AI & Web Development
The AI Tools I Actually Use in My Web Dev Business
Jay Goodman · Absolute 0 Internet Studios · Updated July 10, 2026
After decades of building websites and business systems, I am skeptical of any tool that promises magic. The AI tools that stay in my workflow are the boring useful ones: they help me think faster, check work, draft first passes, and reduce repetitive production time.
The rule: AI assists, judgment decides
The biggest mistake businesses make with AI is treating it like a replacement for strategy, taste, or technical responsibility. I use AI like a sharp assistant: fast at first drafts, pattern recognition, summaries, code review, and repetitive transformations.
The final decision still has to come from someone who understands the business, the customer, the risk, and the system that will carry the work after launch.
Where AI helps in real client work
For website projects, AI is useful for outlining service pages, turning rough notes into clearer copy, comparing messaging against competitors, writing schema drafts, and checking whether a page answers the questions a buyer actually has.
For custom software, it helps map workflows, draft database schemas, generate test cases, review edge cases, and produce documentation that would otherwise get skipped. None of that replaces engineering discipline, but it makes the discipline easier to apply consistently.
The tools that earn their keep
Large language models are the center of the workflow, but the value is not the model name. The value comes from using them with context: real project notes, code, Search Console data, analytics, customer language, and clear constraints.
I also use AI inside development environments for code suggestions and refactoring, image tools for controlled marketing visuals, transcription/summarization tools for meetings and raw notes, and automation agents for repeatable QA or reporting tasks. The common thread is that each tool has a job and a review point.
What I avoid
I avoid AI workflows that publish directly without review, make claims without source material, or hide how an answer was produced. I also avoid adding AI to a business process before the process is understood. If the workflow is unclear, AI usually makes the mess faster instead of better.
For small businesses, the safest starting point is usually not a chatbot. It is a repeatable internal workflow: summarizing intake, drafting reports, classifying requests, generating first-pass content, or turning scattered notes into structured next actions.
A practical starting point
Pick one repetitive task that already has a human review step. Give AI the context, examples, rules, and output format. Measure whether it saves time without increasing mistakes. If it works, tighten the guardrails and build it into the workflow.
That is the kind of AI integration I recommend: specific, useful, reviewable, and tied to a business outcome.
Need help applying this to your business?
If your website, workflow, or AI idea needs a practical next step, start with a focused audit. The goal is to find what is worth fixing first, not to sell you a bloated rebuild.