Lucas Perret

Operations Lead @lemlist

Just a guy obsessed with tech and ways it solves business problems 🤓

I believe people should spend all of their time on meaningful activities such as building relationships with others.

That’s why I spend all of mine solving the inefficiencies I encounter at work by building the right processes and systems for my team.

I am all about networking and discussing anything related to operations, so if you are interested in having a quick chat then feel free to reach out to me. 💌

Growth Manager - Product & Ops

Richard Makara

CEO @ reconfigured | eradicating inconsistent metrics

GTM Engineer-for-hire. 

Returning to GTM/Growth Engineering after a long hiatus and 3 years as a tech startup founder. 

Love to chat with people about this topic. DM me

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From a previous life: 

building reconfigured - a quick-capture journal for overloaded minds juggling tabs, tasks, and tools. soon also with MCP capabilities.

sharing progress as I go, usually in the form of neat tricks/productivity gains I've learned along the way.

-- 

Have had the privilege of building the growth engine of a 🦄 company, as well as completely rebuilding CRMs from scratch (Salesforce, HubSpot). 

Some others stats:

- Triangle shaped person - Design, marketing & programming
- B2B SaaS growth + tech stack building.
- Grandfather of Junction, Europe's leading Hackathon 
- Board alumni of Aalto Entrepreneurship Society
- Occasionally tinkering on app ideas with Flask/TS-Node, ReactJS, PostgreSQL & Docker. 
- In a love/hate relationship with TypeScript.

Member

lots of talk lately about claude code for non coding work. personally feel like i do all my work nowadays with a claude project as my interface so im all bought in on the hype. 

i started using claude code outside of development work a while ago by accident

wasn't super happy with chatgpt / chat interfaces in general for building content or iterating on messaging so I had the silly idea of treating content projects as if they were coding projects

except there was no code, only a collection of text/markdown files that the LLM could reference, create and update.

nowadays CC is even more powerful since it can search the web, run API queries, find files across your laptop

it's also turning out to be a great tool to consistently capture what im working through, retaining a convertible log of learnings as i go vs. scramble documents together at the end.

not sure if im right on the money but sounds like there's a bit of overwhelm when it comes to "how do i structure my project" - luckily claude is pretty good at managing that part, you just gotta direct it regularly.

below is an example of my project structure for consulting, give or take.

what yall wanna know?

starting the new year thinking about what I'd like to share and teach out here.

As a founder it was easy: write about whatever's interesting to my target audience and might start conversations with them.

Now that I've been back to growth/GTM engineering for the last 4 months, it's been more ad hoc: learnings from working with clients, building systems, even tinkering with Claude Code setups for GTM purposes.

The GTM engineering space is wildly different than when I was at Paddle. 

There are many more of us now, and the tooling has evolved to where we can spend more time dissecting why GTM works or doesn't rather than setting up endless automation flows.

also I keep forgetting I burned out this summer and that healing is slow and gradual. But I can feel the nerdy excitement coming back. 🙂‍↕️

On a personal front, this year I hope to do a mix of things: 

continue ongoing "gun for hire" projects where I'm hands-on with teams, some scoped technical implementations, maybe one or two advisory engagements.

Either way, planning to write about what I learn, whether quick posts like this or longer "how to do X" articles.

Lots to cover. Anywhere from "how do we get people to talk to us" to "how do I still in 2025 stitch together all these tools without spending hours maintaining them."

anyone got any better ideas?

inspired by fellow gtm engineers who are building awesome tools, i got curios and built myself a way to operate clay via claude code. Why?

i spend most of my productive time in claude code - planning, analyzing, building context. coming up with the next bits to build for the gtm cases I work on.

and i spend most of not so fun time debugging and upgrading within clay, usually with the help of claude but still very manually feeding it outputs, results, column configurations. 

.. and VERY OFTEN copy pasting new versions of prompts that break everytime 💀

so for now this thing let's me operate clay without ever leaving Claude, AND has access to relevant context AND keeps my shit version controlled when I inevitably mess up and need to revert.

what you dont see in this demo is actually upgrading the ai column prompt based on the row run results, but im fixing that up next. 

as bonus it also lets me document all of the tables i've built and how and why they are constructed 😄

i keep saying, what a time to be alive in the gtm space 🫶

{ insert clickbait one-word keyword to promote engagement in promise of possible access }

i dont know if this is lazy or clever, but i started building a "gtm engineering toolbox" for myself [via claude code, of course], which does a variety of things depending on what im working on. 

latest one being a 'tool oracle' which effectively is a collection of connected markdown files about specific gtm tools, what they are good at, what they aren't, how they integrate and dont integrate, api documentation etc.

... and most importantly griefs and workarounds sourced across community forums (can you guess which one has the most? 🙂‍↕️)

it's been especially useful now at the start of a new project where i need to 

a) evaluate current setup 
b) what else do we need possibly procure  
c) calculate likelihood crying if i have to make any of these tools dance in sync

it's interesting because now i can ask tooling questions WITH context i've put together about the business, goals, stats, whatever else relevant im working on since im running these questions out of my consulting [claude] project that are also a library of text files.

so as an example, the question goes from "does A have an integration with B" to "how do I get these kinds of data points over to tool x and what are my limitations given my tools and plans im on"

and then i can continue the discussion/work in the same session.

yes yes, the toolbox is accessible via MCP

i love sales call transcripts. especially first-sales calls - its the first thing I ask for when I start working with a new client.

- manually written sales call notes are usually biased toward what you want to hear.
- recorded AI summaries always get mixed with whatever the seller said too
- people hear what they want to hear, esp if commission is on the line

ive been guilty of all that for sure

but the transcript doesn't lie whereas our brains do:

you remember the parts that confirm your thesis. you summarize in your language, not theirs. and when you look back across 20 calls, there's no way to actually compare them.

the problem is less about taking accurate notes but that you're filtering in real-time:

- exciting signals get amplified
- lukewarm responses get softened
- "maybe later" becomes "interested"
- their exact words get replaced with your interpretation

you end up with 20 calls worth of confirmation bias dressed up as insights.

transcripts don't have that problem. the words are the words. 

... especially when you strip away the sellers speech 😄

and run them through an LLM that religiously follows a rigid framework to extract signs of demand (see Rob Snyder for the framework/mental model)

i think my new favorite gtm gadget is pulling historical job ads via theirstack and converting the results (incl. job descriptions) into a structured JSON in clay.

if none of that made sense let me rephrase: "find all the relevant job ads from the last 30/90/180 days and extract specific patterns im interested in, eg what specific projects are they focusing on next"

more often than not the descriptions are rich with context:

- What they're actually building/owning - "Build      
 {sales/marketing/people} function from scratch" vs "maintain existing structure & systems"             
- Their philosophy — language like "continuous feedback" or "coaching culture" signals they already think a certain way.                                     
- Concrete growth stage — actual ARR figures and funding amounts show up in job descriptions. Cuts through marketing chat like "fast-growing" or "market leader"                              
- Whether they're distributed — job locations + remote flags reveal multi-country operations. Proxy for async tool adoption if that' important to you 
- Hiring velocity — raw job counts show where they trying to grow                     
- Anomalies — unusual patterns (268 sales jobs across 9 countries) might reveal staffing companies or marketplaces hiding as normal companies

of course whatever people write in job ads maybe simple marketing to attract talent, but at the very least its prose you know came from the source itself, not from a technographic blackbox data provider.

and once its sitting flag as 2-3 labels in your accounts table, it's pretty neat way to start segmenting and building outreach.

i always thought job ads were a signal you "monitor" and respond to when they appear. but seems like its a good data source for good ol slightly customized ICP slicing/identification. 🙂‍↕️

starting to think we got this whole sales call AI summaries wrong. sales calls aren't content to be summarized but superior data to be extracted.

the first 15 minutes of an intro call is what matter the most. that's the window where the prospect spills the beans: who they are, what they do, what they're struggling with. they tell you directly or inbetween the lines why they took the call in the first place.

... and im sorry to break it to you but it's probably not because your product is amazing.

after 15 mins, everything changes. the seller starts preaching about their product, their method, the value they provide and inadvertently either shuts the prospect down or makes them adapt their language to match yours. this is also where "discovery" usually ends and the pitch starts. 

I say it in quotes because sometimes discovery is done as a theatrical exercise just to check the box before pitching whatever you practiced beforehand.

theres incredible value still there even in calls where you didn't drill down on prospects hopes and desires. there are likely phrases customers say that we miss because we're focused on running the call, working through our own checklists. but the language is there.

AI summaries miss this. they process the entire call, extract action items, paraphrase next steps (which btw are prolly the next steps you want as a rep, not what the customer wants 🙂‍↕️).

where im seeing immense value/success is in extracting only customer language from transcripts, analyze using a framework, and extracting everything into a uniform structured object eg JSON.

id love to hear if somebody strongly disagrees or has done something interesting with sales transcripts.🤔

pic related - structure is real, content imaginary. one of these per 1 call

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