what evidence they need. It is not assurance, and Rule26 does not independently assure a workflow it helped design.

Ask About the Map

Larger engagements begin with a defined discovery or review, so scope, responsibilities and expected outcomes are based on evidence.

Have one defined question instead? The Initial Technical Review is a limited $500 entry offer: up to 60 minutes on one defined technical question or proposal, then three prioritized risk and evidence observations and a concise executive follow-up document. It is an initial perspective, not a complete assessment. Discuss the $500 Initial Technical Review. This link schedules a conversation through HubSpot. It does not collect payment or deliver the review itself.

Tell Rule26 about the workflow you want to improve.

If AI is already changing how your team builds and ships software, or an AI feature is heading toward production, that is the right moment.

Discuss Your Project

Find detailed answers on the FAQ page.