The fenbs blogAll articles
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- Learn a Language With AI: A Practice Routine That LastsUse AI for focused language practice, checked feedback, and a record of recurring mistakes. Build a routine around something you want to say without help. · 5 min read
- AI Email Maker: Draft Professional Messages You Can CheckGive an AI email maker the audience, purpose, and verified facts before asking for polished prose. Use a repeatable review to keep the message accurate. · 5 min read
- AI for Business Operations: Workflows People Can ReviewUse AI to prepare routine operating work from approved information, with clear checks before anything changes. Keep procedures, exceptions, and handoffs visible across sessions. · 6 min read
- AI for Policy Writing: Draft Clear Rules for Human ApprovalTurn approved requirements into a policy draft that people can understand and review. Use AI to find gaps while keeping policy choices with the responsible people. · 5 min read
- AI in Financial Software Development: Requirements and ReviewDefine what an AI feature may suggest, which evidence it must show, and who reviews the result. Keep financial data in approved systems while preserving project decisions. · 5 min read
- AI Team Structure: Who Owns the Work and Reviews It?An AI team needs clear human responsibilities for outcomes, inputs, tools, and review. Start with the work people actually do, then make ownership visible to every assistant. · 6 min read
- Apple Notes Second Brain: A Simple Setup for WorkUse Apple Notes to collect ideas, connect references, and return to active projects. Prepare selected summaries for AI work while keeping personal notes separate. · 5 min read
- Chatbots for English Conversation Practice: A Study WorkflowPractice one realistic English conversation, review a few useful corrections, then try again. Keep a clear next step so each session builds on the last. · 5 min read
- ChatGPT Story Writing: Plan, Draft, and Keep ContinuityUse ChatGPT to explore a story, question a scene, and test revisions while keeping creative choices yours. Save approved story facts so the next session starts from the same version. · 5 min read
- CLAUDE.md Size: Limits, Useful Length, and What to CutA file that fits technically can still carry too much instruction. Learn how to judge CLAUDE.md length, separate it from auto memory, and remove changing project history safely. · 6 min read
- Does ChatGPT Save Your Data? Chats, Files, and RetentionChatGPT can retain chats and files, but history, memory, and separately saved files have different controls. Learn what to review before relying on deletion or chat history. · 5 min read
- How to Keep Using ChatGPT After a Limit Stops Your WorkRead the limit message, check the legitimate ways to resume, and save a restart note so a pause does not cost you the project context. · 5 min read
- Copilot for Microsoft 365: What It Does and How to StartUnderstand Copilot for work apps, the permissions behind its answers, and the rollout questions to settle before your team relies on it. · 5 min read
- Zettelkasten Tags: When to Use Them Instead of LinksUse tags to find a useful group of notes and links to explain relationships between ideas. This workflow keeps your index small and your research ready for reuse. · 5 min read
- What Is Mem0? The Memory Layer for AI Agents, ExplainedMem0 is a memory layer that developers put between their app and the model: it extracts facts from conversations, stores them per user, and hands the relevant ones back before the next answer. How it works, what the managed and open-source versions differ on, and who it is for. · 7 min read
- Mem0 Alternatives: Supermemory, Letta, Zep, Cognee and a Shared BoardThe right Mem0 alternative depends on why you are looking. Supermemory, Letta, Zep and Cognee each solve agent memory a different way, and for a team that wants memory people can read and correct, a shared board does a different job altogether. · 7 min read
- Mem0 vs Supermemory: Two Memory Engines ComparedMem0 and Supermemory both give AI apps long-term memory through an API, but they start from different units: Mem0 from facts extracted out of conversations, Supermemory from documents and connectors that feed a memory graph. How they differ on scoping, correction, self-hosting and MCP. · 7 min read
- Letta vs Mem0 vs Zep: Three Different Answers to Agent MemoryLetta, Mem0 and Zep all come up when someone searches for agent memory, but they are three different kinds of product: an agent harness that keeps its own memory, a memory layer your code calls, and a governed context layer for enterprise data. How each works and which problem each solves. · 7 min read
- What Is Supermemory? Memory and Context Infrastructure for AI AgentsSupermemory is a memory and retrieval service for AI agents: you send it documents and conversations, and it builds a graph of facts that update over time, user profiles and searchable chunks behind one API. How it works, how it isolates users, what runs over MCP, and who it is for. · 7 min read
- Supermemory Alternatives: What to Use Instead, and WhenSupermemory is memory infrastructure for AI agents. The right alternative depends on why you are leaving: a different engine, a different hosting model, an agent framework, or a record your whole team can read and correct. · 6 min read
- ByteRover Alternative: Options for Shared Coding-Agent MemoryByteRover gives coding agents durable project memory in shared spaces. If you need something different, the right alternative depends on whether you want automatic capture, plain files in the repository, a company-wide context layer, or a board that people and every AI app share. · 6 min read
- Pieces for Developers Alternative: Automatic Memory or a Record You Write?Pieces remembers your work by capturing it on your machine. Alternatives fall into two camps: other tools that remember for you, and records that you and your AI assistants write on purpose and your team can read. · 6 min read
- AI Memory for Teams: One Record Every Person and Assistant SharesEach person’s AI remembering on its own does not add up to a team that remembers. Team AI memory is a shared record of rules, decisions, current work and handoffs that every person and every AI app can read, and that people can correct. · 6 min read
- Context Layer for AI Agents: Sentra, Glen, Unblocked and Augment ComparedA context layer connects to the systems where your company’s knowledge already lives and serves it to every AI agent. How four of them work, what they ask of you, and where a lighter shared board fits beside them. · 6 min read
- A MemoryPlugin Alternative for Work You Share With Other PeopleMemoryPlugin carries what you tell one AI into every other AI you use. If what you need to carry is a team’s tasks, decisions and progress rather than your own preferences, you need a different kind of tool. Here is how to tell which one you need. · 6 min read
- An AI Context Flow Alternative When the Context Is Your Team’s WorkAI Context Flow saves your briefs and notes once and brings them into ChatGPT, Claude, Gemini and other AI tools. When the context that matters is tasks, decisions and progress that several people share, a different tool does that job. · 6 min read
- A myNeutron Alternative for Keeping Track of Work, Not Just ReadingmyNeutron turns what you read, write and receive into a searchable memory you can bring into ChatGPT, Claude and Gemini. If the thing slipping away is the state of your work and your team’s decisions, here is what to use instead, or alongside it. · 6 min read
- A MemoryLake Alternative When You Need a Record of Work You Can ReadMemoryLake is a large, versioned memory that follows you, your files and your agents across AI apps. If what you need is a plain record of tasks, decisions and progress that people write and AI assistants follow, a different tool fits. · 6 min read
- Portable AI Memory: One Memory Across ChatGPT, Claude and GeminiEach AI app remembers you separately, and that memory stays with the vendor. There are three ways to make memory portable: copy it between apps, keep it in a tool that sits outside all of them, or keep the work itself on a shared board. Here is what each does and when to use it. · 6 min read
- Claude Import Memory: What Moves, What Does Not, and How to Keep Work in More Than One AppClaude can import what another AI assistant remembers about you in one paste. Here is what that carries over, what it leaves behind, and where the record of your work should live if you keep using more than one app. · 7 min read
- Claude Code Projects Shared Memory: What Every Thread Knows, and Where It StopsIn a Claude Code project, every thread adds to and reads from one project memory. How that memory is stored, how it differs from project instructions, CLAUDE.md and auto memory, and what it cannot be shared with. · 7 min read
- Vibe Kanban Alternatives: What to Use Now That It Is Community-MaintainedBloop, the company behind Vibe Kanban, closed in April 2026 and the project lives on as community-maintained open source. Whether you need an alternative depends on which part of it you relied on. Here are the options, job by job. · 7 min read
- Backlog.md Alternatives: When Your Tasks Should Leave the RepositoryBacklog.md keeps tasks as Markdown files in your Git repository, where coding agents can read and update them. It is a strong choice for one developer and their agents. Here is when an alternative fits better, and which kind. · 7 min read
- Rovo vs Linear Agents: AI Agents Inside Your Tracker, and Where a Lighter Board FitsJira and Linear both let you hand work to AI agents without leaving the tracker. How Rovo agents and Linear’s agents differ in setup, visibility, memory and coding, and when a lighter shared board is the better home for the work. · 8 min read
- AI Facebook Ad Optimization: Test Ideas and Check ResultsUse AI to propose useful ad tests, draft controlled variations, and question performance reports. Keep people responsible for claims, spending decisions, and the lessons carried into the next campaign. · 5 min read
- AI Governance Task Force: Members, Authority, and WorkGive an internal AI governance group a specific remit, the right perspectives, and a decision process. Leave each meeting with a human choice or a clear next action. · 6 min read
- ChatGPT Agent Sandbox: Files, Access and BoundariesThe former ChatGPT agent has given way to ChatGPT Work. Check where a task runs, what it can access and which approvals apply before delegating work. · 5 min read
- ChatGPT Enterprise Data Privacy and ProtectionUnderstand the difference between model training, service processing, organizational access, and sharing. Use those distinctions to write practical handling rules for work data. · 5 min read
- ChatGPT Prompts for Copywriters: Briefs, Ads and RevisionsBuild copywriting prompts around the audience, the evidence and the brand’s boundaries. Use them to explore options and revise copy without inventing claims. · 5 min read
- Claude Code Idle Compaction: What to PreserveAn idle compaction can change the context Claude continues with. Check the session state and keep a reviewed work checkpoint before relying on the summary. · 5 min read
- Does Claude Memory Use More Tokens?Remembered information can add material for Claude to process, but saved memory is not a simple token meter. Separate chat memory, local instructions, conversation context, and usage before trying to reduce overhead. · 5 min read
- Fireflies Note Taking: Capture, Check, and Export NotesSet up a deliberate recording, correct the transcript, and export a usable record. Carry only confirmed decisions and next steps into your continuing work. · 5 min read
- Obsidian AI Pricing: Separate Plugins, Models, and SyncAn Obsidian AI setup can involve several providers and separate bills. Check the note app, plugin, model access, and optional services individually before choosing a setup. · 6 min read
- Obsidian AI Security: Check Plugins and Data Leaving Your VaultAn AI plugin or connected assistant adds a new access path to your Obsidian notes. Check what it can read, where information goes, and who approved that sharing before using real project material. · 5 min read
- OpenAI Uses: Practical Features for Work and StudyExplore useful OpenAI capabilities through writing, research, analysis, and coding examples. Choose a task with an observable result and keep the project context ready for the next session. · 5 min read
- How to Share Context Between Claude SessionsGive the next session a checked account of the goal, decisions, current state, sources, and next action. Use recall as help, with a deliberate handoff for active work. · 5 min read
- Windsurf and Cursor Rules: How to Move Your InstructionsMove the meaning of your project rules, then check when they apply. Translate the editor settings while keeping approved decisions and unfinished work available outside either editor. · 5 min read
- Project Assumptions vs Decisions: How to Stop Guesses Becoming FactsA practical way for a small team to separate what it believes, what it has checked, and what a person has actually decided before anyone or an AI assistant acts. · 5 min read