# Working Mono / PATCH > Machine-readable mirror of https://www.workingmono.com/ > Working Mono is the AI-native firm behind PATCH. We do the work. You own the machine. Working Mono · an AI-native firm # Is your business AI-legible? Your agents inherit your data problems. The CRM can look clean while the business is unreadable. PATCH maps the terrain, builds the memory, and ships the workflows your team and your agents act on. Book a 20-minute call -> See how it compounds We do the work. You own the machine. Foundation live in month one. ## Proof 30 + Commercial systems delivered Month 1 Foundation live, guaranteed 100 % Owned by you 270 + Patches shipped to client systems Trusted by AI-native teams The problem ## The CRM can look clean while the business is unreadable. Product usage, billing, support, CRM, lifecycle, and market signal all live in different shapes. Your reps work around it. Your agents inherit it. PATCH maps the terrain, builds the memory, then ships the workflows, into infrastructure you own. How it compounds ## Ship weekly. See what it moved. Every patch reports the revenue it touched in a weekly ROI report. Every report sharpens the memory. The system trends up, in infrastructure you own. TERRAIN · 14 SOURCES 01 / MAP Step 01 ### Map the terrain Consulting discovery asks your team to explain the business in workshops. AI Terrain Mapping runs both halves at once: interview agents debrief every stakeholder while we read the source systems directly. What the team believes, compared against what the APIs prove, charted into a map your team can inspect and correct. Output: the memory map, committed to your PATCH repo Step 02 ### Build the memory The terrain becomes a source-traceable Commercial Memory in your warehouse: product usage, CRM, billing, and support joined into one model. Every answer traces back to source. Humans read it. Agents query it. Nobody argues with it. Output: one model your team and agents both trust Step 03 ### Generate foresight Memory shows what is true. Foresight shows what to do next. The system sweeps the account field and locks what should move: the expansion ready for a human, the signal that needs an owner, the renewal carrying risk. Output: the queue of highest-leverage next actions Step 04 ### Ship the patch The next action becomes a patch: routing, lifecycle, alerts, enrichment, dashboards. Built, verified against live data, and landed in your repo. Production workflows your team acts on the same week. Output: a verified patch, live on your infrastructure Step 05 ### Learn from the result Every patch reports back. What the system surfaced, what the team acted on, and the revenue it moved, trending week over week. The ROI report reads like an instrument, not a slide deck. Output: the weekly ROI report, revenue moved Step 06 ### Update the memory The result feeds the memory. Definitions sharpen, joins extend, exceptions get recorded. The system gets sharper every cycle, and it compounds in infrastructure you own. Output: a sharper memory, and the next patch ships Is your business AI-legible? Find out in 20 minutes. Book a 20-minute call Ask, then act ## One memory. Every surface. Inputs attio stripe metronome snowflake segment postgres slack hubspot mixpanel intercom zendesk linear bigquery salesforce posthog amplitude attio stripe metronome snowflake segment postgres slack hubspot mixpanel intercom zendesk linear bigquery salesforce posthog amplitude + and more 01 / 03 > Month one ## Month one makes the business readable. Weekly patches make it move. We absorb your context, then deploy the infrastructure around it. Concrete by design: warehouse live, first workflow running, query surface working, code committed to your repo. **Week 1** ### Map the terrain Your team names the bottleneck worth fixing first. We chart the sources and stand up the warehouse and data model underneath it. **Week 2** ### The first loop closes That bottleneck runs on real data, not a demo. Signal goes in, the right action comes out, for your team. **Week 3** ### Query surface and alerts Slack alerts and the query surface go live. Your team asks questions and acts, and we push changes between sessions as you learn. **Week 4** ### Foundation owned Code committed to your repo, data in your warehouse. The foundation is live, or your money back. Then we queue the next patch. D01 WEEK 1 / 4 · MAP THE TERRAIN Your team names the bottleneck worth fixing first. We chart the sources and stand up the warehouse and data model underneath it. Week 1 Map the terrain d07 · model committed Week 2 The first loop closes d14 · live on real data Week 3 Query surface and alerts d17 · first question answered Week 4 Foundation owned d28 · code in your repo You own the machine. You own the artifacts. You commission the work. Code in your repo, data in your warehouse, workflows on your infrastructure. It's the RevOps, GTM engineering, and analytics function you'd otherwise hire, running before you can justify the headcount. Cancel any month and the system keeps running. We keep it compounding. In production ## Real systems, running today. Not a Notion deliverable. Running commercial infrastructure across 30+ owned systems, operated weekly. operating ledger systems 34 runs · 7d 0 utc --:--:-- id system motion schedule last run runs·7d status ▮ standing by… The next step ## Let's make your business legible. In 20 minutes you'll know how AI-legible your business is, and what it would take to get there. Booking · intro call ◆ 20 min · direct with the team reading the calendar… prefer email? contact@workingmono.com We do the work. You own the machine . #### Product How PATCH compounds GTM engineering RevOps automation Owned GTM Attio, built right #### Company How month one works In production Proof Contact #### Get in touch contact@workingmono.com Book a call (c) 2026 Working Mono. Official Attio Founding Expert Partner.