This is the second half of a two-part conversation with Matt Schwartz, a longtime WordPress agency owner and creator of CheckView, about practical ways agencies can adopt AI — and the risks to watch for.
Why think about AI now
AI isn’t just a novelty; it can automate repetitive work, surface missed insights, and let agencies focus on higher-value strategy. Matt’s message is pragmatic: experiment, but be deliberate. Document your goals and decide where humans must stay in the loop.
Give AI access to your agency “brain”
One easy win is connecting your AI chat assistant to existing knowledge sources — project management tools, wikis, SOPs, CRM notes. When the AI can reference your living documentation it reduces hallucinations and gives staff consistent answers. Practical result: faster onboarding, fewer forgotten details, and better internal support without heavy engineering effort.
Model Context Protocols (MCPs) and guardrails
MCPs (Model Context Protocols) are emerging as a cleaner way for agents to access multiple systems. Instead of every employee creating separate connectors or exposing API keys, an agency-level MCP acts like a gatekeeper: it aggregates systems, enforces permissions, and presents a consistent interface to the AI. This reduces friction and risk, but still requires strict guardrails. Limit destructive actions (deletes, production changes), add logging, and consider third-party MCP providers carefully — you’re handing them sensitive credentials.
Vibe-coded internal tools vs. public systems
Many agencies are building quick, internal “vibe-coded” tools — dashboards, profit reports, or one-off automations — which are lower risk because they stay behind the team firewall. These can yield big operational wins: consolidated reporting across QuickBooks, time tracking, and e-commerce data; faster insights on profitability; and automation of repeatable tasks.
But caution is warranted for public-facing systems. Replacing mature SaaS or management dashboards with quickly generated, agency-built apps can be risky unless you have rigorous code review, error handling, and ongoing maintenance. A cheap one-off can become a liability if it must run reliably long-term.
QA, checklists, and Claude Skills
AI shines at repeatable checks. Use it to build and run launch checklists, automated QA for binary checks (e.g., is noindex enabled?), and to free humans for nuance and review. Claude Skills (or similar workflow-based AI features) let you teach an agent a process and define which steps need human verification. The sweet spot: automate the mundane, but require human review for high-risk items.
WordPress plugin ecosystem impact
Smaller, narrowly focused plugins are already seeing sales pressure because agencies can spin up tailored solutions quickly with AI. That dynamic may shrink the pool of small plugin authors, which worries both hosts of grassroots contributors and the broader open-source community. The likely outcome: an increased bar for plugins — more robust, differentiated features will be needed to justify monetization — and potential consolidation among larger plugin vendors.
Experimenting beyond WordPress
AI lowers the cost of learning new stacks. Agencies can more easily prototype on modern frameworks (static sites, Astro, Cloudflare setups) for certain projects. That has two effects: more fit-for-purpose choices for simple brochure sites, and a push to evaluate when WordPress remains the best tool. Open APIs and documentation give WordPress an advantage, but agencies may diversify their offerings where it makes sense.
Risks and cautions
Key risks Matt highlights:
– Data security and exposure: chat tools may claim broad rights over inputs and differ in how they treat data. Treat anything you send carefully, particularly client secrets and PII.
– Over-dependence on vendors: built processes tied to specific AI plans can become expensive if providers change pricing or features.
– Error handling and testing: AI-generated tools can miss edge cases. Without proper logging, validation, and manual review, you can create fragile systems.
– Community erosion: if tooling and quick AI fixes supplant plugin development and community engagement, the open-source ecosystem could weaken over time.
Agencies should anticipate price increases, prepare to pivot if vendor terms change, and design systems so they can function without uninterrupted AI access.
Likely outcomes for agencies
Matt expects several shifts:
– Hiring changes: routine execution work may require fewer junior staff as automation handles more tasks, while demand for strategy and oversight roles increases. However, if AI costs rise, that could swing back toward more human execution.
– Productised services: AI makes it easier to package niche vertical offerings (e.g., plumber-specific site processes) into repeatable products.
– New tooling emphasis: more monitoring, QA, and observability tools will be needed to supervise AI-driven automations and sites.
Practical takeaways
– Start small: connect AI to existing docs and PM systems for immediate value.
– Build an AI vision document: define tasks AI handles automatically versus where humans must validate.
– Consider an MCP if you’re technical and need secure multi-system access, but enforce strong guardrails.
– Use AI for internal reporting and checklist automation, but be cautious building public-facing systems without strict review.
– Monitor vendor reliance and plan for pricing changes.
– Be mindful of community health: support open-source participation where possible.
Where to find Matt
Matt is active in agency communities like the Admin Bar, on LinkedIn, and via his sites (CheckView and Inspry). He encourages agencies to experiment thoughtfully, document choices, and prioritize security and error handling.
If you run a WordPress agency or freelance business, the practical advice here can help you identify low-risk AI wins and plan for the inevitable trade-offs as the landscape evolves. For more detail and links, see the show notes at wptavern.com/podcast.