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. Without clear objectives, projects get driven by perceived needs rather than real ones, pushed by whoever is loudest or most senior, whether that's a user, a manager, an executive or the dev team itself. Pet projects get built while real needs that no one has recognized go unmet. Priorities keep shifting, work gets redone, and the result is a pile of features with no clear tie to a business objective, many of which end up unused.

Competency requires technical review.

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

Most contractors aren't following best practices, and almost all clients don't know what to ask for. 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 assess. Many contractors have mastered a strong pitch but their body of work would not hold up against a knowledgeable technical review. Even client referrals may not be reliable, because those clients may not yet have paid the price for the tech debt the contractor left behind.

Quality work goes beyond simply appearing to function.

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

If you don't have the technical expertise, you can't tell whether what you're paying for is any good. Contractors are incentivized to hit the thinnest possible definition of done: software that appears to function at deployment, which is all an untrained eye can judge. Complete and correct software is measured by four additional qualities: it is readable, testable, maintainable and scalable. Logging, test automation, mocking, SOLID code principles, documentation and other unglamorous/unseen work are what create those qualities, and clients don't know to ask for them. In fact, many contractors don't know they should be doing it either. These qualities have real operational and budgetary consequences. Done well, they pay off for years. Done poorly, they cause expensive harm the client may not see until long after the work is paid for.

The same gaps, at unmanageable speed.

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

Weak process lets undisciplined developers push poor work, but there is still human intent behind it: they are trying to build something that works, and at the very least they understand their own code well enough to know what it's doing. AI has no such intent. It has no allegiance to any standard and no self-discipline. Without explicit rules, it guesses from patterns in the existing code, then produces changes at a speed no manual review can match, often code the person who prompted it doesn't fully understand. Companies with good practices see real gains from this speed. Companies without them get an echo chamber, where bad code inspires more bad code and the mess is hard to undo. Keeping up requires automated controls, and automation requires good practices memorialized in the source code as agent skills and prompts.

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 ↗

AI work passed to you without any value added.

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

AI lets contractors work faster, but nothing says those savings will reach you or that the work will be quality. AI also lets firms call people developers who wouldn't have qualified before, because they can produce code without learning the syntax or, more importantly, the best practices of design and architecture. Typing out code was never the hard, valuable part of development. The result is that it gets harder to tell who did your work and to what standard. Was it the expert you hired, someone else on their team, or AI? Who checked it?

When AI is tasked only with making something work and the developer is incentivized to call it done without proper review or refactoring, the gap between what you pay for and what you get widens.

The problems compound.

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

It starts with missing process.

Without a controlled process and clear objectives, money goes to features nobody needed, breaking changes and rework.

The waste is spread across the work, so nobody sees the total.

Weak oversight lets it build up.

Clients can't easily judge quality, and contractors are incentivized to call work done once it appears to function.

The unseen work gets skipped, technical debt piles up, and starting over starts to look easier than fixing it.

AI speeds it up and blurs who is accountable.

It magnifies those same gaps faster than manual review can catch them.

And it makes it harder to tell who did the work and to what standard.

Each gap makes the next one worse, and together they make project failure likely.

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.