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Insights, updates, and deep dives from the Promptev team.
- AI
AI Agents for Banks and Insurers: 7 Use Cases That Pay Off, and How to Deploy Them Safely
Seven AI agent use cases for banks, insurers and takaful operators, the controls regulators expect, and a 90-day plan from pilot to production.
- AI
Permission-Aware AI: How to Stop Your AI Assistant From Oversharing
Why company AI assistants show people documents they should not see, how permission-aware AI prevents it, and a 10-point test to run before you buy.
- AI
Sovereign AI Agents: What They Are and How to Run Them in Your Own Cloud
What sovereign AI agents are, the four ways to deploy them, the questions to ask every vendor, and how to keep data, models and actions under your control.
EngineeringThe promptev Context Engine: the right facts, only for those allowed to see them
How the promptev Context Engine finds the right facts across your documents and systems, returns only what the asker may see, cites its sources, and how to use it from Python, JavaScript, the API or MCP.
AIpromptev agents now cost up to 83% less on large data
We ran the same questions on promptev agents before and after our latest release. Cost per answer fell by 58% to 83%, and tokens fell by 35% to 78%.
EngineeringThe Supabase Extension Trap: Why CREATE EXTENSION Succeeds and Your Query Still Fails
On Supabase, CREATE EXTENSION puts pg_trgm in the extensions schema, so similarity() fails in production. Why it happens, how to catch it, and the fix.
AIEU AI Act Article 12: What Your RAG System Has to Log, and What Most Don't
EU AI Act Article 12 record-keeping for RAG: what the logging duty says, the records a retrieval layer can emit, and the three things you still build.
AIYour ACL Benchmark Is Measuring the Easy Case
Benchmarks assign permissions at random. With team-shaped ones, filtering after a 10x fetch recovers 0.419 of results, not 0.730, for a caller who sees 10%.
AIHow Promptev MCP Server Solves Tool and Context Chaos for AI Coding Teams
Every developer using AI coding tools hits the same wall: one MCP server, then five. See how the promptev MCP server puts every tool behind one URL.
AIRAG Alternatives: What to Use Instead, and When RAG Is Still Right
7 RAG alternatives compared: long context, fine-tuning, GraphRAG, agent memory, hybrid search, tool calls and permission-aware retrieval. When each wins.
AIFrom Lawyers to AI Operators: The Shift Happening Now In 2026
For decades, being a lawyer meant mastering legal knowledge, drafting documents, and manually reviewing contracts line by line. Your value…
AIAI Agents for Legal Teams: Beyond Chatbots, Into Automation
Legal teams have always been known for precision, long hours, and heavy documentation. But today, you’re facing a different kind…
AITop 7 Agentic AI Use Cases in Data Engineering
You don’t lose sleep because of data. You lose sleep because pipelines break at 3 AM. Modern data engineering isn’t…
AIIs Context Engineering Worth the Cost? A Practical ROI Breakdown
You’ve probably heard promises about AI transforming your business. Every business owner wants faster decisions and automated workflows in their…
AIWhy Founders Must Rethink Prompt Engineering in 2026
You’ve probably heard a lot about prompt engineering. It sounds simple: write the right instruction, feed it to an AI…
AI9 Tips: How to Choose the Right Context Engineering Platform for Your AI Stack
Choosing the right context engineering platform is not about features, dashboards, or pricing alone. It is about understanding how your…
AIReal-World Challenges with RAG at Scale & How to Fix Them: 5 Challenges vs 5 Solutions
Retrieval-Augmented Generation looks deceptively simple. You connect your documents, embed them, store them in a vector database, and pass the…
AI9 Tips: How to Tune Retrieval Models for Best RAG Accuracy
When you build a Retrieval Augmented Generation (RAG) system, accuracy does not come from the language model alone. It comes…
AIHow to Evaluate RAG Systems Using Benchmarks Like MS-MARCO and Natural Questions
How to use the MS MARCO and Natural Questions datasets to train and evaluate a RAG system: what each measures, the metrics to report, and common mistakes.
AIWhy Your AI Integrations Break During Real Workflows: Guide to Build Resilient AI Systems
You build an AI system. It works perfectly in testing. Demo looks flawless. Everyone’s impressed. But the moment real users…
AIYour LLM Output Quality Drops Over Time: 5 Tips to Maintain Consistency at Scale
When you first deploy a Large Language Model (LLM), everything feels impressive. Responses are sharp. Accuracy is high. Teams are…
AIWhat Is Agentic AI and Why It’s Becoming a Must-Have in 2026
Agentic AI decides, acts and completes complex tasks without constant supervision. What it is, how it differs from other AI, and why it matters in 2026.
AIAI Costs Are Out of Control: How Context-Aware Workflows Cut Costs
If you’re running AI at scale, you’ve experienced the same frustrating pattern every month. Your cloud bills spike. Token consumption…
AIYour RAG Pipeline Isn’t Performing: 5 Real Reasons and How to Fix It
You built a RAG pipeline because it promised accurate answers, grounded outputs, and production‑ready AI behavior. On paper, everything looks…
AITop 9 Use Cases: How AI Agents Are Helping the Legal Industry
The legal industry is undergoing one of the fastest digital transformations in its history. As firms face growing case volumes,…
AIContext Layer vs Knowledge Graph vs RAG vs Agent Memory: What’s the Difference?
Context layer vs knowledge graph vs RAG vs agent memory: what each one stores, where each fails, and a decision table for choosing between them.
AIHow Context Engineering Improves AI Workflow Accuracy
AI systems have become a core part of business operations, but even the best models still make mistakes. They forget…
AIWhat Is a Context Engineering Platform?
AI systems are becoming more advanced every day, but even the most powerful models struggle without the right context. You…
AIHow Enterprises Can Build AI Workflows Without Rewriting Their Entire Tech Stack
You might think that bringing AI into your business means tearing down everything you’ve built so far. But that’s not…
AIThe Missing Layer in LLM Systems and How Context Engineering Solves It
Large Language Models (LLMs) like GPT, Bard, and other advanced AI platforms have transformed the way we interact with technology.…
UncategorizedThe End of Copy-Paste Prompts: How PromptOps Is Changing AI Forever
PromptOps applies versioning, review, testing, rollback and measurement to production prompts. What it covers, why copy-paste prompts break, how to start.
AICustom AI Agents on a Promptev Platform
Custom AI agents on promptev: build agents without code on your own documents and tools, scoped to each person, on PromptevAI or your own keys.
AIRiding the Waves of Tech: Why Generative AI Is the Next Big Leap
Generative AI in plain terms: what LLMs and GPTs actually do, why AI assistants that read, write and summarize are the next big leap, and what changes.
AIFrom Chaos to Clarity: How Context Engineering is Revolutionizing AI Automation Workflows
Context engineering for AI automation: how structured context turns chaotic workflows into consistent ones, with use cases, benefits and common pitfalls.