Blog
Product updates, guides, and ideas on shipping prompt changes without redeploying.
June 10, 2026
How to Let Non-Engineers Edit AI Prompts Safely (Without Code)
88% of companies use AI, but only ~1 in 5 capture real value. The bottleneck is the prompt-edit loop — here's how non-engineers edit AI prompts safely.
June 10, 2026
Few-Shot Example Selection: How to Pick Demonstrations That Actually Work
Choosing the closest examples scored 46.0 EM vs 31.0 for the farthest in one GPT-3 study. Here's how to select and order few-shot demonstrations that work.
June 10, 2026
LLM Evals: How Do You Test an AI Feature Before It Ships?
31% of teams run no LLM evaluation at all. Here's what an eval actually is, what to test, whether to trust LLM-as-a-judge, and how to gate a prompt change before it ships.
June 10, 2026
Who Should Own Prompts? How PMs and Engineers Collaborate on AI
57% of teams now steer AI with prompts, not fine-tuning (LangChain, 2024). That makes the prompt a shared artifact — here's how PMs and engineers split the work.
June 10, 2026
Prompt Engineering Techniques: What Actually Works for Engineering Teams?
66% of developers say AI output is "almost right, but not quite." Most of that gap is fixable with prompting technique — here are the five that work.
June 10, 2026
Prompt Management Tools Compared: How to Choose in 2026
88% of organizations use AI but only ~6% capture real value. Compare prompt management approaches — DIY, Git, observability, eval, and dedicated platforms.
June 10, 2026
System Prompts: How to Write and Manage Them at Scale
Average prompt length quadrupled to 6K+ tokens in 2025. Here's how to write a system prompt that holds up — and govern it like production config, not a buried string.
June 10, 2026
Who Should Own Your AI Prompts?
Nearly a quarter of companies say nobody clearly owns AI (Sweep, 2025). Here's who should own your AI prompts — and how product and engineering split the job.
June 6, 2026
How Do You Build Reliable LLM Agents in Production?
SOTA agents succeed on under 50% of tasks and Gartner expects 40% of agentic projects canceled by 2027. Here's how to build LLM agents that survive production.
June 6, 2026
How to Set a Latency Budget for AI Features
A developer's guide to latency budgets for AI features. Latency is the
June 6, 2026
LLM Observability: How Do You Debug an AI App in Production?
41% of teams don't monitor LLM apps in production at all. Here's what LLM observability is, what to track, and how to trace a regression back to the prompt that caused it.
June 6, 2026
How to Measure Whether AI Assistants Cite Your Content
AI referral visits grew 3x in a year, yet only 38% of AI-cited pages rank in Google's top 10. Here's how developers actually measure AI citations.
June 6, 2026
Multi-model prompt portability: managing prompts across Claude, GPT, and Gemini
81% of enterprises now run three or more model families in production. Here's why a prompt that shines on GPT can quietly degrade on Claude — and how to fix it.
June 6, 2026
Prompt Injection: Why It's the #1 LLM Risk and How to Defend Against It
Prompt injection is OWASP's
June 6, 2026
Stop Hardcoding Prompts in Your Codebase
1.13M public repos now depend on gen-AI SDKs, and most bake prompts straight into source. Here's why that breaks at scale — and how to pull them out.
June 6, 2026
Structured Outputs with Claude: How Do You Get Schema-Valid JSON Every Time?
84% of developers ship with AI, yet "almost right" output is the top frustration. Here's how Claude's structured outputs return schema-valid JSON every time.
June 3, 2026
Prompts are config, not code
88% of companies run AI in production, yet most still ship prompt changes through a full redeploy. Here's why prompts belong in config, not code.
June 2, 2026
AI governance is becoming an engineering problem
97% of organizations breached through AI lacked basic access controls. Governance has moved from legal's spreadsheet into the engineering stack — here's what that means for CTOs.
June 2, 2026
Generative Engine Optimization for Developers: How to Get Your Docs Cited by AI
Gartner predicts search volume drops 25% by 2026 as buyers shift to AI assistants. Here's how engineering teams structure docs to get cited by AI.
June 2, 2026
How Can Engineering Teams Cut LLM Costs Without Hurting Quality?
Token prices fall ~10x a year, yet GenAI spend hit $644B in 2025. Here's how engineering teams cut LLM costs with caching, model routing, and batching.
June 2, 2026
Prompt Caching: How to Cut LLM Token Costs Without Touching Quality
A practical guide to prompt caching for engineering teams. Anthropic, OpenAI, and Google now discount cached input tokens up to 90% — here's how to capture it.
June 2, 2026
Prompt Engineering in 2026: Why It's Becoming an Operations Problem
Adoption of AI coding tools hit 84% in 2025, but developer trust fell to 29.6%. Here's how prompt engineering became a production operations problem.
June 2, 2026
Prompt Management for Teams: How to Ship LLM Prompts Safely
88% of orgs now use AI, but only ~6% capture real value (McKinsey, 2025). The gap is prompt management — here's how engineering teams close it.
June 2, 2026
Prompt Versioning Best Practices: Ship LLM Changes Safely
A practical guide to prompt versioning. McKinsey reports 88% of organizations use AI, yet only ~6% capture real value — disciplined change control is the gap.