Open-source LLMs crossed into practical, low-cost coding workflows in 2025, while frontier models still lead on deep reasoning and completeness. The next phase demands specialization, hybrid stacks, and new benchmarks...

Addy Osmani's data-driven review finds AI handles isolated React tasks (~40%) but falters on chained integrations (~25%). The cure is context engineering, tooling (MCPs), and stepwise workflows—not swapping models.

Practical guide to Claude Code 2.0: CLI agent workflows, sub-agents, Task tool schema, and context engineering. Learn QoL improvements, hooks, plugins, and tactics to prevent context bloat for long-running agents.

Armin Ronacher shifts from embedding MCP tool specs into LLM prompts to lightweight 'skills'—short guides that teach agents to use tools. Skills cut token bloat, ease maintenance, and allow quick updates.

Practical patterns to prevent Context Rot and simplify multi-agent coordination. Harness-level tactics—compaction, summarization, hierarchical tooling, and agent-as-tool calls—for resilient, efficient AI agents.