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Lead Quality

By Greg Nowak, 19 April, 2026

Form Spam Is a Lead-Quality Problem: How to Harden Your Intake Flow

Fake submissions waste sales time and corrupt CRM data. Harden forms, handlers, rate limits, and lead routing without creating friction for real buyers.

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AI crawler policy now has verbs: separate search, RAG, and training

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AI crawler rules now need separate decisions for search, RAG, and training, backed by practical testing across robots.txt, CDNs, WAFs, and CMS controls.

WordPress Supports Old PHP; Your Production Server Shouldn’t

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WordPress still runs on legacy PHP, but compatibility is not a security policy. Build and test your upgrade path before PHP 8.2 support ends.

The AI-built tool your team relies on needs an owner

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AI-built internal tools can become business-critical before anyone owns them. Here is how to secure, review, monitor, and retire them without blocking useful work.

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Copilot Has Repo-Level Metrics Now. What Should Teams Measure?

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GitHub’s repo-level Copilot metrics show where AI is active, but not whether it adds value. This scorecard connects usage with delivery, quality, and cost.

Not Every AI Job Needs an Instant Answer: Batch the Backlog

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Move delay-tolerant AI work into dependable batch queues to cut processing costs without compromising quality, data controls, or urgent workflows.

A stray Set-Cookie can waste your CDN: audit the cache at the edge

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Cloudflare Cache Response Rules can recover wasted CDN capacity, but first you need a route-level audit of public, personal and authenticated responses.

Shorter TLS certificates expose every renewal you never automated

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Shorter TLS lifetimes leave less room for manual handoffs and faulty deploy hooks. Build a renewal path that protects service availability.

One Timeout, Two Orders: Make AI Actions Safe to Retry

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A timed-out AI action may already have succeeded. Stable keys, durable ledgers, queues and stored results prevent a routine retry from duplicating real work.

Your AI Visibility Dashboard Needs a Methodology, Not More Charts

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A practical framework for measuring AI-search visibility with fixed prompts, repeated tests, separate metrics, retained evidence, and honest reporting.