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12 articles on Artificial Intelligence from the TTMCHANGE blog.
AI coding agents are moving beyond autocomplete and code generation. They can understand repositories, plan changes, modify multiple files, run commands, debug failures, and iterate on their own. The bigger shift is not that AI can write code — it is that software development is becoming an increasingly agent-driven workflow.
9 min read
AI agents are moving beyond chat interfaces. They can now use tools, access data, call APIs, and execute multi-step workflows. As agents become part of real software systems, the biggest challenge is no longer simply making them smarter — it is building the infrastructure that makes them reliable, observable, and safe.
8 min read
NVIDIA is reportedly spending $6 billion to license Poolside’s internal “Model Factory,” while offering jobs to 109 employees and investing another $1 billion in the company. The unusual structure reveals something important about where the AI race may be heading: the most valuable asset may not be the model itself, but the infrastructure used to build it.
7 min read
A mysterious AI model called Ox Alpha has appeared on OpenRouter with a 1-million-token context window and multimodal capabilities. But the biggest question is not what it can do—it’s who built it.
4 min read
DeepSeek is moving beyond models with DeepSeek Harness, an open-source agent runtime built around a simple idea: everything is a plugin. Here’s what makes its architecture interesting for developers building the next generation of AI coding agents.
6 min read
A look at the latest LLM rankings for coding, reasoning, and complex problem-solving—and why Claude Opus models are currently dominating the top positions.
Claude Code can be incredibly powerful, but inefficient context management can consume tokens faster than necessary. Here is a practical engineering approach to reducing token usage while keeping Claude effective across real-world development workflows.
Artificial intelligence is not powered by models alone. Behind every advanced AI system is a complex infrastructure of computing, data, storage, and engineering systems that make intelligence possible at scale.
Artificial intelligence is moving beyond answering questions. AI agents represent a new generation of software systems that can reason, plan, use tools, and complete complex tasks with greater autonomy.
The future of artificial intelligence is not only about building larger models. High-quality data, reliable processes, and thoughtful engineering decisions are what make AI systems accurate, useful, and trustworthy.
AI chatbots transformed how people interact with technology, but AI agents are taking the next step. Learn the key differences, real-world applications, and why AI agents are shaping the future of intelligent software.
Artificial intelligence is transforming how software is built, but technology alone is not enough. Discover why problem-solving, critical thinking, and creativity remain the most valuable skills in the AI era.
