Mission Control
sandbox · read-only mirrorsWelcome to GTM OS.
The simple version: everything your company knows flows into one brain. The brain runs engines that do the daily work of marketing and sales, around the clock. Your people stop doing the grunt work and start approving, steering and deciding. That is the whole idea.
Two shapes of go to market. Most of what follows is account-led, where you sell to a named list of companies. The volume-led engines sit under their own heading for businesses selling to people at scale, starting with the money layer.
A mix of build and buy. We build a lot, everything that runs on your data and your edge. We buy what we can't build better, then wire it into the same brain.
ONE CONDUCTOR
I'm finally getting my job back and focusing on what's important.
GTM Score
Every account ranked nightly, with the next best move already drafted. One marketer covers the accounts of ten.
GTM ABM · the buying-committee engine
A tiered target list, a stakeholder map per account with the gaps exposed and exec plays like the couriered CEO letter. Enterprise deals worked the way enterprises buy.
GTM Ads · the self-learning ads engine
Bids toward paying customers, refreshes its own creatives, learns from every closed deal. You approve the moves.
GTM Outreach · the self-learning outreach engine
Writes like someone who did two hours of homework, learns from every reply. A human sends every message.
GTM Sales · deals kept honest
Calls coached, deals reviewed nightly for drift, proposals priced inside guardrails. Reps sell, the machine carries the homework.
GTM SEO · GEO
A page factory with a quality gate, plus the play that gets you found in LLM chats when buyers ask ChatGPT who to pick.
Get found in LLM chats
120 real buyer questions tracked across ChatGPT, Perplexity and AI Overviews. Citation share is the new rank.
All the other use cases
Churn warnings, quote configurators, crazy experiments. Anyone asks, the brain specs it, the engineer ships it in two weeks.
Good morning. Here is what matters.
Built for the person who owns the number. One recommendation, four decisions, the headline metrics. Click deeper only when you want the machinery. All numbers are dummy data.
Shift €240/day into brand + retargeting winners before Thursday's promo window
Every source flows in here. One dictionary, one memory, every engine reads from this store. Click any node on the map to trace what feeds it and what it feeds.
GTM Score
Every account scored nightly PLUS the next best step, drafted and queued. No black box, every score explains itself and the whole thing syncs into HubSpot for the people who live there.
Fit and intent are different questions. How well an account resembles the customers you already win is a slow structural fact. Whether anyone there is looking right now is a fast one that decays in days. Blend the two into a single number and you lose the ability to say which of them moved, so this engine keeps them apart and always shows the split.
Scores are a ranking, expect a few percent of nonsense. The self-driving-car rule applies, the rep stays behind the wheel. Something looks wrong? Flag it on the account, wrong twice = the rule changes.
How GTM Score builds a score
Plain English, no black box. Scores are a relative ranking, recalibrated weekly against closed-won and closed-lost deals. The weights live in a sheet the ops lead owns, the engine reads it, nobody hand-sets a number.
How much the account looks like your ideal buyer before anyone lifts a finger. Size, industry, tech stack, region. A perfect-fit company starts with points even at zero activity.
What they actually do. Pricing visits, doc opens, webinar seats, trial activity, reply patterns. Doing beats being, a small account moving fast can outrank a perfect logo that never visits.
Outside signals. Funding rounds, hiring patterns, competitor contract windows, category research. The signals that say a buying window is opening.
Buying intent decays in days, so the score decays with it. Today beats yesterday beats last week.
HOT 85+ · act this week. WARM 65-84 · work the plan. COLD under 65 · nurture watches, reps spend zero time. Every score shows its evidence, hover any row in the list.
RUNNING TOTAL · DECAY + CAPSUnder the hood the score is a running total per account. Every signal ages out on a decay curve and every signal type has a cap, so one noisy topic can never dominate an account’s score. Twelve pricing-page hits stop counting once the cap is reached, the next point has to come from a different kind of evidence.
THE VERIFICATION GATEA story must name the account or it goes to a review list, never to a seller. A wrong name in a rep’s queue costs more trust than an empty slot, so the ambiguous ones wait for a human match.
WHAT DOES NOT FEED THE SCORECompany grade and raw size. Those live in the GRADE (A to E, human can override it in the CRM), so a small account moving fast can outrank a big logo doing nothing. And the CRM's own predictive score is ignored, one black box is enough to distrust.
HOW THE MODEL EARNS TRUSTReps flag anything wrong on the account itself (the ⚑ button), flags feed a Friday rules review, wrong twice = the rule changes. Every quarter the win-loss analysis reweighs the factors against what actually closed. And the pilot question never changes: are the people using this list selling more than the people who aren't? The feedback loop reads task closure, actioned, open or no touch, which only works if the team closes tasks, we say that out loud.
Flag Helios Payments
Granular beats general. One flag on one account teaches the engine more than a paragraph in a channel. Pick what's wrong:
Flags land in the ops queue with the full score evidence attached. Reviewed every Friday. If the same rule is wrong twice, the rule changes and you'll see the change noted in the model card.
Helios Payments
Draft attached in the buyer’s language. Due today. Created automatically from the nightly score run, cancel window honored.
Pricing page x4 this week, CFO office opened the security docs, champion quiet 9 days. Full factor breakdown in the GTM OS record link.
GTM ABM
Enterprise deals are won by committees, so this engine works the whole committee. A tiered target list, a stakeholder map per account with the gaps exposed and plays matched to how big companies actually buy. The score decides who is warm, this decides how you surround them.
Large purchases are made by groups, with the size of the group tracking the size of the deal. The same finding turns up across every large study of enterprise buying: deals that close carry more people on both sides of the table. Deals that stall have one contact quietly carrying everything. So the unit of work here is the committee rather than the lead, which means a missing role counts as a real gap.
Ranked by account intent. Click an account, the right side becomes its war room.
GTM Account Lists
Every target account sits in one of three lists with a written entry gate. The engine counts who moved this week, refuses a promotion that has no evidence behind it and drafts the next touch as the excuse for the one after. The score says who is warm. This says what state the relationship is actually in.
An account list behaves like a state machine. Each list has an entry condition somebody wrote down, so moving an account becomes a decision with evidence attached rather than a feeling on a Monday. Promotion asks for proof. Demotion only asks for time to pass, because attention is the scarce resource and an account nobody has touched is already demoted in practice.
The three lists
Fit, warming, focus. An account is in exactly one. The gate between each is written down, so a promotion is a decision with evidence attached. Nobody moves an account on a feeling.
Pick an account
30sAccount velocity
Moves between lists, per week. Every bar is a count of accounts that changed state.
Measured against your own last quarter in the same window. No published benchmark sits here, because the only comparison that survives a board meeting is the one taken off your own data.
Program goals
Every account carries a program. Each program is measured on its own things. Three of the four are easier than net new and almost nobody runs them.
Net new covers warming and focus. Acceleration is open deals that stalled, so it lives in the deal journey and never on this board. Expansion and renewal sit outside the 412 target accounts because those companies already buy from you.
Clusters, computed from won and lost deals
A cluster is a set of accounts sharing a use case and a challenge, regardless of industry. Built from 18 months of deals, both sides. The loss side is what stops you leading with the wrong one. Win rate is measured on the 1,267 deals of 1,412 where a cluster was assignable, so an unassignable deal never quietly improves the number.
| CLUSTER | ACCOUNTS | MEDIAN ACV | WIN RATE | CYCLE | CASES | VERDICT |
|---|
The vetoes
Patterns the lost deals share, turned into rules that stop outreach before it starts. A veto is a hard stop. A strong score never gets a vote on it. Each one is a verified signal with evidence attached.
Touch ledger
Every touch per account, counted against what your own won deals needed. The accounts that got dropped early are named.
| ACCOUNT | TOUCHES 12MO | LAST | NEXT PLANNED |
|---|
Two tracks run at once. The time track fires on a calendar, the signal track fires on verified buying signals. The cap is two touches per contact per week, so the tracks never collide.
Last night
What the engine did while nobody was watching.
GTM Market State
Most target accounts are between decisions. The engine dates the next one from your own contract history, routes each account to the message its date allows and keeps a ledger of who you actually lose to. The score says who is warm. The list says what state the relationship is in. This says when the buying decision happens.
At any moment most of a category is not buying anything. The share that is in market is roughly three months divided by how long a customer stays between decisions, which makes it arithmetic on your own contracts rather than a number worth borrowing from somebody else's category. That single calculation splits the work in two: a small group you can sell to today, plus a much larger group who will only recognise you later if you were present before they started looking.
The in-market rate, computed
Three months divided by how long a customer stays before the next decision. The formula is not the argument. The interval is, so use the one in your own contracts.
Median contract term across 186 customers with a start and end date on record. About one account in eight is facing a decision in any given quarter.
The version most people quote assumes a five-year gap between decisions. Run the identical arithmetic on your own two-year term and it doubles and a half. Borrowing the figure instead of the method understates your addressable quarter by that same factor.
Computed from your own contracts once at least 50 customers carry both dates. Until then the engine says so and falls back, rather than quietly using someone else's category.
market:
in_market_rate: computed # 3 / median_term_months
source: won deals with contract_start and contract_end
customers_with_dates: 186
median_term_months: 24
fallback:
assume: 0.05
until_customers_with_dates: 50
The re-entry calendar
When each dated account faces its next decision. The engine works backward from here, so a first vendor touch lands 90 days ahead of the date rather than on the week somebody remembers.
12.5% of 412 is 52 accounts facing a decision this quarter. 27 are visible, because 281 accounts carry no date at all. The other 25 are deciding right now behind a blank field, which is the whole argument for the research track.
A contract end is when a decision becomes possible, never proof that one happens. Most renewals roll. The content track is what raises the share that actually evaluates. The ledger measures whether it worked, because 471 of 1,003 losses chose nothing at all.
Route by date
Pick an account. The engine decides which track it is allowed on from the date. It refuses the vendor pitch when the date says the decision is far away or unknown.
This rule binds the 412 named accounts. The cold lane in Outreach works companies that have never been on a list. A reply is how one of them earns a date and a place here.
Who you actually compete with
Built from what buyers said was on the shortlist across 1,412 closed deals, won and lost. Doing nothing is a row like any other. It is never absent.
| ALTERNATIVE | ON THE SHORTLIST | SHARE | LOST TO | WON FROM | VERDICT |
|---|---|---|---|---|---|
| Doing nothing the default row, present on every deal | 1,412 | 100% | 471 | 50 | THE REAL RIVAL |
| Northwind Ledger named in definitions.yaml | 388 | 27.5% | 241 | 118 | ALTERNATIVE |
| Cadence Fiscal named in definitions.yaml | 296 | 21.0% | 172 | 79 | ALTERNATIVE |
| Spreadsheet plus in-house build absent from definitions.yaml | 252 | 17.8% | 84 | 151 | ADD TO DEFINITIONS |
| Verity Close named in definitions.yaml | 41 | 2.9% | 23 | 9 | HORIZON |
| Orlin Systems named in definitions.yaml | 14 | 1.0% | 12 | 2 | HORIZON |
Value themes, proven by wins
Every closed-won carries a reason and one theme. A theme nobody cited in a win is a theme you are guessing at.
The account lists engine parked the multi-entity cluster on its own arithmetic, 16% win rate over a 286-day cycle. The win reasons agree with it from a different direction.
Last night
The whole engine is one pass over deals and contracts, then a write of two columns.
GTM Ads
The console optimizes toward paying customers with their revenue attached. Every move ships with its reasoning and waits for your yes.
Every ad platform reports on itself, crediting the last thing it can see. Add the reports together and they claim more revenue than the business actually made. The honest question is incremental: if this channel went dark tomorrow, would that money still arrive. So budget moves here are judged against closed revenue sitting in your own warehouse, never against what a platform says about its own work.
| CHANNEL | SPEND | CUSTOMERS | REAL CAC | REVENUE |
|---|---|---|---|---|
| Search · brand | €8.2k | 71 | €89 | €3.4M |
| Search · generic | €96k | 40 | €2,410 | €4.8M |
| PMax · catalog | €28k | 13 | €2,190 | €0.9M |
| Social · prospecting | €22k | 24 | €917 | €1.1M |
The old dashboard showed platform CPA €270 and called generic search the winner. Real CAC tells the opposite story.
Mechanical moves inside agreed guardrails run alone and get logged in the night log. Anything that moves money, kills spend or changes strategy lands here first.
| PLATFORM | SPEND · MO | REAL CAC | 7-DAY TREND | VERDICT | NEXT |
|---|---|---|---|---|---|
| GGoogle Search | €104k | €1,180 | FIX | cap generic, protect brand | |
| ∞Meta | €22k | €917 | SCALE | lookalike seeded from closed customers | |
| PPMax · catalog | €28k | €2,190 | FIX | kill segments with zero closed revenue | |
| RReddit | €4k | €640 | TEST | the unowned conversation, probe live | |
| ♪TikTok | €6k | €1,480 | HOLD | creator test, verdict in 4 days |
Trend bars show customers per day, so a rising bar means the platform earns more budget. Verdicts refresh nightly with the rescore.
Optimization finds the local peak. These are the campaigns that move the whole curve, each one probes at €1k with pre-registered kill criteria before it scales to €4k.
Chat-first ad funnel
Your market lives in chat. Send clicks straight into a concierge conversation, skip the landing page entirely.
Trend front-running
FX rates, weather, events and competitor moves feed the engine. When signals stack on a category that converts, a campaign is drafted before the spike peaks.
Customer UGC army
Your best-converting format is a real customer talking. Generate one testimonial per region, per vertical, per objection, no film crew.
True-conversion feedback loop
Feed closed customers and their revenue back to the ad platforms as the conversion event, so the bidding algorithms chase buyers instead of form fills.
The brain drafts angles from the attribute learnings. Claims to press, hooks to retry, formats to skip.
▸ drafting gen-8 angle fileVariants inside brand rules. Statics, motion, avatar testimonial videos. A batch in an afternoon.
▸ 12 variants renderingSmall batches, one variable each, capped spend. Clean reads without upsetting the algorithm.
▸ 6 in market · €40 cap eachOvernight, on real customers. Winners scale, losers die fast, fatigue gets caught early.
▸ 2 scaled · 2 killed tonightEvery verdict is decomposed into attributes. The lift table updates, the brain gets smarter.
▸ 3 attribute updates writtenEvery learning is an attribute with a sample size. The lift is measured on closed customers, so "videos work" becomes a number.
Day 13 of 14. CTR is off its peak, the gen-7 successors are already in test. The handover happens before the decay hurts.
Every render inherits the learning library, price-difference hooks + problem-first openers are already in the prompt. Nothing goes live from here, assets land on the platforms as paused drafts.
Testing 6 variants…
GTM Unit Economics
One money number, the orders that ladder to it, and how much more each channel can absorb before a customer gets expensive. Built for businesses that sell to people at volume.
Revenue is the wrong unit.
Where the miss came from
How much more each channel can take
Cost of a new customer fitted against monthly spend, per channel, on the range each has actually run. The number on the right is how much more you can spend in a month before a new customer costs a euro more.
| CHANNEL | SPEND RANGE SEEN | COST OF A NEW CUSTOMER | ROOM |
|---|
GTM Outreach
The outbound cockpit. The engine builds its own cold lists, wakes up the leads already in your CRM and runs everyone through one multichannel sequence, email, LinkedIn and WhatsApp, through rails like Instantly and HeyReach. A human still sends every message that matters.
Two things decide whether outbound works. Neither of them is the writing. The first is relevance, which really means having a reason you are contacting somebody this week rather than any other week. The second is whether the message arrives at all, which comes down to published thresholds a machine checks more reliably than a person. A signal with no play wired to it is just a notification, so every trigger here carries its message before it is switched on.
~150 new companies a day discovered from intent signals, enriched, verified and scored before a single send. Cold fills most of the daily sending capacity.
Conference contacts and old opportunities get watched for fresh activity. The cheapest pipeline you own is the list you already paid to build.
The rule under the score: missing data never zeroes a lead. Score what you can measure, report a confidence percentage next to it.
~7,600 one-off researched emails. Heavy cost, flat reply rate. The homework nobody asked for.
3 variants per block, {{keyword}} + {{company}} injected, follow-up does the math for them. Research moved downstream, to repliers only.
Personalization only counts when it touches the problem you solve. The rest is an attention hack. Buyers smell it.
The test for every tool on this wall: does it own data or access you can’t rebuild? Then it’s a rail, wire it in. The intelligence layer above the rails is the part you own.
How the sending machine is built
| SENDER DOMAIN | BOXES | WARMUP | SENDS/DAY | REPLY | BOUNCE | |
|---|---|---|---|---|---|---|
| get-acme.com | 6 | 420 | 14.2% | 0.3% | ||
| try-acme.io | 6 | 390 | 12.8% | 0.4% | ||
| acme-hq.com | 4 | 310 | 9.1% | 0.6% | ||
| meet-acme.co | 4 | 180 | 7.4% | 0.5% | ||
| acme-team.net | 4 | 150 | warming | 0.2% |
24 mailboxes across 5 domains, rotated automatically. Spam-rate ceiling 0.1%, one breach pulls the domain for 14 days. The engine slows itself down before any platform has to.
What goes out · today's 1,450
The pre-send gate
| CHECK | MEASURED | THRESHOLD | WHOSE RULE | |
|---|---|---|---|---|
| SPF and DKIM both passon every sending domain, checked live | 5 of 5 | both must pass | Microsoft, 550 5.7.515 | PASS |
| SPF stays inside the DNS lookup limita record over the limit returns permerror, which breaks DMARC alignment | max 7 | 10 terms | RFC 7208 §4.6.4 | PASS |
| DMARC published and alignedSPF or DKIM must align with the From domain | 5 of 5 | p=none minimum | Microsoft, 550 5.7.515 | PASS |
| One-click unsubscribe headers presentList-Unsubscribe plus List-Unsubscribe-Post | 1,450 of 1,450 | both headers | RFC 8058, required by Google | PASS |
| Daily volume to one consumer providerpast this line the enhanced sender rules bind | 623 to Gmail | 5,000 a day | Google and Microsoft | PASS |
| Spam complaint rate, trailing 7 daysthe ceiling is the one that ends a domain | 0.04% | below 0.10%, never 0.30% | PASS | |
| Messages per user per daythe platform limit, well above anything we send | max 77.5 | 2,000 a day | Google Workspace | PASS |
| The primary domain never sendsacme.com carries the invoices and the password resets | 0 sends | 0 | POLICY | PASS |
| Sends per mailbox per daypublished vendor guidance runs from 30 to 150, so this is a setting | max 77.5 | 80 | POLICY | PASS |
| Mailboxes per sending domainone bad address drags the others on the same domain | max 6 | 6 | POLICY | PASS |
| Warmup score before cold volume | 90 | POLICY | CAPPED | |
| Volume growth, day over dayacme-team.net asked for 220 tomorrow against 150 today | +46.7% | 20% | POLICY | HELD |
| Bounce rate, trailing 7 daysthe earliest sign a list has gone stale | max 0.6% | 2% | POLICY | PASS |
| Reply rate per domain, trailing 7 dayswarming domains are excluded until they send cold | min 7.4% | 1% | POLICY | PASS |
Met at a conference in May, quiet for 90 days. This week he opened the integration guide twice. The lead woke itself up.
Re-open with the pain he named himself at the booth, AI agents reasoning over stale project docs.
A 60-engineer platform team cut new-hire ramp-up 40% once project knowledge stayed current on its own.
Engineer to engineer. Short, concrete, zero marketing.
Email first, he answers email. The LinkedIn touch waits 48h and only fires if this thread stays quiet.
Subject
The quiet win is the "no" row. Suppression is honored everywhere, so nobody gets step 4 after they said stop.
| ACCOUNT | ANGLE | OWNER | STATE |
|---|---|---|---|
| Helios Payments | champion re-engage · ROI one-pager | Sarah | READY |
| Nordwind Logistics | new CMO · first-90-days opener | Sarah | READY |
| Cobalt Systems | renewal window · migration path | Daniel | IN REVIEW |
| Vanta Retail | webinar trio · working session | Daniel | IN REVIEW |
| Meridian Foods | trial activation nudge | Ana | SENT 09:12 |
GTM Sales
Every call heard, every deal reviewed, every proposal priced inside the guardrails. The engine coaches the humans and keeps the deals honest. Reps sell, the machine carries the homework.
A deal review is usually an argument about optimism. It gets shorter when qualification is a set of fields rather than a feeling: who controls the budget, what happens to them if nothing changes, what has to be true internally before anyone can sign. The most common competitor in any pipeline is the decision to do nothing, so it is carried as a named row here and never quietly left off the list.
Transcripts land within the hour. Sentiment and moment tags are model output, wrong sometimes, the audio link is one click away when a tag looks off.
Send the recap
Call intelligence · this morning's cards
| DEAL | STAGE | SIZE | CLOSES | DRIFT | OWNER |
|---|
Flags are hypotheses with evidence attached, expect a few percent of nonsense. A rep can dismiss any flag with one line of why, dismissals feed the Friday rules review.
Deal review · needs a decision today
TL;DR
The manager stays the coach. The engine brings the receipts, picks the clips and keeps the score, the actual conversation on Friday is human to human.
Battle cards · auto-updated
What changed this week · and from which call
Edits from calls wait 24h in a review queue before going live. One misheard quote on a card costs more than a day of delay.
Proposal workbench
Pricing recommender
Anchored on 3 comparable closed deals in the segment. 8% discount available inside guardrails IF traded for the case-study right. Below €7,900 this deal needs the CRO's yes, the engine will route it there automatically. CONFIDENCE 86%
The recommender advises, the floor decides. In 6 months it has been overruled 14 times, 11 of those overrules closed. Both numbers stay on this page.
GTM Lifecycle
The CRM that runs itself. Every contact sits in a journey, every journey watches behaviour, the right message leaves at the right moment. Templates get approved once by a human, then the machine holds the rhythm around the clock.
Not all churn is worth preventing. Separating the customers you wanted to keep from the ones who were never a fit changes both the number and what you do about it. The second finding underneath this engine is about timing: a message that reacts to something a person just did outperforms a scheduled one sent to everybody, which is why journeys here watch behaviour instead of a calendar.
Every journey keeps a 10% holdout forever. Lift you can defend beats lift you can claim.
| COHORT | ACCOUNTS | WAVE STATUS | RECOVERED |
|---|---|---|---|
| Churned April | 38 | WAVE 1 SENT | 4 |
| Churned May | 29 | WAVE 2 DRAFTED | · |
| Churned June | 33 | WAITING FOR DAY 90 | · |
| Older cohorts | 104 | QUARTERLY TOUCH | 7 |
Win-back economics get audited too. A recovered account that churns again in 90 days counts against the wave.
Cancel reasons come from offboarding calls plus the exit survey. Where the reason is unknown the draft says less, guessing in a winback email reads worse than silence.
+9% opens carried through to +4% activation on 840 signups. Rolled to 100% on day 22.
Converted +11% short term, the saved accounts churned at 2.1x by month 3. Kill criterion caught it at day 45.
Day 12 of 30 · booking rate 1.4x control so far, sample still thin. Kill line sits at 1.2x.
Day 5 of 21 · early invites +23%, too early to celebrate. Kill line sits at +15%.
No separation after 200 sends per arm. Closed at the pre-agreed sample, plain stays.
GTM SEO · GEO
One factory, two fronts. Pages that rank in search, answers that get cited by the AI engines your buyers now ask first.
Keyword research lives inside this engine, demand mapping is step one of the same loop.
Search and AI answers reward different things. A page ranks on relevance and authority. An answer gets cited when a machine can parse it, attribute it and trust the source. The overlap is real but partial, so the factory writes for both and measures them separately. Underneath both sits an older finding that has survived every change in the channel: most people choose from the options they already recognised before they searched.
And some pages ship with zero search volume on purpose. They exist for sales enablement and AI citations, two jobs the volume number never sees.
| PAGE | TYPE | STAGE |
|---|---|---|
| /best-demand-forecasting-tools-2026/ | listicle · MOFU | DRAFTING |
| /compare/meridian-vs-legacycore/ | comparison · BOFU | DRAFTING |
| /alternatives/spreadsheet-forecasting/ | alternatives · BOFU | QA GATE |
| /glossary/net-revenue-retention/ | glossary · TOFU | QA GATE |
| /tools/roi-calculator/ | free tool | PUBLISHED |
| /state-of-b2b-buying-2026/ | original research | PUBLISHED |
Every money page gets two touches a month, no exceptions. A page that misses two slots in a row gets escalated to the fix queue.
One prompt fans out into ~5 hidden queries per run, so the engine tracks whole narratives.
| GPTBot | 214 fetches | reading the comparison pages |
| PerplexityBot | 96 fetches | deep on the research report |
| ClaudeBot | 122 fetches | glossary + pricing pages |
Listicles draw about 44% of AI citations. Owning ours is half the play, appearing in everyone else's is the other half.
84 to 90% of citations point off-domain. Off-domain is where authority lives, so the engine earns it deliberately instead of waiting for luck.
The factory queue · this week
| CLUSTER | PAGES | STAGE | NEXT |
|---|---|---|---|
| pricing comparisons | 24 | QA GATE | your approve |
| migration guides | 12 | PUBLISHING | 6h rollout |
| glossary · long tail | 48 | DRAFTING | QA Fri |
| listicles · GEO bait | 8 | INDEXED | citation sweep 14:00 |
| alternatives pages | 16 | REFRESH DUE | 2x monthly cycle |
Citation share · by engine
Listicles earn ≈44% of all citations, comparisons 27%. The gap engine drafts a fix for every lost prompt, fed straight back into the factory queue on the left.
Keyword Research
Where demand actually lives. Search Console tells the engine what you already own, the rank tools tell it what you are missing. The factory builds from both.
Not every search is the same kind of demand. Somebody typing your category name has already decided the category is the answer, so they are now choosing between vendors. Somebody describing a problem has not got there yet. The gap between those two states is where most of the winnable volume sits. It is usually the part nobody on the team has written for, because it does not look like a buying query.
| QUERY | CLICKS | IMPR | CTR | POS |
|---|---|---|---|---|
| demand forecasting software | 4,812 | 88.4k | 5.4% | 2.1 |
| meridian vs legacycore | 2,904 | 31.0k | 9.4% | 1.2 |
| net revenue retention formula | 2,211 | 64.7k | 3.4% | 3.8 |
| roi calculator forecasting | 1,688 | 22.9k | 7.4% | 1.9 |
| best forecasting tools 2026 | 1,342 | 58.1k | 2.3% | 6.7 |
| CLUSTER | INTENT | VOL/MO | STATUS |
|---|---|---|---|
| brand + comparisons | BOFU | 12.4k | OWNED · #1 |
| category head terms | MOFU | 33.1k | RANKING · P4 |
| alternatives to incumbents | BOFU | 6.2k | RANKING · P3 |
| glossary + definitions | TOFU | 41.8k | OWNED · #1-3 |
| industry x use case | MOFU | 18.9k | GAP · QUEUED |
| pricing + cost questions | BOFU | 9.7k | GAP · QUEUED |
TOFU brings readers, MOFU brings evaluators, BOFU brings buyers. The factory builds BOFU gaps first, the money pages.
Prediction is a bet. The engine drafts outlines early, the factory only commits pages once a predicted query shows real impressions at striking distance.
GTM Content
Everything your team posts, sends or hands to a rep, drafted from what the pipeline is saying, in a voice you wrote down once, with every claim carrying its source.
Pages that rank and answers that get cited live next door in Engine 04. This engine ships assets to people.
Two things make content trustworthy at scale. Both are boring. The first is that every claim traces to something real, carrying the date it was checked plus the day it stops being true. The second is that voice lives as written rules rather than as example documents, because a rule can be enforced by a machine while an example can only be imitated. The third, smaller finding: assets built around one idea consistently beat assets carrying five.
It is one function, content.lint(text). This prototype runs it inside this engine.
Off the shelf, brand voice is a style guide that one tool enforces on its own output. Here it is a rule set every engine reads, tied to the claims library. It prints the reason when it blocks.
A model with no ledger behind it will invent a number sooner or later. The ledger is the fix. A better model is not. One refresh in this table updates every asset that quotes it.
The blocker is the role most often left with nothing and the one most often named in a lost reason. The map shows the hole weeks before the deal does.
Eleven source moments produced all 86 assets this month. The engine never starts from a blank page.
Pricing. Security. Compliance. Anything naming a customer. Anything naming a competitor. A new claim entering the library. Public replies and comments.
An outreach mistake costs one relationship. A content mistake is one to many and stays indexed. The engine's job is to make the human click take nine minutes instead of an hour. The click stays.
Names show only where a consent basis is on file. Everything else rolls up to the role.
Sales content lockers join what a rep sent to the opportunity. Nothing joins the post, the newsletter and the rep’s send into one committee view. Nothing draws the roles that have opened nothing at all. That is the job this section does.
GTM Localization
Every asset a rep hands over in another market is a translation of a claim. The engine renders each variant under that market’s written rulebook, re-checks every claim per market nightly and holds the variant the moment a claim behind it dies.
Translating a sentence and being allowed to say it are two different problems. A number that is true everywhere may only be sayable in the markets where somebody actually signed off on it. A translation stays perfect right up until the source it came from changes underneath it. So the rulebook for each market is written once by a person who knows that market, then the engine re-checks the claims under every variant every night.
The shelf
Every cover is one asset in one market. Held first, then never rendered, then current. A shelf that only showed the good ones would be a gallery.
No rulebook for es-ES
Spain is in scope in definitions.yaml with an empty block, so the engine renders nothing here and says so. A rulebook is five keys a person in the market writes once. The engine never invents a register.
registerterminologykeep_in_sourcenumbersclaimsPick a cover
Held, with the reason
Four reasons, all computed. A held variant is never deleted, because the fix is usually one claim away.
Last night
Runs after the content engine writes, so it always checks the newest source.
Reporting
Numbers reconciled against the warehouse every morning. The report drafts itself, a human signs it before anyone else sees it.
The CFO asked for CAC by segment again, mid-market versus enterprise. Second time this quarter.
Noted. CAC by segment added as a standing section, every future pack carries it. First appearance in the August draft.
The manual version of this took the team 2 to 3 days a week. Pull the analytics tool into a spreadsheet, pull each ad platform into the same spreadsheet, reconcile by hand, rebuild the deck. The engine does the pulling and the reconciling. People keep the judgment calls.
Every number traces to a warehouse query. Click any figure in the real product to see its source.
Chat with the brain
Ask in plain language. Answers come from your warehouse and your CRM, with the sources attached. If the brain does not know, it says so.
Every answer cites its query. The brain reads from read-only mirrors, it cannot touch production.
Second Brain
Everything the company knows, in one place the agents can read. dozens of sources across four tiers, clean data underneath, shared definitions on top, know-how beside it.
Day one, every table counted against its source. Incomplete mirrors make confident dashboards wrong, so this runs before anything scores. The two amber tables carry a backfill job and the engines ignore them until they clear.
The tiles above are the live feeds with their numbers. The map is the point, one brain reads all of it, so a funding round, a pricing visit + a rival's job post become one picture of one account.
Every agent and every report uses the same math. When "customer" means one thing, the numbers stop arguing with each other.
The ads engine bids on CUSTOMER. The old setup bid on LEAD. That one change explains most of the CAC story.
Data Explorer
The modeled tables under every engine. Read-only mirrors, production stays untouched.
from ad_spend_daily join campaign_customers using (campaign_id)
where closed_at >= date_trunc('quarter', now())
group by 1 order by 2;
| CHANNEL | REAL_CAC |
|---|
This is the exact query behind the GTM Ads reallocation card. Every number in the OS traces back to a table you can open here.
CRM Cleanup
Most bad CRM data is inconsistent rather than missing. One real value shows up under a dozen spellings, which is why fill rate looks healthy while the reporting built on top of it does not. That also explains why cleaning a database once achieves very little. Without a rule at the point of entry the same drift returns within a quarter, so the fix here is a written rule plus a nightly check rather than a one-off project.
Duplicates, collisions and dead records, found nightly, merged only after a human says yes. Every ruling you make teaches the engine your rules.
Cleanup jobs
refresh the read-only copy from the CRM
rebuild the shared-signal pair analysis
company dedup keyed on the VAT registry id
the evening batch, fully reversible for 30 days
Collision pairs · found last night
| SIGNAL SHARED | RECORDS | ENGINE'S READ | |
|---|---|---|---|
| +31 6 ••• 4471 | 2 contacts, same surname | LIKELY SAME PERSON | merge queue |
| +31 20 ••• 900 | 6 contacts, one company | OFFICE SWITCHBOARD | keep all |
| ops@vanta-retail.com | 2 contacts, names differ | UNCLEAR · ASK A HUMAN | review |
| VAT NL8522••••B01 | 3 companies, 1 parent | BRANCHES → ROLL UP | merge queue |
| +49 30 ••• 118 | 2 contacts, colleagues | SHARED LINE | keep all |
Numbers on more than 5 records count as switchboards and are excluded automatically. Companies merge on the VAT registry id, never on website, marketplaces share those.
Merge rehearsal · 1 of 41 queued
CONFIDENCE 96%Same phone once formats are canonicalized, same surname, the gmail is the older personal address. The survivor keeps the work email, the gmail moves to the secondary field, activity history merges.
Stage gates
A stage is a claim about a deal. Five fields have to exist before a deal can be called an opportunity, so the forecast stops inheriting whatever a rep dragged into the column on a Friday.
An override is allowed and logged as one, with the name of whoever signed it. The forecast then shows the deal with a flag on it, so nobody reads it as qualified.
MCP Servers
The sockets the agents plug into. Each connection is scoped, logged and read-only unless a human approval sits in front of the write.
Reads are free, writes wait for a yes. Every tool call lands in the audit log with who asked, what ran and what came back. Access Control decides which agents see which sockets.
Access Control
Who sees what, who may approve what. This is the part that turns a clever demo into something a real company can run.
| CAPABILITY | REP | LEAD | OPERATOR | ENGINEER | EXEC |
|---|---|---|---|---|---|
| See scores · own accounts | ✓ | ✓ | ✓ | ✓ | ✓ |
| See scores · all accounts | · | ✓ | ✓ | ✓ | ✓ |
| Send outreach drafts | ✓ | ✓ | · | · | · |
| Approve budget moves | · | ≤ €500/d | ✓ | · | · |
| Approve page batches | · | · | ✓ | ✓ | · |
| Edit playbooks + prompts | · | · | ✓ | ✓ | · |
| Change connections + scopes | · | · | · | ✓ | · |
| Read every report | · | ✓ | ✓ | ✓ | ✓ |
The outreach agent has scopes: crm.read, web.read, email.draft. Billing is structurally out of reach. Push on it.
Crazy Ideas
The brain reads everything you feed it, then asks what if. Ideas beyond optimization, each one cheap to test, each one with a kill switch agreed before a euro moves.
Concierge chat funnel
Send paid clicks straight into a live concierge conversation. Skip the form, skip the landing page, qualify in the thread.
Trend front-running
Watch FX, weather, events and competitor moves. When signals stack on a category that converts, draft the campaign before the wave peaks.
Renewal-window sniper
A dedicated always-on motion for switching-window accounts. Migration-path content, peer proof, no discounts until legal is in the room.
The wildcard campaign
Mix the audiences, break the structure the playbook says you need, let the algorithm find a pocket nobody targeted on purpose.
Customer-as-creator army
Generate one testimonial per region, per vertical, per objection. Real customer stories, no film crew, refreshed before fatigue hits.
Free-tool magnet blitz
Ship a small interactive tool per buying question (pricing, sizing, benchmarks). Tools get linked, cited and remembered long after posts fade.
Own the "State of X" report
Publish the definitive annual benchmark from your own anonymized data. Every stat becomes a quotable line the AI engines repeat with your name on it.
Conference-week surge
A geo-targeted, time-boxed burst around each event. Custom pages, outreach angles and ads that only exist for those ten days.
Send prospects the forecast
Push the demand forecast TO your prospects. "Your category spikes in 5 weeks, here is the data." Be the vendor who told them before it happened.
GTM Simulator
Simulate your GTM before you run it live. The simulator starts from what the OS already knows, your connected sources and the motions you have run so far, then ranks 145 plays from real builds and sequences a 90-day plan sized to the hours you actually have. Clone a scenario, change one input, compare the arms side by side. Every plan starts in dry mode and everything below is a suggestion, you decide what actually runs. Or scroll down, describe what you wish existed in one sentence, the brain drafts the spec on the spot.
named accounts carry the pipeline, reps close
7 engines live in this workspace
nightly account ranking, two outbound lanes, budget shifts behind the gate
CRM · ads · product analytics · billing · calls · search console + the rest of the connected stack
Demo workspace, sample sources. In an install this state loads from your live mirrors and every motion the OS has already run.
Most teams run one or two. Pick what is true today.
The plan is sized to the hours you actually have, an honest number beats an ambitious one.
The ranking runs on encoded practitioner heuristics. Impact and ease are scored from 20+ real builds, the PROVEN flag is earned by plays that keep getting picked as first builds across implementations. The base state above comes from this demo workspace's sample sources. In an install it reads your live mirrors, with every play that runs reporting its outcome back so the simulator re-ranks on your numbers instead of the community prior. Nothing here executes anything, every plan starts in dry mode.
"I want to know which customers are about to churn." That sentence is the whole request.
Data needed, where it lives, who approves the outputs, build estimate. If the data is missing, it says so before anyone builds anything.
Two weeks in the sandbox, behind the same human gate as everything else. Used = hardened. Ignored = retired, cheaply.
Type your own wish above or
| APP | ASKED BY | VOTES | STATUS |
|---|---|---|---|
| Churn early-warning | Customer success | BUILDING | |
| Quote configurator | Sales | SHIPPED | |
| Partner co-sell finder | Partnerships | SCOPING | |
| Competitor price watch | Product marketing | BACKLOG | |
| Event lead capture | Field marketing | BACKLOG | |
| Onboarding health score | Customer success | BACKLOG |
The quote configurator was asked for on a Tuesday, shipped two Fridays later. That story is why this board fills up.
Every app on this board is the same recipe. An operator who owns the outcome, the shared brain underneath so nothing gets rebuilt, one embedded engineer who ships. The apps multiply because the foundation is already paid for. App number twelve costs a fraction of app number one.
Monitoring
The boring dashboard that keeps the exciting ones honest. Tokens, cost, drift, anomalies and guardrails, watched around the clock, escalated only when a human is actually needed.
| SOURCE | LAST INCREMENTAL | LAST FULL SYNC | ROWS LAST RUN | STATUS | |
|---|---|---|---|---|---|
| CRM mirror | 06:00 today | Sun 02:00 | 18,412 | HEALTHY | |
| Product analytics | 06:05 today | Sun 02:20 | 241,038 | HEALTHY | |
| Ads platforms | 06:10 today | Sun 02:40 | 9,284 | HEALTHY | |
| Search console | 06:00 today | Sun 03:00 | 3,412 | HEALTHY | |
| Call transcripts | 05:45 today | Sun 03:15 | 86 | BACKFILL QUEUED | |
| Warehouse | 06:15 today | Sun 03:30 | 312,940 | HEALTHY |
when a seller hears nothing for a week they assume something broke, this page is the answer.
| ENGINE | TOKENS/DAY | €/DAY | PER OUTCOME |
|---|---|---|---|
| GTM Score | 6.2M | €3.70 | €0.003 / account |
| GTM Ads | 4.8M | €3.40 | €0.05 / move drafted |
| GTM Outreach | 3.1M | €2.40 | €0.02 / draft |
| SEO · GEO factory | 14.6M | €9.30 | €0.13 / page |
| Chat + reporting | 7.4M | €4.20 | €0.01 / answer |
| Cleanup + enrichment | 5.1M | €2.50 | €0.005 / suggestion |
Roughly €26 a day, €782 a month all-in, runs the whole room. One drafted page costs €0.13 to produce, the humans it frees are the real line item.
The 8 Jul spike is the throttle earning its keep, a crawl loop capped at +€38 instead of +€800.
| MODEL | LIVE | EVAL | FALLBACK |
|---|---|---|---|
| Scoring | v14 | 98.6% | v13 · 1 click |
| Next-move | v9 | 97.8% | v8 · 1 click |
| Creative judge | v7 | 94.1% | retrain Thu |
| Cleanup matcher | v11 | 99.0% | v10 · 1 click |
Drift past the band schedules a retrain on its own. Nobody has to notice the model got stale, the monitor notices.
Under the Hood
The whole machine on one page. Data flows down, decisions flow through people, outcomes flow back and make everything smarter. Click any block to open it.
CRM data
First-party
Second-party
Third-party
The database
The Shared Brain
one place everything becomes usable · the part 80% reusable across every new capabilityPerformance
Every paid channel on one desk, judged against closed revenue in your warehouse. The engine moves budget nightly toward the cheapest real customer. You approve every move.
Three questions decide whether a performance number means anything. Where the credit concentrates, because a model handing most of it to the last click is mostly describing itself. Whether the revenue came from people who were already customers. And whether a channel comfortably beating its target is a win or a sign you are underspending it, which it usually is.
What the platforms say vs what your warehouse says
| CHANNEL | PLATFORM SAYS | WAREHOUSE SAYS | WHY THE GAP | THE MOVE |
|---|---|---|---|---|
| Search · brand | €78 CPA | €81 real CAC | honest. clicks become customers | SCALING |
| Search · non-brand | €96 CPA | €2,410 real CAC | brand halo credited to generic terms | REBUILT · RETEST |
| Paid social · prospecting | €54 CPA | €510 real CAC | optimizes to leads that rarely close | NEW BID SIGNAL |
| LinkedIn · ABM | €210 CPA | €390 real CAC | pricey clicks, real pipeline behind them | SCALE TO ICP LIST |
| Retargeting | €12 CPA | €3,800 real CAC | was re-buying people who already bought | CUT 80% |
Your three decisions this morning
Where the next €1,000/day goes
Proof, on purpose
Triangulated attribution
Three methods, printed side by side, because they disagree and the disagreement is the useful part. Self-reported is what the buyer said. Tracked is what the pixel saw. Modeled is what the spend curve implies.
| CHANNEL | SELF-REPORTED | TRACKED | MODELED | SPREAD |
|---|
Which one is right? None alone. The CRM source field always names a channel. It is rarely the first one the buyer actually met. The pack prints all three and the spread, so a budget argument starts from the disagreement instead of hiding it.
Agents
The digital teammates that run the engines. Each one has a job description, a skill set, guardrails and a cost. Hiring a new one takes weeks, so does firing one. That part we made easy.
The roster
| AGENT | JOB | ENGINE | RUNS TODAY | COST/DAY | APPROVED | STATUS |
|---|---|---|---|---|---|---|
| The Conductor | routes every job to the right model | platform | 1,410 | €11 | · | |
| Scorekeeper | rescores every account nightly | GTM Score | 3,120 | €9 | 98% | |
| Bid Captain | drafts nightly budget moves | Performance | 96 | €6 | 94% | |
| Creative Director | briefs + generates ad creatives | GTM Ads | 48 | €7 | 91% | |
| Creative Judge | pre-scores creatives, kills losers | GTM Ads | 48 | €3 | 96% | |
| Outreach Drafter | drafts outreach worth sending | GTM Outreach | 210 | €8 | 89% | |
| Reply Learner | learns from every reply | GTM Outreach | 140 | €2 | · | |
| Page Factory | builds pages behind a quality gate | SEO · GEO | 31 | €5 | 93% | |
| Citation Tracker | tracks who the AI engines cite | SEO · GEO | 120 | €3 | · | |
| Reconciler | reconciles + drafts reporting | Reporting | 18 | €2 | 99% | |
| CRM Janitor | keeps the CRM clean | platform | 260 | €2 | 97% | |
| Watchdog | monitors the other agents | platform | continuous | €2 | · | |
| Spec Writer | turns requests into build specs | expand | 6 | €1 | 95% | |
| Researcher | deep-dives accounts + markets | shared | 44 | €4 | · | |
| Call Coach | scores calls, writes coaching cards | GTM Sales | 61 | €5 | 92% | |
| Deal Reviewer | nightly drift + compliance sweep | GTM Sales | 214 | €4 | 96% | |
| Battle Card Keeper | auto-updates competitive cards | GTM Sales | 12 | €2 | · | |
| Proposal Drafter | CRM record → priced draft | GTM Sales | 9 | €2 | 95% | |
| Media Planner | cross-platform budget planning | GTM Ads | 33 | €6 | 93% | |
| Asset Builder | briefs → assets in every format | GTM Ads | 58 | €7 | 90% | |
| Localizer | drafts in the buyer's language | GTM Outreach | 120 | €3 | · | |
| Deliverability Sentinel | guards the sending fleet | GTM Outreach | continuous | €2 | · | |
| + 14 more on the payroll · enrichers, refreshers, summarizers, escalators, the plumbing crew | ||||||
1 · Pick the job
3 · The ship plan
Skills
The company's know-how, written down once and packaged so any agent can run it. When your best marketer's method becomes a skill, it stops leaving in their notice period.
Scores one account from product, CRM and web signals, with the reasoning attached.
Joins any channel's spend to closed revenue in the warehouse. The truth serum behind Performance.
Writes a first touch like someone who did two hours of homework. Carries the reply-pattern library.
Scores a creative against every attribute the account has ever learned, before a euro touches it.
Turns a keyword cluster into a page that survives the quality gate. Refuses to ship thin.
Asks the AI engines a buyer question, records who gets cited and why. 120 questions a week.
Checks every reported figure against the warehouse before a human ever sees it.
Finds and merges duplicates with the confidence score attached. Learns from every human call.
Turns a plain-language request into a build spec with scope, tables and guardrails.
Sweeps any outbound text against the brand voice rules. Nothing off-voice leaves the building.
Checks every experiment against its agreed stop conditions. Pulls the plug without a meeting.
Scores a sales call on the mechanics that win. The card goes to the rep before anyone else.
Checks one deal against the signed deal rules. Flags drift with evidence attached.
Prices a deal from comparables + the price book, inside guardrails. Routes exceptions up.
Splits budget across Google, Meta, Reddit and TikTok from marginal CAC. The chat runs on it.
Turns an approved brief into every format via Higgsfield, Arcade and AdCreative.
Rewrites any outbound text in the buyer's language, tone preserved, flags checked by a native reviewer weekly.