“I have no idea how we got here.”
Every team says it. Few know how to stop it.
Builder Lab reconstructs the reasoning behind decisions your company has already made, using the Slack threads, docs, and tickets it already generates. No documentation. No behaviour change.
The problem
Someone joins your team. They're taking on a product, a system, a process. They need to understand why it works the way it does.
So they search Slack. Dig through docs, PRDs, tickets. Ask whoever was in the room. Piece together whatever they can find.
They get fragments. Enough to move forward. Not enough to be confident.
They make their best guess about what was decided and why, and hope they're not missing something important.
This is how context actually gets reconstructed today. Every time it happens, there's a cost. Work gets repeated. The same thinking gets redone. New people take longer to become useful.
The reasoning behind the decision exists somewhere. It's just not in a form anyone can use when they need it.
Raw artifacts
Slack threads, docs, tickets, emails, meeting notes. Whatever exists.
Reconstruction
Builder Lab identifies real decisions and rebuilds the reasoning behind them.
Structured output
Every claim sourced. Gaps named. Confidence scored.
The output
What comes back.
One decision area. Days, not weeks. Every claim sourced, every gap named, confidence scored throughout.
01 · Verdict
A confidence-scored summary of what was decided, what is still in force, and what the most recent decision was.
02 · Decision log
Every real decision, dated, attributed to who had the authority, and tagged with what triggered it.
03 · Evolution
How the decision changed over time. What was sidestepped. What was deferred and why.
04 · Still open
Unresolved questions. Recurring debates. Conflicts and gaps named explicitly — not smoothed over.
05 · Narrative
A chronological account of everything that happened, written in plain language that someone new can act on immediately.
Confidence is scored. Conflicts are surfaced. The output tells you how much to trust it — and why.
Who it's for
GTM and operations leaders at companies between 50 and 150 people.
Big enough that memory has visibly broken. Small enough that one person still owns the answer when the foundation goes wrong.
“My team is running 25 projects at the same time. Every one has a decision history nobody fully remembers. Someone says it didn't work — who made the call? What happened here?”
What makes this different
Other tools help you work faster with the information you already have.
Builder Lab goes underneath that. It doesn't store what someone wrote down. It doesn't ask anyone to document anything. It doesn't smooth conflicting accounts into a tidy answer.
It tells you what was actually decided — sourced, scored, and honest about what it doesn't know.
The pilot
One decision area. A structured output in days.
Flat fee, not a subscription. Operationally simple by design. The question we answer together: is the output trustworthy enough to use.
01 · Scope
You name one decision area you want reconstructed. We sign an NDA with privacy clauses appropriate to your data.
02 · Artifacts
You drop the raw material into a shared folder — Slack threads, emails, tickets, meeting notes, screenshots, PDFs. No system access. No integrations.
03 · Reconstruction
I run the artifacts through the extraction and reconstruction process. You get all five layers: verdict, decision log, evolution timeline, gap analysis, and narrative.
04 · Iteration
I work the output against your judgement until you trust it on a real decision. Then we stop.
Fee$800
TimelineDays, not weeks
AccessNo integrations. No system access.
OutputFive layers. Sourced. Confidence-scored.
Design partner spots are limited. This first cohort is 8–10 companies. What I ask for in return: one real decision area, honest feedback on the output, and candour about what doesn't work.
Founder
Why I built this.
The problem kept finding me.
A decision that should have been explainable. The information was there: Slack threads, docs, tickets, people who remembered pieces of it. But the reasoning wasn't. I could find what happened. I couldn't find why it made sense at the time, what was ruled out, what nobody had actually settled.
The company hadn't lost the information. It had lost the thread.
I spent years inside scaling companies in the room for the decisions, reading the threads, making sense of what was actually settled versus what people only thought was settled. You develop a particular instinct for the gap between what got discussed and what got decided.
As a lawyer, I'm trained to ask what was actually decided here, and whether the reasoning is strong enough to build on. Most of the time, it isn't.
As an operator, I know how easy it is to keep moving anyway. You piece it together, make your best guess, and hope you're not missing something important.
And now AI is making confident answers out of the same fragmented inputs.
That's what made this worth building.
EC — Elana Caplan, Founder
Contact
If a real decision area is on your desk, I want to hear about it.
Design partner spots are open. Email goes directly to me.