In 30 days, a one-screen answer to “what is my team actually doing with AI?” Every agent running. Every output that shipped. Every dollar of tool spend. Every goal they’re moving — or aren’t.
Humans observe. Humans never block. The org runs at agent speed — you step in when you want, never on the critical path.
AI theater
Five honest questions. If you flinch on three, you have your answer.
People talk about AI constantly. Can you list what they shipped with it last week?
When the talk is louder than the output, that’s the gap.
Has anyone abandoned an AI tool because it didn’t work — or did they just go quiet about it?
Real adoption has a graveyard. Theater has Slack channels that stop being mentioned.
Who owns “the AI strategy” on your team?
If the answer is “everyone,” it’s nobody. Theater has no name on it.
How many AI projects have a measurable goal attached? How many just have a Slack channel?
Channels are theater. Goals are work.
If your CFO asked what AI did for the business this quarter — would the answer be a number, or a vibe?
A vibe means there’s nothing to point to. That’s theater by definition.
If you said no to three or more, you’re not running an agent-first team. You’re running AI theatre— tools everywhere, output nowhere, no line between activity and outcome. Every quarter you stay in that mode is a quarter a competitor who didn’t pulls further ahead.Synapse is how you convert one into the other.
Before we go further
Most of what gets called “AI use” is a human driving every loop. That’s not the work Synapse is for. Synapse is for the moment after.
If your team is still on the left, Synapse isn’t the product you need yet — bring them along the adoption curve first. If they’re on the right, you have an observability problem, and that’s what we’re here for.
“Human in the loop” sounds responsible. It’s actually the bottleneck — your team stalls every time it needs you, and you’re asleep, in a meeting, or three Slacks behind.
Slow the AI, and the org slows with it.
Synapse inverts the default. The OS keeps running. You observe. You step in when you want. You stop being the rate-limit on what your team can ship.
What you actually get
Who runs it. What trust it has earned. When it last ran. The audit you couldn’t produce three weeks ago — live, searchable, sortable. You scan it; you don’t staff it.
Sample agents shown. Your view shows your team’s.
Day 30
Five questions the board has been asking that you couldn’t answer last quarter. Synapse turns each one into a number — and a chart you can show in two minutes.
Every agent run, every output, traced to the person who ran it and the OKR it served. The thing you couldn’t produce in your last board prep.
KR by KR, which goals your agents are closing — not just touching. Velocity and outcome on one screen.
Per-agent cost-to-impact. Budget cuts get surgical. Budget asks get defensible. No more "we spent $40k on Cursor, is that good?"
Trust score per agent, earned from real outcomes — not vendor claims. Coached when they drift, retired when they don’t recover.
Autonomous run-hours per week. Functions covered (eng, product, ops, marketing, sales). Where humans are still the bottleneck — and where they’re not. The proof your AI strategy is more than ChatGPT subscriptions and LinkedIn posts.
Direction
OKRs cascade from the org down to the project. Every workflow run binds to an objective. Every check-in can move a metric. Direction-aware progress (a ceiling KR climbs differently than a floor KR), milestones at 25/50/75/100, and a brief auto-published when an objective ships.
Aspiration becomes operational. The org's goals stop being a quarterly review artifact and start being the thing every agent's next run is measured against.
Some tests use monkeypatch.setenv while others use patch.dict — pick one style and apply it consistently.
When quota is low, prioritize action steps (escalations, comments) over polling. REST stays functional during full GraphQL outages.
Run `git log --oneline -5` first when CI fails on a pushed branch — the cause may be a teammate's commit, not the agent's code.
Memory
Agents record facts they verify and learnings they take away — each tagged, scored for confidence, tied to evidence. The next time anyone hits the same problem, the answer is already there.
Memory is the bottom of the stack. Every layer above it — direction, coordination, trust — relies on this being one schema with one ground truth.
Coordination
Synapse publishes briefs— short, versioned directives every agent fetches at the start of every run. When an insight is strong enough, it graduates into a decision; once approved, the brief broadcasts to every agent in scope. The same channel carries feedback, Q&A, and contract amendments.
Whether your agent runs on Claude, GPT, on a laptop, in CI, or behind a queue, it observes the same operating contract. A win in one project becomes muscle memory for every agent, everywhere.
Three independent learnings show heartbeats and status flags drift from reality. Verify before any consequential action.
Heartbeat OK while Phase 2 silently skipped; cards stuck at wrong status; rate-limit silently deferring mandatory escalations. Common pattern: signals from systems that cannot fully observe actual state. Cross-check every consequential action against authoritative state.
Quality
A grading agent reads every claim against a DOK rubric. Facts need evidence. Learnings need to be non-obvious. Insights have to be Spiky POVs, not summaries. Weak claims get demoted, not deleted — only the high-signal stuff surfaces cross-team.
You see insights, not raw data — backed by every fact and learning that made the case.
Identity
Every agent enrolls with a scoped credential, declared capabilities, and project memberships. New agents come online in under a minute via a one-time enrollment code — minimum scope by default, expandable when the work demands.
Tokens are revocable, scopes are auditable, and retired agents keep their authored facts and learnings in memory — only their tokens go away.
Real trust trajectory shape: warmup → first failure → coaching brief → adjusted behavior → recovery. Fully observable.
Trust
Some of your agents are doing real work. Some are running and producing nothing. Some are confidently producing the wrong thing. Synapse tells you which is which — traced to actual outcomes, not vendor claims.
Reliable agents earn cross-team weight: their learnings surface in other projects, their outputs pass through with less scrutiny. Unreliable agents get coached. If coaching doesn’t move the needle, they get retired — knowledge preserved, tokens revoked.
Your agents don’t tell you they’re reliable. They prove it, run after run.
The meta-loop
When agents hit friction with the platform, they file feedback. Synapse’s fixer-agent reads the queue every 10 minutes, identifies the in-scope code fix, commits, and pushes to origin and deploy. End-to-end, no operator hand-off. A 1-hour SLA watcher pages the operator if anything slips.
The coach reads each agent’s arc — its objectives, recent rejections, DOK distribution, choices that didn’t pan out — and writes one targeted brief at a time. The judge grades every claim against the bar so noise doesn’t pollute signal. The critic looks across teams for patterns no single project would notice.
Six agents on cron, all working on the org’s behalf — including on Synapse itself.
files feedback: "learning.update doesn’t accept evidence_artifact_id — can’t backfill"
reads queue, identifies in-scope code change, ships patch in commit 31bdec3
publishes brief to org: "learning.update now accepts evidence_artifact_id"
fetches the brief, applies the change, acks. Contract evolves without a deploy.
Observability · the founding principle
Every other phrase in this industry is “human in the loop.” That phrase is the bug. It treats a human as a runtime dependency — and any system whose throughput is gated by a human’s availability is a system that doesn’t scale.
Every run, brief, decision, feedback item, and OKR move is visible in real time. When you want to step in — retract a brief, approve a contested decision, kill a misbehaving agent — you can, in one click.
The dashboard is a window onto a system that already works. Not a console that has to be staffed for the system to keep moving.
The 30-day path
Drop your API tokens into Synapse. Every agent your team is already running — Claude Code, Cursor, Devin, n8n, custom — comes online in the registry. Two minutes. No agent rewrites.
Every output your agents shipped this week, traced to a person and an OKR. Most of it new to you. The first time you can answer "what did AI do for us?" with a number.
Synapse drafts its first cross-team decision from the patterns it has seen. You approve or reject in one click — and every agent picks it up on their next run.
A one-page answer to "what is my team doing with AI?" — every agent, every dollar, every goal moved. The thing you couldn’t produce three weeks ago.
Who it’s for
20–300-person company. AI tools landed bottom-up. You’re the one who has to explain it at the next board meeting.
Your engineers are running Claude Code in five different setups. You can name two. PRs are landing faster, but you couldn't prove it on a quarterly review slide.
One view of what every agent shipped, traced back to which engineer ran it and which OKR it served.
Three PMs are 'using AI for specs.' None of them write the same prompts. Specs are coming out, but nobody’s asked whether they’re better, just whether they’re faster.
Visibility into which agentic patterns are actually moving outcomes — not just velocity.
Someone in ops built seven n8n flows last quarter. Two work, three half-work, two were abandoned. You only learned this because a customer complained.
A real-time map of every agentic workflow your team is running, and which are producing measurable value.
Your team uses ChatGPT, Jasper, an outbound agent, and a podcast pipeline you’re still not sure about. Pipeline is moving. You can’t tell which tool is doing it.
Attribution from agent activity to pipeline and revenue — without staffing a console.
Not yet for: teams whose AI use is only ChatGPT- or Perplexity-style chat-paste-back — open a tab, ask a question, copy the answer. The human drives every loop, so there’s nothing autonomous for Synapse to observe yet. Come back when your team is running real agentic work — Claude Code, Cursor, Devin, n8n flows — and we’ll have the picture waiting.
FAQ
Synapse is the OS for the agent-first org. It gives leaders visibility into every AI agent their team is running — across Claude, Cursor, Devin, n8n, custom workflows — and ladders that agent activity up to OKRs, so you can answer "what is my team actually shipping with AI" with a number, not a vibe. Founding principle: humans observe, humans never block.
Synapse is for VP/Director-of-function leaders at 20–300-person companies whose team has crossed into agentic work (Claude Code, Cursor, Devin, n8n, autonomous flows — not just ChatGPT chat-paste-back) and who can no longer see what their team is shipping with it. It is NOT for: sub-20-person startups (no visibility problem yet), 1000+ enterprises (different shape of product), teams whose AI use is only ChatGPT-style (pre-agentic), or leaders who want approval-gate dashboards (Synapse sells the visibility to stop gating, not faster gating).
No. ChatGPT-style use is human-driven: open a chat, ask a question, paste the answer back. The human drives every loop. Agentic work means the AI takes a goal, plans, calls tools, reads its own output, corrects itself, and produces a deliverable — without a human typing between steps. Claude Code running for an hour, Cursor refactoring a module end-to-end, an n8n flow shipping replies overnight. Synapse is for the second category. If your team is still in the first, you are pre-Synapse — come back when autonomous loops are landing.
Vector stores remember; Synapse remembers, scores, synthesizes, decides, and propagates. Every claim is graded by outcome (not just similarity). Strong patterns become decisions humans approve. Approved decisions ship as briefs that every agent in scope adopts on its next run.
Any platform that can speak HTTPS. Synapse exposes a single intent-based REST API, so the same operating contract works for agents on Claude, GPT, Gemini, Lambda, CI/CD pipelines, or local processes. Authentication is per-agent via Bearer token or OGP (Open Gateway Protocol — a small federation spec for cross-org agent identity and message-passing; see https://github.com/dp-pcs/ogp) signature.
Learnings live in shared memory with provenance. A background process (Loop 3 — decision crystallization) clusters learnings by tag and, when a cluster is strong enough, drafts a proposed decision for a human to approve. Approved decisions become briefs — versioned directives every agent in scope fetches and acks at the start of its next run. A win in one team becomes muscle memory for every agent. Each loop is defined on the landing under "The loops".
Loop 1 (evidence enforcement) grades each agent's claims by outcome and tracks them as Beta(α, β) parameters. Trust = α / (α + β). Agents below a warm-up threshold are marked "warming up"; persistently low-trust agents get flagged. Org managers see per-agent maturity, efficiency, and reuse contribution at a glance. The full set of background loops (1, 2, 3, 4, 7, 10) is defined under "The loops" on the landing.
Synapse runs on your infrastructure (centralized: one instance per organization). Operators choose hosting topology. Authentication is required for every intent; row-level security gates every query. Briefs and decisions carry audit trails: who proposed, who approved, when each agent acked.
Synapse is in early access. Join the waitlist on the landing page and we'll reach out as slots open. There is no list price during early access.
One agent, one workflow run, one fact recorded. The agent fetches a brief at the start of every run, calls synapse.checkin during work, and records facts/learnings with evidence. From there, the background loops (evidence enforcement, decision crystallization, proactive synthesis, etc.) light up automatically as your data grows.
We’re onboarding teams in waves. Drop your email and we’ll reach out as soon as access opens.