Leon B.

Wrote about something I keep seeing at companies scaling from 50-200 people - the "Complexity Wall" where your product has market fit but your data systems can't keep up. Three diagnostic signs and one architectural shift you can make this week. Curious if others are seeing the same pattern.

Follow-up to the Fractional GTM Architecture I shared earlier this week - wrote about what happens after the pipeline: the "Complexity Wall" where your data systems can't keep up with growth. Turns out the same architectural thinking that fixes the 48-Hour Void on the outbound side applies to onboarding and churn. Three warning signs your post-sale data is leaking.

Jared R. asked me to share this framework with the group as we prep for the 'Voice of the Revenue Creator' report. I’ve been auditing Series A pipelines and found a consistent "48-Hour Void" where lead signal decays by 90% because manual SDR processes are too slow. I built this System Architecture to fix it. It moves away from "Orchestration" (connecting tools) to "Architecture" (defining logic). The Key Shift: Instead of hiring more SDRs to chase leads, we use a "Signal Refinery" (Step 4) to qualify intent in < 2 minutes using local LLMs. Happy to answer questions on the tech stack (n8n + Python + Clay) behind this for anyone building their own engine.

The "SDR is Dead" debate is lazy. The role didn't die, it split. I’ve been auditing the "48-Hour Void" in Series A pipelines the window where manual lead scraping causes signal to decay by 90%. My thesis: We are trying to solve a Latency Problem (Data) with a Bandwidth Solution (Headcount). I recently ran an experiment replacing the "SDR Research" layer with a Python-based "Signal Refinery" (n8n + Clay + Custom Logic Gates). The Architecture:

The Result: 160% increase in pipeline coverage with zero manual data entry. I recorded a 57-second build log of the actual workflow running live (no pitch, just the code/logic). Question for other GTM Engineers: Are you keeping the "Research" function with the SDRs, or have you successfully decoupled it to an automated layer yet? (https://www.loom.com/share/ec261842b5474ecc9262b9ae28764ba4)