How the central question of building with AI has shifted three times in four years — from 'what should I say?' to 'what system should I build?' A deep dive into prompt engineering, context engineering, and harness engineering with architecture diagrams, decision frameworks, and production lessons for engineering leaders.
One year after Andrej Karpathy coined 'vibe coding', the industry is moving on. Discover why vibe coding fails at scale — context collapse, cognitive debt, zero system design — and how agentic engineering is emerging as the professional discipline for AI-first software development.
A personal take on the hidden cost of AI-generated briefs. When CEOs and managers skip the reasoning process and hand developers full AI implementations as 'briefs,' they double the workload instead of halving it. The same problem plagues multi-agent AI systems — and the solution is the same: a Harness.
The vision behind building autonomous AI agents for every role in a software team: PO, BA, QC, TA, SSE, DevOps, TL, and PM. From solo developer bottleneck to an AI-powered development pipeline.
Complete hands-on guide to building a production-ready agentic AI system. From project setup to deployment — every layer implemented with working code, tests, and Docker compose.
A complete technical guide to building a profitable agentic AI system using only open-source tools — with retrieval, orchestration, tool use, and observability. Includes architecture diagrams and real cost analysis.
Stripe's autonomous agents write 1,300 PRs per week. OpenAI extended its Responses API with shell tools. AWS launched Strands Labs. The agentic shift is no longer theoretical — here's what it looks like in the real world.
GPT-5.4 crossed human performance on desktop tasks. With a hosted shell, 1M context window, and native compaction, the era of AI as an autonomous coworker is finally here — and the implications for developers are profound.
Cursor's March 2026 release brings parallel subagents, BugBot Autofix, and cloud agents — a genuine shift from AI coding assistant to AI workflow engine. Here's what it means for real teams.
94% of engineering leaders report agentic AI skills gaps. Here's what the tech lead role actually looks like in 2026 — and the skills you need to stay relevant.
Most people are stuck in Phase 1 of AI — asking questions and doing work themselves. Phase 2 is Agents: you set a goal, the agent delivers results. Here's the complete breakdown of what changed, how it works, and why it matters.
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