Prototyping
A working Salesforce prototype gives business users and developers a shared reference, then turns that understanding into specifications.
Salesforce engineering · Business judgment · AI-era delivery
More code isn't progress.
Better software is.
AI makes software faster to create. I bring the Salesforce engineering, business judgment, and controls that make it worth creating.
Jim Coningsby / Independent Salesforce consultant
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.
See the transformation outcome breakdown
30%
Met or exceeded target value.
Sustainable change.
44%
Created some value, missed targets.
Limited long-term change.
26%
Created limited value.
Less than half of target value; no sustainable change.
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 problem isn't new
The tools change.
The need to verify remains.
AI can speed up the wrong work as easily as the right work. Unclear requirements, fragile architecture, and unchecked changes still cost you.
Why Salesforce needs engineering discipline
Salesforce makes it easy to build without calling it software development. A flow, a configuration change, and a line of Apex can all change how the business operates. They deserve the same engineering discipline.
AI lowers the bar for creating those changes and raises the speed at which they arrive. It can also misunderstand the requirement or produce convincing code that is wrong. Without controls, "vibe coding" can scale technical debt faster than a team can understand it. The risk is not just a bad feature. It is losing the ability to safely change the system your business depends on.
90%
AI is already at work.
30%
Little or no trust in its code.
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 ↗
Neither denial nor blind faith
Take AI seriously.
Keep it accountable.
Dismissing AI as a fad misses the opportunity. Blind faith misses the risk. I work with people who see its power and know it cannot be unleashed unsupervised.
The upside, the risk, and my response
THE UPSIDEMore people can contribute.Business expertise can become working software. Ideas can be explored faster.
THE RISKMore changes can go wrong.Misread requirements. Unchecked code. Technical debt at machine speed.
MY RESPONSEA system built for both.Engineering, quality control, and governance designed together. Speed with accountability.
The aim: software you can keep changing, trusting, and growing.
DORA's 2025 research found AI adoption associated with better delivery throughput and greater delivery instability. The benefit depends on the system around the tools. These are observational findings, not a guaranteed causal effect or a forecast for your team. DORA 2025 source ↗
Controls do not have to mean bureaucracy. DORA's research favors peer review and automated checks during development over heavyweight external approval boards; it found no evidence that the latter reduced change failure rates. Change-approval research ↗
The customer's side of the table
Faster for the firm.
Better for you?
Your supplier's speed is not automatically your value. You need independent expertise to judge the people, the proposal, and the work. I put that expertise on your side.
What the information gap costs you
AI makes that gap more important. A firm's ability to produce code faster does not automatically mean a lower bill or a better result for the client. The client still lives with the system, the maintenance burden, and the risk.
I level that playing field. I help make the requirement clear, connect it to the business objective, and give you an independent way to judge the people, the proposal, and the work.
Independent ways to work together
Different ways I bring that judgment and machinery to the work.
The development ecosystem
Quality control, change management, governance, and CI/CD designed to work as one system.
Owner's rep
Independent expertise on your side of the table, so you can judge the people, the proposal, and the work.
Technical depth.
Connected to the business.
I connect engineering decisions to business objectives, and make the tradeoffs clear.
Explore the detail
Keep reading.
These links open a separate page. The blurbs above expand here.