The PromptWake blog
Guides and ideas on capturing, searching, and reviewing your AI coding history.
AI Data Loss Prevention: A Buyer's Guide to What It Covers
The first of five guides to the tool categories that get called 'AI monitoring'. This one answers whether confidential data left the company through an AI tool — and stops measuring the moment the prompt is sent.
Shadow AI Discovery: A Buyer's Guide to Finding What Is Already in Use
The second of five guides to the categories called 'AI monitoring'. This one answers which AI tools people are using without approval — an inventory question, and the one most likely to be answered wrongly with confidence.
AI Application Security: A Buyer's Guide for the AI You Ship
The third of five guides to the categories called 'AI monitoring'. This one protects the AI systems you deploy — models, applications and agents — and has nothing to do with the AI your developers use to write code.
LLM Observability: A Buyer's Guide to Watching the AI You Built
The fourth of five guides to the categories called 'AI monitoring'. This one tells you whether your own AI feature is working and what it costs — and sees exactly nothing your developers' coding tools do.
AI Code Provenance: A Buyer's Guide to the Category We Are In
The last of five guides to the categories called 'AI monitoring'. This one asks what AI actually built and whether you can reconstruct why — and it is the one we sell, so read it with that in mind.
How to Monitor Employee AI Usage: A Map of the Tool Categories
Every vendor in this space says visibility, prompts, and audit - but they solve five different problems. Here is an honest map of the categories, which tools belong to each, and how to tell which one you actually need.
Claude Code Deletes Your History After 30 Days
The retention default is 30 days and the setting that controls it is absent from a normal install. Here is how to check your own machine, how to stop the deletion, and why stopping it is not the same as solving it for a team.
SOC 2, Security Questionnaires and AI-Written Code
What you are actually asked to prove about AI-generated code in 2026 — which is less than the EU AI Act headlines suggest and more than most change-management narratives currently cover.
Where OpenCode Stores Your Session History
OpenCode keeps every session in one SQLite database under ~/.local/share/opencode. Here is the schema, the queries that let you read your own history, and what to do about the fact that it is one file.
Where Gemini CLI Stores Your Chat History — and When It Deletes It
Gemini CLI keeps sessions per project under ~/.gemini/tmp, and deletes anything older than 30 days by default. Here is the layout, the setting that controls the deletion, and how to turn it off.
Where Windsurf Stores Your Cascade Chat History
Windsurf keeps Cascade conversations in ~/.codeium as binary protobuf files — one per conversation, unreadable in a text editor, with no export. Here is the layout and what you can actually do about it.
Where Codex CLI Stores Your Session History
Codex writes every session to a JSONL rollout file under ~/.codex/sessions, and recent versions index them in a SQLite database alongside. Here is the layout, what each file holds, and how to keep it.
Where GitHub Copilot Stores Your Chat History
Copilot Chat is saved per workspace, in a directory named after a hash of your project's path. Here is the exact location, why renaming a folder makes the history vanish from the UI, and how to get it back.
Where Cursor Stores Your Chat History
Cursor keeps every conversation in one SQLite file on your disk. Here is the exact path, how to read it yourself, why it is the single point of failure people discover the hard way, and how to back it up.
Cursor Chat History Disappeared: How to Get It Back
Four things cause Cursor chat history to vanish, and three of them are recoverable. Diagnose which one you have, then use the file Cursor already keeps — or read the conversations straight out of the database with SQL.
How to Back Up Your AI Coding History
Every AI coding tool stores its history somewhere different, in a different format, under different rules — and two of them delete it after 30 days. Here is the complete map, one script that backs all of it up, and an honest account of what a backup does not solve.
Edge Computing and Serverless Architecture: A Developer's Guide
A deep technical guide covering edge compute platforms, serverless function models, cold start optimization, state management patterns, database access from serverless, and when to choose serverless over traditional infrastructure.
Cross-Platform Mobile Development: Choosing Your Strategy
A comprehensive comparison of React Native, Flutter, Kotlin Multiplatform, and native development - with practical advice for teams choosing their mobile strategy.
Modern Software Testing Strategies: From Unit to E2E
A practical guide to building a testing strategy that actually catches bugs without slowing you down - covering unit tests, integration tests, E2E with Playwright, TDD, property-based testing, visual regression, mocking patterns, and the testing trophy vs pyramid debate.
Observability and Monitoring: A Complete Guide for Engineering Teams
A practical deep-dive into observability - covering the three pillars, OpenTelemetry, structured logging, distributed tracing, alerting strategies, SLI/SLO frameworks, and how to build a culture that treats production data as a first-class concern.
Machine Learning Engineering: Building Production ML Systems
A practical guide to building production ML systems - covering MLOps, feature stores, model training pipelines, serving infrastructure, monitoring drift, and the workflows that separate ML engineering from traditional software engineering.
Micro Frontends Architecture: Scaling Frontend Development
A practical guide to micro frontends covering Module Federation, iframe integration, single-spa, communication patterns, routing, deployment, and when to avoid the architecture altogether.
Data Engineering and ETL Pipeline Patterns for Modern Teams
From batch processing to real-time streaming, learn the patterns that power modern data platforms and how to build pipelines that scale.
WebAssembly in Modern Web Development: Beyond JavaScript
How WebAssembly is changing the web platform - from high-performance browser applications to serverless compute. A practical guide for developers.
Developer Experience Engineering: Building Tools Developers Love
How to design APIs, CLIs, documentation, and developer platforms that make users productive and happy. A practical guide to DX engineering.
Progressive Web Apps: A Deep Dive into Modern Web Capabilities
Service workers, offline-first architecture, push notifications, and everything you need to build PWAs that compete with native apps.
Secure Coding: A Developer's Guide to Writing Safe Code
Security is not the ops team's job. Every line of code you write either opens a door or bolts it shut. Here is what every developer needs to know about writing secure code in 2026.
Building a Modern CI/CD Pipeline: From Commit to Production
A practical guide to designing CI/CD pipelines that are fast, reliable, and secure - covering GitHub Actions, GitLab CI, caching, deployment strategies, and production monitoring.
API Design: REST vs GraphQL vs gRPC - How to Choose
REST, GraphQL, and gRPC each solve a different problem. This guide compares their design philosophies, trade-offs, and ideal use cases so you can make an informed decision for your next API.
The Complete Guide to React Performance Optimization
From memo to server components - a practical guide to making your React app faster without over-engineering it.
Modern TypeScript: Patterns and Practices for 2026
From strict configuration to type-safe API clients - the TypeScript patterns that separate production-grade code from toy projects in 2026.
Docker and Kubernetes: A Practical Guide for Modern Developers
A no-fluff guide to containerization, Dockerfile best practices, Kubernetes fundamentals, and knowing when you actually need an orchestrator.
System Design Fundamentals Every Developer Should Know
Load balancing, caching, sharding, CDNs, message queues, CAP theorem, rate limiting - demystified with real-world examples and configs you can actually use.
Monolith vs Microservices: How to Choose Your Architecture in 2026
The architecture pendulum has swung. Microservices are no longer the default answer. Here is how to decide - with practical advice on modular monoliths, extraction strategies, and the one question that cuts through the debate.
The State of AI-Assisted Coding in 2026: Trends, Tools, and What's Next
AI coding assistants have crossed the chasm. Over 70% of professional developers now use them daily. Here is a survey of the tools, protocols, and workflow changes defining development in 2026.
Database Design Patterns for Modern Applications
From choosing between relational and NoSQL to managing migrations in CI/CD, these are the database design patterns every developer needs to know.
How to Keep a Searchable Memory of Your AI Coding History
AI assistants write more of your code every week - but the prompts, decisions, and diffs behind them vanish. Here is how to capture your AI coding history into one searchable, restorable timeline.
Prompt Engineering Patterns for Software Development
Not all prompts produce good code. These battle-tested patterns will help you get better results from AI assistants every time you open a chat.
The Developer's Guide to Reviewing AI-Generated Code
AI writes a growing share of every pull request. Here is how to review AI-generated code effectively - what to look for, what to trust, and when to rewrite.
The Complete Guide to Debugging with AI Assistants
AI assistants excel at finding bugs - if you know how to ask. This guide covers the techniques that turn AI from a code generator into a debugging partner.
Terminal Productivity Hacks for AI-Assisted Development
Your terminal is the most powerful tool in your development workflow. Here is how to optimize it for the age of AI-assisted coding.
Building a Local-First Development Workflow
Most developer tools default to the cloud. Here is why local-first is the better default for privacy, speed, and reliability - and how to set it up.
Collaborative AI Development: Best Practices for Teams
AI is often used individually. The teams that get the most value from AI use it collaboratively. Here is how to build team-wide AI workflows that scale.
From Prompt to Production: Managing AI-Generated Code Through the Software Lifecycle
AI code does not stop at generation. Here is how to take AI-generated code through testing, review, staging, and deployment with confidence.
The Art of AI Pair Programming: Working with AI Assistants
The best AI-assisted development is a partnership, not a delegation. Here is how to pair program with AI effectively - when to lead, when to follow, and when to take the keyboard.
Building a Second Brain for Your Code
Your codebase contains thousands of decisions, each with a reason. Here is how to capture, organize, and search the knowledge that your code alone cannot express.
The Future of Software Development in the Age of AI Agents
AI agents are moving beyond code generation toward autonomous development. Here is what the next wave of AI-assisted development looks like and how to prepare.