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Navigating Rising Ad Costs: An Honest Review of Google Ad Guy's Hybrid Search Model

Running digital ad campaigns in Australia has become increasingly tough for business owners. Google Search remains the most effective place to find high-intent customers. When someone needs an urgent electrician, a commercial lawyer, or a local service provider, Google is still their first port of call. However, rising cost-per-click (CPC) rates, automated algorithm updates, and widespread agency burnout have made running profitable ad campaigns trickier than ever.

Data-Driven Decisions Accelerate IT Results

Modern IT teams, having moved beyond the traditional reliance on hunches and personal experience that once shaped their day-to-day choices, no longer operate on intuition, since every meaningful decision now rests upon measurable, verifiable evidence gathered from their systems and workflows. Every deployment, capacity change, and incident response now depends on measurable evidence, not guesswork. Companies that base their operations on concrete numbers ship faster, recover quicker, and allocate budgets with far greater accuracy.

What Are Stealth Models?

The recent mystery around Ox Alpha last week and the week before was a fun slice of what makes social media fun. The hunt for the model provider and how people did that discovery should be studied. But, this post is more about stealth models in general. You might be wondering what the phrase “stealth model” even means and if you already know, you might still be curious about why companies release stealth models.

AI gross margin: how AI spend hits SaaS profitability

AI gross margin is what remains of SaaS profitability after inference, model routing, and AI infrastructure land in cost of revenue. The numbers have moved. AI products averaged 45% gross margin in 2025 and are projected near 53% in 2026, against the 70% to 85% that SaaS built its valuations on. The compression is real, measurable, and manageable for companies that can see their cost to serve.

Why Most Enterprise AI Agent Programs Overspend, and What Actually Fixes It

Enterprise AI agent programs overspend because leaders optimize token costs, which represent just 20-25% of variable run costs. Human oversight accounts for 70-75%. The real fix is reducing exception rates and embedding governance directly into agent execution from the start.

Your next internal developer platform is a library of agent skills

What happens when AI agents become direct users of your infrastructure? Michael Kutsch, Staff SRE and Team Lead for Cloud Foundations at PostHog, argues that the next internal developer platform may be a library of agent skills. Instead of forcing every task through a portal, his team is giving agents structured context, reusable workflows, and deterministic scripts they can call when reliability and governance matter.

Fin's CTO on Building Great Engineering Organizations in the AI Era

A few months ago, Darragh Curran, CTO at Fin (formerly Intercom) set a public goal to double engineering productivity and nearly tripled it instead. They did so by pulling a few levers: AI writing code at scale, building an AI-driven PR review system, leveraging observability as a trust mechanism, and with leadership becoming more hands-on through the transition.