The next leap in AI software development: from assistance to orchestration
The next wave is not just writing code with a copilot. It is coordinating supervised agents, context, tests, and boundaries across the entire development lifecycle.
Term
Software-Engineering
Ontologies for AI agents: the missing contract between model, memory, and tools
LLMs can converse, but they do not share a stable domain model. Ontologies, knowledge graphs, and semantic validation can give agents a common vocabulary, safer actions, and verifiable memory.
When Commits Scale Faster Than Reviews
Code volume is growing faster than human review capacity. The problem is not using AI, it is pretending review still costs the same.
Meta Harness: the missing layer in agent engineering
The agent is no longer the whole product. The next jump is the layer above it: memory across sessions, coordination across agents, context across repos, and automatic optimization of the harness itself.
Domain-specific agents: composition against the bloated agent
The generic agent looks simple until it becomes a giant context window with too many tools, too many permissions, and too much cost. Domain-specific agents trade that accumulation for composition, clear boundaries, and cheaper execution.