Built for AI companies

AI forward-deployed engineers.

Launchway AI’s AI FDEs turn customer requirements into tested changes in your codebase. Your team sets the scope and reviews every change.

Bring us a deployment

From requirement to reality

Your AI FDE, from context to code

Every customer brings
a different world.
Your product has to work in it.

The workflows. The business rules. The systems already in place. Your AI FDE does the engineering between your product and the way your customer works.

How it works

From their requirements.
To working code.

AI FDE / illustrative integration01 — 04

Customer requirement / retained context

Connect item-level requests
to the retailer’s order system.

01 / Connected contextUnderstand

RequirementsSystem boundariesExisting code

02 / Connector changeCandidate 01

retailer / request-policyIllustrative logic

Candidate 01 · retained implementation

01when request.type == "return"

02 check(order.owner, item.eligibility)

+ save_once(order.line, quantity)

+ confirm_after(source.read_back)

Revision 02 · AI FDE change

+if order.is_gift

+ offer("size_exchange")

03else preserve(standard_return)

04confirm_after(source.read_back)

03 / Behavior & outcomeTraceable

✓Eligible item onlyPassed✓Safe retryPassed✓Standard returnsPassed✓Gift size exchangePassed

↳

Retailer record → read back

Size exchange request saved

Matched ✓

Revision 02 / waiting for verification

Revised result appears after the checks.

Customer feedback → AI FDE↶

“For gifts, offer a size exchange instead of a return. Keep standard returns unchanged.”

Candidate 01 previous result retained→ Revision 02 ready for team review

01 Read feedback
02 Update code
03 Rerun checks
04 Revised result

01 Understand

One requirement.
The whole context.

A customer needs item-level returns connected to their order system. Your AI FDE connects that request to the policy, APIs and code already in place.

Start with the customer’s actual system.

RequirementsConnected contextDefined scope

02 Implement

The context becomes
a concrete change.

The AI FDE builds the connector in your codebase: check the right item, save the request safely and confirm the retailer’s record. Your team gets a focused change to review.

The requirement stays attached to the code.

Your codebaseReviewable candidateSafe retries

03 Verify

Follow the change.
Through to the result.

Check the behavior against the requirements. Trace the customer’s request through the connector to the saved retailer record, with confirmation after read-back.

A saved request, with the path that led there.

Behavior checksSource read-backReview trail

04 Iterate

Your feedback.
The AI FDE’s next change.

A new request starts the next implementation. The AI FDE changes the connector and verifies the revised behavior, using the context it already holds.

01
Read the feedback. Reopen the context.
For gifts, offer a size exchange instead of a return. The AI FDE reconnects that feedback to the policy, order API and existing connector.
02
Update the affected code.
It adds the gift-exchange branch, keeps standard returns unchanged and retains the first candidate. The feedback becomes a focused patch.
03
Rerun the checks.
It reruns the original return and retry checks alongside the new gift scenario. A revised result stays pending until verification finishes.
04
Verify the revised result.
The size exchange is saved and read back from the retailer’s system. Your team can review Revision 02 with its code, checks and retained earlier candidate.

AI FDE implements the feedback. Your team reviews the next version.

Focused code changeOriginal + new checksRetained versions

An AI FDE in action

One refusal.
A different outcome.

A voice agent kept offering instalments after the caller said no. Launchway AI’s AI FDE changed the code so the conversation could move forward.

Anonymized case · local recorded test

Before the changeRecorded case

The caller declines instalments.
The same offer is repeated.
The conversation gets stuck.

Saved call outcomeCall later

After the AI FDE's changeLocal test

The caller declines instalments.
The refusal follows the correct branch.
The conversation moves forward.

Saved call outcomePayment refused

A requirement. A repair. A result you can inspect.Download the film

What the AI FDE changed

The caller says no.
The voice agent moves on.

Launchway AI’s AI FDE fixed the code behind a voice agent that kept repeating an instalment offer. In the test, the refusal led to the next step and the correct call record.

No repeated offer

The voice agent stops offering the instalment plan the caller has already rejected.

A conversation that progresses

The agent moves through the remaining options instead of getting stuck on the same offer.

An accurate call record

The call is saved as “Payment refused” rather than “Call later,” so the record reflects the conversation.

How this was checked

34 behavior checks, repeated three times each. These checked rules for how the voice agent should handle the conversation and save its result. Every check passed.

100 imported records checked. All matched the original data when retrieved from the system.

Recorded in a local test environment. The film uses reconstructed English dialogue.

Built around your team

Your AI FDE does the work.
You keep the decision.

Your product.

Implementation happens in your codebase, against the scope your team agrees.

Your environment.

Start with a test environment you control, before moving toward a customer rollout.

Your review.

Inspect the change and its checks. Your team decides what gets merged.

Explore a read-only run in the app Public open-source repository · separate rehearsal

Start with one deployment

Bring us
their world.

Join the waitlist. We’ll start with one customer deployment in a test environment you control.

AI forward-deployed engineers.

Every customer brings a different world.Your product has to work in it.

From their requirements.To working code.

One requirement.The whole context.

The context becomesa concrete change.

Follow the change.Through to the result.

Your feedback.The AI FDE’s next change.

Read the feedback. Reopen the context.

Update the affected code.

Rerun the checks.

Verify the revised result.

One refusal.A different outcome.

The caller says no.The voice agent moves on.