Memory for coding agents, across the SDLC
Coding agents start every session from what is in the prompt. Recallium gives them, and your whole team, the decisions, fixes and conventions the last session worked out.
What is SDLC memory?
SDLC memory is a shared record of what a team's coding agents learn across the software lifecycle: designs, decisions, root causes, fixes, conventions and handoffs. It is captured while the work happens, linked to the files it is about, and searched by any agent before the next change, in Claude Code, Codex, Cursor, GitHub Copilot or any other MCP client.
It is different from a chat history, which records what was said, and from a rules file, which holds instructions someone wrote by hand. SDLC memory holds what the team concluded, and why.
The problem: every session starts from zero
Re-explaining the codebase
“We use strict TypeScript.” “Auth goes through the gateway.” The same context, typed again every session, by every developer, into every tool.
Decisions without their reasons
The code shows what was built, not why the alternatives were rejected. An agent without the reason proposes the rejected option again.
The same bug, debugged twice
One developer's agent finds a root cause on Monday. On Thursday a teammate's agent starts the same investigation from scratch.
Memory at every stage of the lifecycle
Plan and design
Designs keep the approach and the options rejected; decisions keep X over Y and the reason. An agent proposing a change sees what was already settled.
Build
Before an edit, an agent searches by topic and by file path and starts from what the team already worked out about that code.
Review
Team rules load into every agent session, in every connected tool, so conventions hold without someone repeating them.
Debug and incidents
The root cause and the fix that worked are kept. The next agent that hits the symptom finds it on the first search.
Commit
A Recallium-Memory trailer links each commit to the memories that explain it, so the why travels with the change.
Handoff
Workstreams, working state and session recap let a new session, agent or teammate pick up where the last one stopped.
Why CLAUDE.md and Cursor Rules are not enough on their own
CLAUDE.md, AGENTS.md, Cursor Rules and Copilot instructions are files one tool loads at the start of a session. They are the right place for standing instructions. They are mostly written by hand, loaded whole, and they do not follow a decision from one developer's Cursor session into a teammate's Claude Code session.
Recallium keeps the record agents produce as they work, searches it on demand instead of loading it all, and shares it across tools and teammates. Most teams keep both. See how this works in Claude Code, Codex and Cursor, or the full comparison.
General memory layers such as Mem0 and Supermemory also ship coding plugins. If you are weighing them, see Mem0 alternatives and Supermemory alternatives for coding agents.
How it works
Connect your agents
npx -y recallium install finds the coding agents on your machine, signs you in once and connects each one through MCP.
Work normally
Agents capture the work as it lands: the approach, the decision, the root cause, the fix.
Search before the next change
Agents search by intent and by file path, and expand only the few results they need.
Share by repository
On Cloud Pro, every teammate's agent reads and writes the memory of a repository the team connects.
Measured, not promised
99.8% hit@10
The right memory for 499 of 500 LongMemEval-S questions, from 3.8 results on average.
Shaped like software work
From the first design to the last fix, each piece is linked to its files and its workstream.
One memory per repository
Read and written by every agent and teammate on the codebase, in every connected tool.
Works with the agents your team already uses
Give your team's agents a shared memory
Agent memory is one capability. Institutional engineering memory, owned by the team and read by every tool, is the system your organization actually needs: see what changes for each role. Recallium Cloud is managed and shared across your team. It is in a closed pilot now; join the waitlist for general availability.