Stop guessing. Based on community patterns and documentation analysis, the difference is clear - Tasks for parallel search, subagents for persistent expertise. Here is the decision framework emerging from real usage.
Forget the marketing. Based on thousands of real user experiences, here is what Claude, ChatGPT, and Gemini actually do well, where they fail spectacularly, and which one you should use for specific tasks.
AI agents wreck environments in loops while burning through thousands in tokens. But the real failure? Feedback systems that collect input then do nothing. Here is what actually works in production.
Consultants get you started with Claude. Operations managers keep it running. With 95% of AI pilots failing after launch, the real work begins after implementation - monitoring usage, optimizing costs, and preventing the drift that kills ROI.
One-time fees, unclear percentages, high minimum deals - here is what nobody tells you about AI vendor partner programs and why building a business on referrals alone requires massive volume.
Most AI consultants fail at Claude Code because they treat it like ChatGPT with a different logo. Specialists understand MCP, context windows, and why your 66,000 tokens disappear before you even start. Here is how to spot the difference between someone who read the docs yesterday and someone who can implement.