A year in AI doesn't feel like a normal year, it feels like about five. The AI landscape has shifted faster in the last twelve months than most businesses could track, let alone act on. For Early Adoptr's first anniversary, we're taking the opportunity to map what actually changed: the model landscape, the rise of MCP, what happened to agents, and what's worth paying attention to in the next twelve months.
We close out with a look ahead at what's actually worth paying attention to: outcome-based pricing, orchestrated multi-agent systems reaching smaller businesses, and what we're calling agent debt, the accumulating consequences of workflows that were built in a hurry and haven't been stress-tested yet.
Thanks for being with us for the last year, and here's to the next 12 months!
All previous episodes of Early Adoptr can be found here or via your podcast player of choice: https://shows.acast.com/early-adoptr
Timestamps:
00:00 What We've Been Up to This Week
04:14 One Year of Early Adoptr: What We Got Right (and Wrong)
06:27 The Model Landscape: Why ChatGPT Lost the Top Spot
11:01 AI Pricing Is Changing — and Your Bill Is Going Up
16:20 Context Windows: From Headache to Non-Issue
20:03 When Smaller Is Better: The Case for Specialist AI Tools
20:35 Use Cases for Small Language Models
22:53 Agents: From Conference Buzzword to Actually Useful
29:02 What MCP Did for the Agent Ecosystem
31:29 Agentic Commerce and the Two-Tier Internet
37:55 How Brands Are Using AI for Discovery Without Losing the Customer
39:05 AI Security: How the Risk Picture Changed When Agents Got Real Access
44:17 Prompt Injection, Data Leaks, and What to Actually Watch For
48:26 From Subscriptions to Outcome-Based Pricing
50:22 AI Regulation, Memory, and the GDPR Question Nobody's Asking Yet
52:20 The Agent Debt Problem
56:12 What's Worth Watching: AI Predictions for the Next 12 Months
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