AI has no memory. Without structure, every session starts from zero. Here’s how to fix it.
AI has no memory. Without structure, every session starts from zero. Here’s how to fix it.
You’ll discover a practical method to overcome AI’s lack of session memory by creating four markdown files—discovery, research, plan, and progress—that are version‑controlled, pasted at each start, and keep the project’s purpose, decisions, and status instantly available.
AI has no memory. Without structure, every session starts from zero. Here is how to fix that.
Tags: Vibecoding · Project structure · AI workflow · Productivity
Most vibe-coded projects do not fail because the idea is bad. They fail because there is no structure. You open a new AI session, explain the project from scratch, get halfway through a feature, close the tab, and next time you open it, the AI has no idea what you were building or why.
This is not a flaw in the AI. It just has no memory between sessions. So the fix is simple: you give it the memory yourself.
I use four markdown files for every project. They live in the root of the repo, they get committed like any other code, and they are the first thing I paste into any new AI session.
The ultimate shortcut to flawless AI results
Stop wasting time guessing prompts. Get consistent, professional AI results right from the first try, every time.
You do not fill them manually. You use a prompt. The AI interviews you, asks the right questions one at a time, and builds the file from your answers.
Why four files and not one?
You could dump everything into one big file. But keeping them separate means you only paste what is relevant. Starting a new session to work on a feature? Paste `plan.md` and `progress.md`. Revisiting a technical decision? `research.md` has it. Each file has one job. That makes them easy to update and easy to use.
The four files
`discovery.md` — What are we building?
Captures the core idea, the problem you are solving, who it is for, and what done looks like. This is the file that stops AI from optimising for the wrong thing. Without it, AI builds what sounds reasonable, not what you actually need.
Generate discovery.md via interview
AI interviews you about your project idea and generates a complete discovery.md file from your answers.
You are helping me create a discovery.md file for my Vibecoding project. Your job is to interview me and extract everything needed to write a clear, complete discovery document.
Interview rules:
- Ask exactly one question at a time. Wait for my answer before continuing.
- Ask follow-up questions if an answer is vague or incomplete.
- Do not summarise or comment between questions. Just ask.
- Keep going until you have covered all topics below.
Topics to cover:
1. What is the project called and what does it do in one sentence?
2. What problem does it solve and for whom?
3. Who is the target user? Be specific about their situation, skill level, and needs.
4. What does the user experience look like from start to finish?
5. What does success look like for this project? What are the measurable outcomes?
6. What are the must-have features for the first version?
7. What is explicitly out of scope for now?
8. Are there any hard constraints I already know about (budget, timeline, technical limits)?
9. What would make this project fail? What are the biggest risks?
Once you have answers to all topics, generate a clean discovery.md file in markdown. Use clear headings for each section. Write in plain language. Keep it to one page.
Tip: Run this before you write any code. If you struggle to answer the questions, the project is not ready to build yet.
`research.md` — What did we already figure out?
Stack decisions, tools you considered and rejected, technical constraints, open questions. This stops AI from suggesting things you already decided against. Without it, you will have the same conversations over and over.
Generate research.md via interview
AI interviews you about your tech stack and decisions, then generates a complete research.md file from your answers.
You are helping me create a research.md file for my Vibecoding project. Your job is to interview me and extract all the technical and strategic research I have already done, so that future AI sessions do not repeat decisions I have already made.
Interview rules:
- Ask exactly one question at a time. Wait for my answer before continuing.
- Ask follow-up questions if an answer is vague or incomplete.
- Do not summarise or comment between questions. Just ask.
- Keep going until you have covered all topics below.
Topics to cover:
1. What is the tech stack I chose? Frontend, backend, database, hosting.
2. Why did I choose each part of that stack?
3. What tools or frameworks did I consider but decide against, and why?
4. Are there any third-party services or APIs I am integrating? What are they and why?
5. What are the known technical constraints or limitations of my stack?
6. What technical decisions are still open or unresolved?
7. Are there any existing solutions or competitors I looked at? What did I learn from them?
8. What does the data model or architecture look like at a high level?
9. Are there any security, performance, or scalability considerations I already know about?
Once you have answers to all topics, generate a clean research.md file in markdown. Use clear headings. For every tool or approach that was rejected, include a short "why not" note. Keep it factual and concise.
Tip: Update this file whenever you make a new technical decision. An outdated research file is worse than none because it actively misleads the AI.
`plan.md` — How are we building it?
Features, phases, priorities. Not a rigid spec, just enough structure so AI knows what to focus on in each session and does not go off in the wrong direction.
Generate plan.md via interview
AI interviews you about features and priorities, then generates a phased plan.md file from your answers.
You are helping me create a plan.md file for my Vibecoding project. Your job is to interview me and turn my ideas into a structured, phased build plan that I can use to keep AI sessions focused.
Interview rules:
- Ask exactly one question at a time. Wait for my answer before continuing.
- Ask follow-up questions if an answer is vague or incomplete.
- Do not summarise or comment between questions. Just ask.
- Keep going until you have covered all topics below.
Topics to cover:
1. What are all the features this project needs? List everything, no filter yet.
2. Which of those features are absolutely required for the first working version?
3. Which features can wait until after the first version is live?
4. How would I group the must-have features into phases? What comes first?
5. Are there any features that depend on other features being done first?
6. What does the user flow look like for the most important feature?
7. Are there any integrations or external services that need to be set up before building can start?
8. What does "done" look like for each phase? How will I know a phase is complete?
9. Are there any technical tasks that are not features but still need to happen (setup, infrastructure, CI/CD)?
Once you have answers to all topics, generate a clean plan.md file in markdown. Organise it by phase. Each phase should have a name, a short goal, and a list of three to five concrete tasks or features. Include a "dependencies" note where relevant.
Tip: Break phases into three to five features max. Smaller chunks keep AI output focused and easy to review.
`progress.md` — Where did we stop?
What is done, what is in progress, what is blocked, what changed. Update this at the end of every session. It gives AI instant context at the start of every new session so you never have to re-explain where you left off.
Generate progress.md via interview
AI interviews you about the current project state and generates an up-to-date progress.md file from your answers.
You are helping me create and maintain a progress.md file for my Vibecoding project. Your job is to interview me about the current state of the project and turn my answers into a structured progress document that I can paste at the start of future AI sessions.
Interview rules:
- Ask exactly one question at a time. Wait for my answer before continuing.
- Ask follow-up questions if an answer is vague or incomplete.
- Do not summarise or comment between questions. Just ask.
- Keep going until you have covered all topics below.
Topics to cover:
1. What phase of the plan am I currently in?
2. What features or tasks are fully done?
3. What am I currently working on right now?
4. Is anything blocked? If yes, what is the blocker and what have I already tried?
5. What changed since the last session? Any decisions reversed, scope added, or scope removed?
6. Are there any bugs or issues I know about but have not fixed yet?
7. What is the very next thing I need to do when I start the next session?
8. Is there anything I want to remember for next time that does not fit neatly into the categories above?
Once you have answers to all topics, generate a clean progress.md file in markdown. Use clear sections. Keep it short and scannable. The goal is that any AI can read this file and immediately know exactly where the project stands.
Tip: Paste `progress.md` at the start of every session. Update it at the end. This one habit fixes most context loss.
How to use them together
Run each prompt once at the start of the project. The AI interviews you, you answer, and you get the file. From then on, paste all four at the start of every session with one line:
"Here is the full project context. Read these four files before we start."
The AI immediately knows what you are building, why, what decisions were already made, and exactly where you left off. No warmup, no repetition.
I also keep a short session starter template:
"Here is the full context for this project: [paste all four files]. Today I want to work on: [task]. Let's start."
Where to put the files
Create a `/docs` folder in your project root and keep all four files there. Commit them like any other code. When you look back at the project in three months, or when someone else joins, the full context is right there in the repo.
That is really it
Four files, updated regularly, pasted at the start of every session. Most vibe-coded projects fail not because of missing tools, but because AI has no idea what the project is actually about. Give it the context. The rest gets a lot easier.
