People / Author
Joshua Wendt
Articles by Joshua Wendt on AI implementation, workflow automation, and software engineering.
189 articles · Page 14 of 16
The AI Software Selloff: A $1T Wake-Up Call
AI product launches wiped $1 trillion from software valuations in one week. Here's what the selloff signals for your business.
Claude Opus 4.6: Adaptive Thinking, 1M Context
Claude Opus 4.6 introduces adaptive thinking, a 1M-token context window, and leads agentic benchmarks with 80.8% on SWE-bench.
Building Software That Survives the AI Wave
The SaaSpocalypse is real for some software, overblown for others. Here's what AI can't replicate and how to build for it.
GPT-5.3-Codex: OpenAI's Agentic Code Model
OpenAI releases GPT-5.3-Codex with 77.3% on Terminal-Bench 2.0, an agentic coding model partially used in its own creation.
Why Automation Should Come Before AI
Automate workflows before investing in AI. Automation delivers immediate ROI and builds the clean data pipelines AI needs to succeed.
Emergent AI: When Models Surprise Creators
Why large AI models develop surprising capabilities like arithmetic and reasoning that smaller models lack. Emergent behaviors explained.
Foundations of Transformer Reasoning
A technical deep-dive into transformer architectures, attention mechanisms, scaling laws, and emerging techniques for reliable AI reasoning.
Prompt Engineering: Better Results From AI
Practical techniques for writing effective prompts that produce reliable AI outputs. Works across ChatGPT, Claude, Gemini, and other LLMs.
Taxonomy of AI: From ML to World Models
A map of AI systems — machine learning, deep learning, LLMs, multimodal models, and world models — with clear definitions and comparisons.
Technical Debt: The Product Velocity Killer
Technical debt compounds silently until it dominates your roadmap. Learn to measure, communicate, and systematically reduce it.
Why Bigger AI Models Work Better
The science behind AI scaling laws and chain-of-thought reasoning, without the PhD. Why larger models are smarter and how to use them.
Seven AI Mistakes That Sink Projects
Most AI initiatives fail due to predictable organizational and technical missteps, not bad technology. Here's how to avoid them.