Workspace Agents Need Change Control, Not Just Prompt Engineering
Workspace Agents Need Change Control, Not Just Prompt Engineering
#llm
36 articles
Model Portfolio Governance After GPT-5.5 and DeepSeek-V4: A Practical Operating Model
How platform teams can run mixed proprietary and open models with measurable quality, risk, and unit economics.
Structured Outputs as Reliability Contracts: An LLM Ops Playbook for Enterprise APIs
How to convert brittle prompt parsing into schema-driven contracts with validation layers, fallback policies, and measurable error budgets.
Inference Reliability in 2026: Vendor Verification, Multi-Provider Routing, and SLO-Aware Fallbacks
How teams should verify model provider claims and design resilient routing across heterogeneous inference backends.
Claude Opus 4.7 and Claude Design: An Enterprise Workflow for Design-to-Delivery
How enterprise teams can combine Claude Opus 4.7 and Claude Design to reduce handoff latency between product, design, and engineering without losing governance.
Defending Against Hostile Distillation: A Practical Security Program for AI Teams
A governance and engineering playbook to reduce model extraction risk while maintaining partner ecosystem velocity.
Cloudflare Workers AI After Gemma 4: Designing for Unit Economics, Latency, and Task Routing
How to redesign edge AI workloads after new model availability and pricing shifts: routing, caching, SLOs, and cost controls for production teams.
Copilot Memory Meets Enterprise Knowledge Governance
How to design safe persistent context for coding assistants using scope boundaries, retention policy, and review loops.
After Codex Model Deprecations: A Migration Playbook for Stable AI Developer Platforms
How platform teams should handle rapid model deprecations in coding assistants without disrupting delivery, quality, or compliance.
From Demo to Device Strategy: Operational Lessons from Local Gemma 4 Momentum
How enterprises can evaluate on-device LLM opportunities without sacrificing security, supportability, or governance.
Gemma 4 Commercial Use and Multimodal Support: An Enterprise Edge-AI Adoption Playbook
How to evaluate and operationalize commercially usable multimodal small models for endpoint and edge workflows with governance and cost discipline.
Model Routing in 2026: Cost-Latency Governance Patterns for Enterprise AI Products
Design patterns for selecting, fallbacking, and auditing LLM calls across vendors without losing product quality.
GitHub Copilot SDK Public Preview: An Enterprise Integration Playbook
How platform teams can safely productize the new Copilot SDK with policy, observability, and staged rollout controls.
TurboQuant and the New Quantization Race: A Production Playbook for LLM Teams
Reports of major compression advances renew the quantization race. Here is a practical path to ship lower-cost inference without quality collapse.
GitHub Copilot in 2026: Model Routing, Premium Budgets, and Enterprise FinOps Controls
A practical operating model for managing Copilot model choices, premium usage, and quality risk across large engineering organizations.
GitHub Copilot Model Deprecations: Enterprise Governance Playbook for Safe Migration Windows
A practical operating model for handling model retirements in GitHub Copilot without disrupting developer productivity or compliance posture.
TurboQuant and the New Economics of LLM Serving: A Practical Capacity Playbook
How to translate major LLM memory-compression gains into concrete architecture, FinOps, and reliability decisions.
Local LLM Adoption in 2026: Cost, Privacy, and Operations Playbook for IT Teams
A practical guide for choosing where local models fit, from developer laptops to controlled on-prem inference pools.
Copilot Auto-Model Transparency: A Practical FinOps and Governance Playbook
How to operationalize GitHub Copilot model-level visibility into budget controls, policy guardrails, and engineering outcomes.
Copilot Auto-Model Resolution: Building a FinOps and Audit-Ready Control Plane
How platform teams should redesign Copilot governance now that auto model usage is resolved to actual models in metrics.
GPT-5.3-Codex LTS in GitHub Copilot: An Enterprise Rollout Blueprint for Speed Without Audit Blind Spots
A practical operating model for adopting GPT-5.3-Codex LTS in Copilot with policy tiers, unit economics, and compliance-grade evidence.
Copilot Auto-Model Resolution Metrics: A FinOps and Governance Playbook for Engineering Leaders
How to operationalize GitHub Copilot’s resolved model metrics for cost controls, policy design, and developer productivity governance.
OpenAI + Astral and the Python Toolchain Shift: A Governance Playbook for Enterprise AI Teams
What Python platform owners should standardize first when Ruff and uv become part of AI coding workflows: build reproducibility, policy controls, and release gates.
GitHub Copilot GPT-5.3-Codex LTS: Enterprise Rollout and Risk Controls
A practical rollout blueprint for moving enterprise Copilot programs to GPT-5.3-Codex LTS without breaking compliance, budget, or developer flow.
Copilot Auto Model Selection in JetBrains: Enterprise Control Patterns That Actually Work
Auto model selection can improve coding velocity, but only if organizations pair it with data boundaries, audit trails, and measurable quality guardrails.
From MicroGPT Demos to Production Decisions: Tiny-Model Evaluation Playbook
How to use minimal GPT implementations as a controlled lab for architecture learning, benchmarking, and safe production decisions.
Copilot Auto Model Selection in JetBrains: Governance Before Convenience
Auto model selection improves developer flow, but teams need policy, observability, and exception controls before broad rollout.
Gemini in the Browser Is Forcing Enterprise Control Plane Redesign
Google is embedding assistant capabilities directly into browser workflows, forcing teams to redesign governance, observability, and data controls.
GitHub Copilot with GPT-5.4: Risk-Tier Routing That Actually Works
A practical governance design for rolling out GPT-5.4 in Copilot without turning pull request reviews into chaos.
Copilot Model Routing SLOs in 2026: From Feature Launch to Operational Discipline
How platform teams can operate multi-model Copilot deployments with latency, quality, cost, and policy SLOs instead of ad-hoc defaults.
Copilot Workspace Governance in 2026: From Fast Suggestions to Accountable Delivery
How teams can combine GPT-5.4, editor policy, and review telemetry to scale AI-assisted coding without losing control.
GitHub Copilot with GPT-5.4: An Enterprise Rollout Governance Playbook
How engineering leaders can safely scale GPT-5.4-powered Copilot with policy controls, metrics, and review discipline.
GitHub Copilot GPT-5.4 Rollout Playbook for Enterprise Teams
How to introduce GPT-5.4 in Copilot without breaking review quality, security controls, or delivery predictability.
Model Routing in PR Comments: A Governance Pattern for Faster Reviews
Using model selection in pull-request comments to align review depth, cost, and risk with change criticality.
Prompt Injection Red Teaming for Coding Agents: A Practical Playbook
How engineering teams can test whether coding assistants leak secrets, follow poisoned instructions, or break trust boundaries.
Sovereign On-Prem LLM Programs Are Entering the Production Phase
Enterprise announcements around Qwen-class on-prem models show a shift from experimentation to governed, costed, and auditable internal AI platforms.