Technical Expertise · Business Fluency

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

Jim Coningsby Salesforce Architect

The problemDevelopment without Controls

The barrier isn't how fast your admins and developers work - it's the rigor of your process. AI magnifies every gap, introducing breaking changes to your production org. Rapidly.

The solutionRobust ecosystem

I've designed and built the machinery: quality control, change management, governance, and CI/CD working as one system. It creates a pit of success where only quality changes that deliver value reach production, whether they come from your team, contractors, or AI.

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

Your suppliers know more about the work than you do. That asymmetry of information makes it hard to know who to trust, what you're paying for, and whether their work meets the standard.

The solutionVetted Resources, Verified Work

Think of me as your owner's rep - the person on your side of the table who knows this world. I give you the information, competency, and mechanisms to hire the right resources and evaluate their work.

Already convinced? Let's talk.

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

The long version

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.

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

A benchmark, not a prediction

The gap between investment
and outcome is not new.

The investment-to-outcome gap predates AI. Newer AI research shows why faster tools still need a sound delivery system.

Where transformations land.

30%

Met or exceeded target value.

44%

Created some value, missed targets.

26%

Created limited value.

Source & context

Source: BCG, Flipping the Odds of Digital Transformation Success (2020). Based on 70 BCG-supported transformations and a survey of 825 executives. These are broad digital transformation findings, not a Salesforce failure rate, a measure of wasted spend, or a result promised by Jim.

The same gaps, at greater speed

AI doesn't fix a weak process.
It speeds it up.

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

They keep the savings.
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

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.

The judgment on your side of the table

An owner's rep who knows the work.

I give you the information, competency, and mechanisms to judge the resources you hire and the work they deliver.

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.

Contractors alone

Bridging the gap

With your judgment in the room

Hiring resources that may not have the experience or competency to take on their project but may initially appear as if they do.

Technical scoring for RFP submissions

Competently created and delivered work that delivers on the expected requirements.

Work, produced with AI or without, that passes the initial smell test but is fundamentally rotten: bugs, data corruption, technical debt, unmaintainable code.

Observability tools on the progress and quality of the work

Work you're not afraid to change as you scale or onboard/offboard products and services.

The meter running with no real relationship to the value of the work being produced.

Incentives are aligned through the RFP, the observability metrics and the controls that enforce standards. It makes it harder, if not impossible, for them to ship junk, which forces them to design properly so they can ship, and then you're benefiting from that proper code.

Predictable costs where increases are driven by additional identified functionality, not devs spinning wheels.

Inconsistent or missing coding standards and practices as a source of technical debt.

Evidence driven

Contractor/firm onboarding

Code that any resource from any team, now or in the future, can pick up and reason about due to its internal consistency and adherence to best practices and clean design.

AI tooling lets firms write code faster and cheaper, but not necessarily pass all those savings onto the client, while the client is inherently absorbing all of the risk of AI.

Primarily the CI and coding standards ones

Protecting the client from absorbing all the risk of AI.

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.

From business need to work you can evaluate.

Define

Business needs turned into requirements.

Assess

Resources and proposed approaches evaluated against those needs.

Set standards

Clear criteria and ways to verify the work.

Evaluate

Delivered work judged against the requirement and standard.

Decide

Cost, quality, and risk made clear for your next decision.

What the work reveals informs the next decision

Valuable software. Informed decisions on your side.

A working demo isn't the whole test. I help connect the requirements, the people, and the standards so you can evaluate the work and what it will take to maintain. If AI changes how a supplier delivers, you have a basis for asking what changes in the price, quality checks, and responsibility.

Technical depth.
Connected to the business.

I connect engineering decisions to business objectives, and make the tradeoffs clear.

Explore the detail

Keep reading.

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