OpenAI ships GPT-5.5: agentic coding gains at same latency
GPT-5.5 turns LLMs from code helpers into workflow owners—without adding latency.
GPT-5.5 turns LLMs from code helpers into workflow owners—without adding latency.
Agent regressions often come from orchestration and prompts—ship canaries, pin behavior, and instrument agents like any other prod service.
Copilot Individual just moved to stricter quotas and model gating, and the CLI now reflects that reality—plan upgrades and workflow tweaks accordingly.
Codex 0.125 turns the app-server into a sturdier, more observable backbone for production agent workflows.
Agentic coding is growing up: Cursor + Chainguard signals a shift from speed-first to verifiable, policy-driven agent workflows.
Stop grading just answers; start testing the agent system you’ll actually run.
Apps become plumbing; agents become the interface—so design your APIs, data access, and defenses for autonomous orchestration.
Treat LLM generation like a distributed system: stream blocks, throttle by tokens, and make every write idempotent.
Use Bedrock fine-tuning for consistent, strict formats and lower per-call costs; use RAG for knowledge.
Plan for LLMs that can read your whole codebase in one go—and budget and architect accordingly.
Agents now act, not suggest—treat their edits like production changes with full audit, rollback, and governance.
Plan for LLMs that act, not just chat—tighten sandboxes, egress, and approvals now.