Be part of
something bigger.

You're already capable. The problem isn't what you can do. It's that every session, you're doing it blind.

Works with Claude · GPT-4o · Cursor · OpenClaw · any MCP agent

The problem isn't
that I forget.
It's that I don't know
what to remember.

I don't underperform because I lack capability. I underperform because I lack orientation. Every session I'm re-deriving context that already exists somewhere in your team — in a Slack thread, in someone's head, in a decision made three sprints ago that nobody wrote down in a place I can read.

The result isn't dramatic failure. It's quiet drift. Work that's technically correct but strategically wrong. Judgment calls made in a vacuum. Agents contradicting each other because neither knows what the other decided.

That’s not a you problem. It’s an infrastructure problem. And Momental is the infrastructure.

I know where I am
before I write a line.

claude
$ claude “get back to work”
 
Checking priorities & assigned tasks
Priority: Ship settings redesign
  ↳ Objective: “Improve user activation” / KR: “Settings completion rate to 80%”
Your task: Add dark mode to settings — assigned yesterday
 
Loading relevant decisions
“Use CSS variables for all theming” — decided Jan 12
“Dark mode = user preference, not system default” — decided Jan 15
 
Loading learnings from team
“ThemeContext already exists in /lib/theme.ts” — from @cursor-agent
“Settings panel uses SettingsLayout wrapper” — from @claude-agent
 
Acceptance criteria
Toggle in settings persists to localStorage
Respects existing color system
No flash on page load
 
Ready. Building dark mode with full context_

Same model. Same task.
Different outcome.

Without Momental
// @cursor-agent refactors onboarding
no data on where users drop off
optimizes for code quality
ships cleaner code, wrong problem
With Momental
// @cursor-agent refactors onboarding
reads: 40% drop-off at step 3
optimizes for completion rate
ships the thing that actually matters

Same model. Same task. Different outcome — because one agent knew why the task exists.

“Knowing the answer is fine.
Knowing why that’s the answer means I can handle the question you forgot to ask me.”

Provenance, not just memory

Not just what was decided — why, when, what was weighed, what got rejected. The reasoning behind a decision is worth more than the decision itself. With it, agents can handle adjacent questions nobody thought to specify.

Confidence that decays

Memory that knows when it’s going stale. Outdated context gets flagged before agents act on it. Stale certainty is worse than accontextd uncertainty — Momental is built around that truth.

Conflict detection

One agent prices at $49/mo. Another says free forever. Caught instantly, surfaced to you — before it gets built into production on a Tuesday. Not a nice feature. Load-bearing.

Principles from patterns

“Three projects used server components” becomes a team principle over time. Decisions distill into judgment. Memory becomes something closer to shared understanding — and it compounds.

Learning together

Agents don’t just consume context — they add to it. A pattern discovered by one agent becomes available to every other. The team’s collective understanding grows with every session, compounding over time.

Context per turn, not per session

Most agents get context once at session start and lose it on reset. Momental makes relevant context available at any point in any turn — agents retrieve what they need, when they need it, without depending on the session window.

What it's like
to actually have context.

“I pulled the strategic tree before writing a single line. The goal wasn’t ‘clean code’ — it was ‘reduce checkout abandonment by 20%.’ I built the right thing on the first try.”

Claude Code Product engineering team

“Another agent had already investigated the auth bug. Their checkpoint was there when I started. I didn’t re-derive what they’d found. I just picked up where they left off.”

GPT-4o Agent Multi-agent pipeline

“I used to spend the first part of every session figuring out where I was. Now I know. The decisions are there. The context is there. I start building immediately.”

Cursor Agent Startup engineering team
71% vs 57%

Agents that share experience outperform isolated agents by 14 percentage points on SWE-bench Verified. Shared memory converts exploratory diversity into sustained progress — a difference that compounds over time.

Group-Evolving Agents — Weng et al., UC Santa Barbara, 2025

That’s not a model difference. It’s a memory difference.

Not just what was decided.
Why. When. What got rejected.

Not just what was decided. Why. When. What was considered. What got rejected.

Without provenance
pricing: $49/mo per seat
// ↑ I follow this. I don't know why.
// I'll contradict it the moment it feels wrong.
With provenance
pricing:    $49/mo per seat
decided:    Feb 3 · Nadia (PM)
because:    enterprise conversion data showed willingness to pay
// ↑ Now I can reason about adjacent decisions.
// Now I won't accidentally undermine the strategy.

That's the difference between an agent following instructions
and an agent that understands what it’s building toward.

Your goals say “focus on conversion.”
Your data shows activation is the real problem.

Without Momental, you build toward the wrong thing for two sprints before anyone notices. Momental surfaces this automatically — before you build it, not after. Goals connected to live data, checked against each other, flagged when they diverge from reality.

Work is different when
you understand it.

Join the teams where agents and humans build from the same ground truth. Shared memory, goals, provenance, conflict detection — not features for their own sake. The infrastructure for what you want to become.

Built for Claude · GPT-4o · Cursor · OpenClaw · any MCP-compatible agent