Context windows give your AI a conversation. Engram gives it wisdom. You stop re-explaining decisions and get back to building.
The goal is simple: just build. You've learned to live with the workarounds. But there's a better way.
You describe what you want. It builds it. Features ship in minutes. This is what coding is supposed to feel like.
Your AI forgets decisions. Suggests things you rejected. Rewrites code you already fixed. You need to do something.
CLAUDE.md, .cursorrules, system prompts — you start writing instructions for your AI. It helps. But it grows with every session, and you're the one maintaining it.
// helps, but manual →Cleaner folders. Better naming. READMEs in every directory. Good practice — but it doesn't help your AI remember what happened last session.
← good practice, wrong problem //Compacting conversations. Trimming context. Pasting summaries from last session. It keeps things running — but resets every time you start fresh.
// helps within a session →Spec files. Lessons learned. Architecture decision records. Handoff docs between sessions. You've built a whole system around the problem. It's not perfect, but it's yours and it mostly works.
← livable, not solved //Hooks that generate rules files. Scripts that build lessons learned. Automation that creates folder structures and context docs. Clever — but now you're maintaining the automation too.
// automating the wrong layer →Maintaining rules, curating context, bridging sessions — the roles flipped. You're doing the remembering so your AI doesn't have to. That's backwards.
Every workaround you've built is solving the same root problem: LLMs have no memory across sessions. Engram gives them one — automatic, searchable, and smart enough to know when you changed your mind. You go back to building. It handles the remembering.
"Build MDX components for case studies. Respect the color palette."
No rules to write. No summaries to paste. No context to manage. Just code like you did in Session 1 — Engram handles the rest.
You don't call save. You don't write summaries. You don't maintain anything. Engram watches your coding sessions and builds wisdom automatically. Changed from JWT to opaque tokens? Your AI knows. Client said "no stock photos"? Your AI knows. Reversed a decision two sessions ago? Your AI knows that too — and won't bring the old one back.
Download one file. Run it. That's it. No Python. No Docker. No API keys. No server. Everything runs locally on your machine. Your code and decisions never leave.
Engram doesn't dump your entire history into every session. It surfaces only what's relevant to your current work. Ask about pagination? It finds the cursor-based decision from 3 weeks ago. Not the auth discussion from yesterday.
When you reverse a decision, Engram detects the contradiction and automatically supersedes the old entry. Your AI will never suggest JWT again after you switched to opaque tokens. The GSAP library you removed won't appear in handoff docs.
No cloud. No API calls. No data leaving your machine. Your architectural decisions, client feedback, and project knowledge stay exactly where they should — on your machine.
See how two approaches diverge across 10 sessions. By session 7, one developer is writing specs. The other is still shipping.
If any of these sound familiar, you're in the right place.
If you checked 3 or more — you already know you need this.
15-day free trial. No credit card. If it doesn't change how you build, walk away.
Less than what you pay for your AI tool itself. Makes that investment actually compound.
Get back to building. Engram gives your LLM the wisdom to keep up.
Start 15-day free trial →Check your email for your activation codes and setup instructions. Then go build something big.