Technical Expertise · Business Fluency

Velocity of change isn't progress.Change that delivers value is.

Jim Coningsby Salesforce Architect

A thorough evaluation first

Know where you stand.

Projects go wrong early, when the preparation isn't done and the right tools and resources aren't in place before work begins. I begin with a discovery process in order to produce a readiness assessment report with recommendations on how to set up the project to succeed. It also informs both of the solutions below.

The problemDevelopment without controls

The barrier isn't how fast your admins and developers work - it's the rigor of your process, without which attempts at speed result in more wasted money rather than value delivered. AI magnifies every gap, introducing potentially damaging changes into your production org... rapidly.

The solutionRobust development ecosystem

I set up your system's core infrastructure and architecture necessary for well written and consistent code, add skills files for your AI agents, and configure CI/CD pipelines. Together they give you quality control, change management, and governance, so only quality changes that deliver value reach production, whether they come from your team, contractors, or AI.

The problemYou can't evaluate what you don't know

Potential contractors know more about development work than you do. That asymmetry makes it hard to know who to select, whether their work is quality, and whether you're getting your money's worth. If they use AI (they will), it becomes murkier what you're getting, and they keep most of the benefit while you carry the risk.

The solutionContractor transparency

I craft an RFP and scoring rubric to help you select the right contractor for your needs. The development ecosystem provides guardrails to promote adherence to expected standards, including any use of AI, which mitigates the risk. I incorporate tools into your system that allow you to evaluate the quality of their work, and I periodically review it and report back to you.

These solutions keep the work high quality and aligned with business objectives, so each change delivers value.

Why me

I have over 18 years of Salesforce admin and development experience and have led many successful projects as well as been brought in to try to salvage ones that failed. I know what separates them.

Already convinced? Let's talk.

Not yet? Keep reading, or skip ahead to learn more about how I solve it.

The long version

Software development is risky.

A lot of the money spent on software development is wasted.

As detailed below, software development has many ways to fail, and each one is an opportunity to waste money. Some are obvious. Many aren't. Weak process (especially in Salesforce work), poorly defined objectives, and a lack of transparency in choosing and working with a contractor are all major sources of waste. AI is tempting as an easy fix, but it can't repair any of these. It only amplifies your practices, good and bad. And while contractors stand to gain from AI efficiencies, most of that benefit is unlikely to reach you, while you carry all of the risk of AI slop reaching your production environment.

Changes require a controlled process.

A lot of software waste comes from missing process.

Software projects lose money when there's no controlled process to catch problems early or enforce standards. Breaking changes, technical debt, inadequate documentation and poorly designed architecture that requires disruptive changes to correct are all expensive manifestations of that gap. The problem is compounded in Salesforce work where most teams don't follow software development best practices at all.

This same discipline is required for Salesforce.

Salesforce work is software development.

Whether your team writes code or builds with clicks, they're changing how your business runs. Calling it configuration doesn't change what can go wrong, or make testing, version control, and change management any less necessary. Most Salesforce teams don't treat it that way, and that gap results in breaking changes in production and costly back and forth rework.

The promise of low-code and no-code made Salesforce feel like an exception. It isn't. Every change should be traceable, tested, and validated before it reaches production, whether it comes from an admin, a developer, or AI.

Features nobody needed provide no value.

Without well defined objectives, even quality work results in waste.

Even well-built work is waste if it doesn't serve what the business is trying to achieve. When the target is unclear or no one is aiming at it, projects tend to conform to arbitrary feature requests where the purpose has drifted significantly rather than agreed upon business objectives. The result is the wrong thing being built which shows up as poor user adoption and abandoned work.

It's hard to know whether you're hiring a competent contractor.

Salesforce certifications and Trailhead badges have very little to do with competency. If you don't understand code, you can't evaluate code samples, and configuration samples can be just as hard to read. Many contractors and firms have mastered a strong pitch, and the information is asymmetrical: they know far more about their work than you can verify. Even client referrals may not be reliable, because those clients may never have faced the tech debt the contractor left behind. Most contractors aren't following best practices, and almost all clients don't know what to ask for.

It's hard to know whether you're getting the value you're paying for.

If you don't write code or do configuration, you can't really tell what you're looking at or whether it's any good. Contractors are incentivized to hit the thinnest possible definition of done, so things like logging, test automation and mocking get skipped, along with readability, testability, maintainability and scalability. The work is rarely built so a future developer can pick up where the last one left off, and documentation is weak or missing. Clients don't know to ask for these things, contractors take advantage of that, and many don't know they should be doing them at all. Maintenance, not the purchase or development cost, is what drives the real cost.

The same gaps, at greater speed

AI doesn't fix a weak process.
It magnifies your practices, both good and bad.

If your team already struggles to turn changes into business value, adding AI doesn't remove the reasons why. It can produce code faster, but it can also misread requirements, invent answers, and introduce changes that look right until they reach production.

Keep the same bad practices and you give those problems more room to grow. Without testing, review, and controlled releases, faster development can mean more failures, more technical debt, and less value from the work.

Widespread use. Uneven trust.

90%

used AI at work

30%

reported little/no trust in AI-generated code

Source & context

DORA 2025: 90% used AI at work; 30% reported little/no trust in AI-generated code. Survey of nearly 5,000 technology professionals. Different questions, not complementary groups; self-reported, not measured code quality. Source ↗

The customer's side of the table

Any AI-enabled contractor keeps most of the benefit. You carry the risk.

Your firm or contractors can use AI to do the work faster without passing those savings on to you. You still pay the bill, and you still live with the software, the maintenance burden, and anything that breaks.

It also gets harder to see who is actually doing the work and to what standard. Was it built by the expert you hired, someone else on their team, or AI? Who checked it? You need a way to judge the work, not just trust the people selling it.

The problems compound.

Software development is hard and risky even when it's done well.

Without the basics in place, the costs show up everywhere:

abandoned work, breaking changes, hours spent testing or waiting to deploy, and people overwriting each other's changes.

It's hard to see the total because the waste is spread across the work.

Over time, that becomes technical debt.

Tests take hours, nobody is sure what a change will break, and people become afraid to change anything.

The system gets harder to maintain until starting over begins to look easier than fixing it.

AI doesn't remove those problems.

It can produce more changes faster than your team can check them.

And faster work doesn't automatically mean a lower bill.

You still have to run the system, maintain it, and deal with what breaks.

How I help

Readiness assessment

A report that evaluates your readiness to take on your project.

Before anything gets built, I assess how ready your organization is to deliver successful software, and where the risks are.

Where you stand on each fundamental.

Aligned stakeholders

Clear objectives, a champion on staff, an appropriate budget, and defined roles.

Enforceable quality

Practices, architecture, and automated testing that make standards stick.

Visible progress

A firm chosen on proven experience, work judged against your standards, and progress you can see before the budget is gone.

You get a Readiness Report: where you stand and the risk each gap carries. It confirms everyone is aligned on the business objectives and shapes everything that follows.

Development ecosystem

An ecosystem designed to yield successful software development

The goal is valuable software. The process connects what your business needs to what reaches production, then uses what happens there to improve the next change.

The machinery behind controlled delivery.

The machinery and plumbing every org needs.

Scaffolding specific to your business.

Expectations for how code is written.

Merging code that works. Finding problems early.

Immutable artifacts. Controlled deployment.

Give AI agents a seat at the table.

The pit of success

Good work is the natural outcome rather than relying on discipline or compliance alone

Clear intent · Consistent builds · Checked changes · Repeatable releases

I fit this machinery to your org and move your team into it in stages, so admins, developers, contractors, and AI work through the same controlled path.

Contractor transparency

Help finding the right resources and evaluating their work

The gap in information is narrowed.

Salesforce customers suffer from asymmetrical information in terms of the firms, contractors and even employees they seek to hire. They don't really have any good way of determining whether they've chosen the right people and whether those people are doing a good job. I'm here to level that playing field.

I'm creating an environment where the gap in information is narrowed and they can achieve productive work together on what the client truly needs.

RFP creation

Rubric for RFP

Technical scoring

For RFP submissions

Contractor/firm onboarding

Guiding them through adoption of the systems and standards and helping them get their environments set up correctly.

Observability tools

On the progress and quality of the work

Periodic review

Regular assessments of the work, reported back to you.

Services →

The benefits

Help your project succeed by shaping how the work gets done.

Less rework. Reducing waste and rework through reducing opportunities for miscommunication or misunderstanding of the requirements.

Aligned incentives. Align the incentives and motivations of the contractor with the overall long-term benefit to the client.

AI benefits without all the risk. Ensure the client gets to benefit from the contractor's decision to use AI without absorbing all the risk.

Right-size the engagement.

Create opportunities for the client to leverage the ecosystem and these tools to take on more of the scope themselves by reducing the barriers to entry without sacrificing engineering fundamentals or non-technical people having to learn technical steps.

And further helping the client to right-size their engagement with contractors and select the right ones for the right jobs.