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If your team has tried to scale LinkedIn prospecting recently, you already know the pain: getting high-quality lead data is expensive, slow, and full of.
If you follow AI agents, you have probably seen two ideas collide.
The fastest way to lose trust in AI is to treat a slick demo like a production system.
If you want to earn real money from AI automation, the hardest truth is also the most useful one: generic "I will automate your business with AI" offers are.
If you have ever defended a single-vendor, single-model setup for AI automations, you probably had good reasons.
The uncomfortable truth about democratized automation is that ease of building does not ease operations.
If you have read the companion piece on [why agents crush micro-tasks but choke on vague mandates](/blog/why-ai-agents-stall-big-tasks-crush-micro-tasks-2026.
If you have typed "will AI take our jobs" into a search box or asked an assistant late at night, you are in good company. The question is not silly.
There is a story you hear after almost every AI pilot: leadership funds an agent, the demo looks magical, and six weeks later nobody trusts the output.
When a team automates with artificial intelligence, the tidy version of the plan sounds obvious: pick a strong model, wire it into the workflow, and move on.
On February 25, 2026, Perplexity launched Computer, a new multiagent orchestration system that the company describes as "a general-purpose digital worker".
The way we value software is changing. For over a decade, success in tech meant building a product, exposing an API, and scaling through seats and features.
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