Palm Beach Software Design
Palm Beach Software DesignHow We Use AI in Our Development Process
Transparency in How We Work
We use AI tools. We’ll be direct about exactly where, how, and — importantly — where we don’t rely on AI. Because the distinction matters more than most people realize.
Founded 1987 | American-Owned & Operated | Developers Answer Your Calls Directly | On-Time Delivery
AI-accelerated vs. AI-generated
These two things sound similar. They aren't. The difference is human judgment, review, and accountability at every stage of the development process.
- ✓ AI suggests code; a developer reviews, tests, and approves every line
- ✓ Architecture decisions made by humans with full context about your business
- ✓ Security design is explicit and intentional, not assumed
- ✓ Every integration reviewed for edge cases and failure modes
- ✓ Output tested against real requirements, not just "does it run"
- ✓ Documented, accountable, and maintainable by any qualified developer
- ✕ AI output accepted without systematic review or testing
- ✕ Architecture emerges from prompts rather than deliberate design
- ✕ Security considerations left to chance or the AI's training data
- ✕ Integrations written for the happy path only
- ✕ Testing is manual and surface-level if it exists at all
- ✕ Code is often brittle, undocumented, and opaque to outside reviewers
Where AI helps — and where it doesn't
This table shows exactly how AI fits into our development process at each stage. No marketing language — just specifics.
| Development Stage | How AI Helps | Where We Don't Rely on AI | Why It Matters |
|---|---|---|---|
| Discovery & Requirements | Research assistance, summarizing documentation, drafting requirement specs for review | Identifying what the client actually needs vs. what they asked for | Requirement gaps are the #1 source of failed projects. This requires experience and judgment. |
| Architecture Design | Exploring options, generating diagrams, reviewing tradeoffs | Final architecture decisions, database design, security model | Architecture determines a system's ceiling. Wrong decisions here compound forever. |
| Development | Boilerplate generation, autocomplete, test scaffolding, documentation drafting | Business logic, security-sensitive code, integration design | AI accelerates the routine. Humans own the consequential. |
| Security Review | Automated scanning for known vulnerability patterns | Security architecture, threat modeling, remediation decisions | Scanners find known patterns. Novel threats require human analysis. |
| Testing | Generating unit test scaffolding, creating test data, drafting test plans | Defining what constitutes correct behavior; edge case identification | AI can write tests for what it sees. It cannot anticipate what the requirements missed. |
| Documentation | First-draft generation of technical docs, API references, inline comments | Architecture decision records, operational runbooks | Process documentation must reflect actual system behavior — requiring human verification. |
| Deployment & Operations | Infrastructure-as-code scaffolding, monitoring configuration templates | Production deployment decisions, incident response, post-mortems | Production environments affect real users. Accountability cannot be delegated to a model. |
The standards that apply regardless of tooling
Whether a line of code was written by a developer, generated by AI, or some combination — every line we deliver meets the same standard.
Every line is reviewed
AI-suggested code is treated as a draft, not a deliverable. A developer reads, tests, and approves every line before it enters a client system. There is no "AI generated it, so it's probably fine" in our process.
Security is explicit
Security requirements are defined at the start of every engagement — not audited at the end. We apply OWASP standards, conduct threat modeling, and document every security-relevant decision.
Code is maintainable by anyone
AI-generated code is often inscrutable to human maintainers. We refactor for clarity and document everything so your system isn't a black box if PBSD isn't involved in future work.
Accountability is ours
If something we built has a problem, that's our responsibility — not the AI tool's. We stand behind our work the same way we have since 1987, regardless of what tools were involved.
Our founders are still directly involved in software development. For over 39 years, our accountability standard has been simple: the software works, it's secure, and we stand behind it. AI makes us faster. It doesn't change that commitment.
PBSD brings decades of production software experience to every engagement — with AI accelerating the work, not replacing the judgment.