0%
longer code review when AI tools are used heavily
Faros AI · 2025 · 1,255 teams
The grounding layer for AI-led SDLC
As AI writes more of your product, Lucigent ensures your AI builds what you meant.
One living memory beneath the AI tools your team already uses — so intent survives every handoff.
JiraGitHubCursorClaude Code…
The shift
AI was supposed to be faster and cheaper. The data doesn't fully align.
Generation is cheap now — but the work moved to verifying what the AI produced. The promised gains are being eaten by longer reviews, rework, and rising complexity.
0.0×
more issues in AI-co-authored PRs vs human code
CodeRabbit · Dec 2025 · 470 PRs
~0×
code churn — lines rewritten within two weeks
GitClear · 2024
+0%
rise in code complexity after AI adoption
CMU · MSR 2026
Why it's happening
Every persona has an AI. The decisions still get lost.
Those decisions used to get made in grooming, planning, and the Slack threads — then folded back into the spec. The agentic flow skips that, so they scatter across tools and never reach the one that builds.
- The requirement's AI sees the words — not the questions.
- The IDE's AI sees the code — not the intent.
- CI's AI sees the diff — not what was meant.
Three AIs, three guesses, no shared truth — so a GDPR violation ships.
It's not missing intelligence — it's missing grounding.
— Lucigent, the grounding layer
Everything you build, woven into one living graph beneath it all.
Your work is continually ingested into a single living knowledge graph — then reached three ways, so every persona is grounded in the same memory.
1Continually ingested
2The grounding layer
3Grounded where they work
Requirements
Code
Tests
Production signals
Domain · Org Context · Compliance
Ingest
Weave
+
link
+
link
Living knowledge graph
one graph, every link
Anchor
- Semantic Search
- Multi-lens Context Bundle
- Verify
Lucigent Agents
act in your tools
MCP
your agents pull
Ask the graph
query + converse
Product Manager
Jira & Slack · decision-ready
Developers
in the IDE · builds to intent
QA / SDET
in the IDE · tests from intent
Leadership
ask + dashboard · risk & readiness
In action · one ticket, every persona
Pick a persona. Watch the work build itself.
The same ticket — APP‑247 — end to end in every persona's own
tool. First and last frames are theirs; the middle is Lucigent grounding the graph.
Intent · Product
One vague requirement. One quiet rescue.
Priya posts a one-liner about deleting users. Walks away. Lucigent's Ambiguity agent enriches the ticket before grooming — with questions grounded in the product graph.
Delete user accounts
Let admins delete user accounts.
Priya · created 2 min
ago
A one-liner. Priya posts and walks away.
L
Hi Priya — APP-247 needs a few
decisions before grooming. Three questions from the graph:
- Soft delete, hard delete, or anonymize? We use anonymize for APP-184 (project deletion). GDPR matters.
- The user's comments and mentions — hide, replace with "Deleted user," or leave intact?
- Active subscriptions — cancel immediately, prorate, or honor through end-of-period?
P
Anonymize. Replace author with "Deleted user." Cancel subscription
end-of-period.
L
Got it. Writing the enriched ticket back to Jira now — with linked
tickets and an audit summary of this thread.
Grounded questions from the graph. Not chatbot prompts.
Delete user accounts
Admin-initiated user deletion. Anonymize the user record (don't hard-delete) per GDPR pattern from APP-184. Replace comment authorship with "Deleted user." Cancel active subscription at period end (not immediately).
Acceptance criteria
- PII removed from the user record on delete; user record retained with anonymized fields.
- Author replaced as "Deleted user" across all the user's comments and mentions.
- Active subscription cancelled at end of current billing period; no further charges.
Linked
follows APP-184 (anonymize pattern)
touches APP-92 (billing)
Enriched by Lucigent
View Slack thread →
Enriched, linked, auditable. Priya hasn't returned yet.
Build · Developer
Their AI agent. Grounded in your codebase.
Arjun starts the build. His IDE's AI agent doesn't know the codebase — so it asks Lucigent. Real patterns and conventions come back, not boilerplate guesses.
src/users/delete.ts
// TODO: implement user deletion
export async function deleteUser(userId: string) {
}
You
Implement user deletion from APP-247.
Dev hands the AI a ticket ID.
Lucigent
· context fetch
3:15 PM
- Anonymization utility —
lib/anon/with helpers for stripping PII from user records (from APP-184 precedent) - Cascading author updates —
lib/comments/cascadeAuthor.tshandles updates across all the user's comments at once - Billing API —
lib/billing/cancelAtPeriodEnd()supports end-of-period cancellation (from APP-92) - Intent — 3 acceptance criteria from the enriched ticket: anonymize, replace authorship, cancel subscription end-of-period
Patterns, conventions, and intent — from the real product graph.
AI
Reusing your anonymize utility from APP-184. Cascading the author update across all comments via
the existing helper. Cancelling the subscription at period-end per the billing API. Following
the APP-184 deletion pattern.
import { anonymizeUser } from "@/lib/anon";
import { cascadeAuthorUpdate } from "@/lib/comments/cascadeAuthor";
import { cancelAtPeriodEnd } from "@/lib/billing";
export async function deleteUser(userId: string) {
await anonymizeUser(userId);
await cascadeAuthorUpdate(userId, "Deleted user");
await cancelAtPeriodEnd(userId);
// matches APP-184 anonymize pattern
}AI builds like a teammate who knows your codebase.
QA/SDET
Built fast. Verified against intent, not the code.
The PR opens. Lucigent's verification agent authors tests from the enriched intent — not from the code it's checking. Result tied back to the original ticket.
Add user account deletion (APP‑247)
feat/account-deletion
main
Implements admin user deletion per APP-247. Anonymizes user record, cascades author replacement across comments, cancels billing subscription.
Arjun · 4 commits · 12 files changed
Dev opens PR. Lucigent watches.
Lucigent
· independent verification
5:44 PM
Pulled intent from product memory.
- AC#1 — PII removed from user record on delete
- AC#2 — Author replaced as "Deleted user" across comments
- AC#3 — Subscription cancelled at end of period
Authored 3 tests from intent. Not from the diff.
Authored from intent. Independent of the implementation.
✓ AC#1 passing
✓ AC#2 passing
× AC#3 failing — user deleted but billing continues to
charge
Tests written from acceptance criteria — not from the code being verified.
Result tied back to intent. PR can't merge until the intent matches.
Leadership · Eng lead
Know what's at risk — before you ship.
Before sign-off on release 4.7, Elena (VP Eng) asks Lucigent the questions she used to chase across five tools. It answers from the same graph Product, dev, and QA built on.
Lucigent
· leadership view
4:30 PM
Ask the graph
- → What's at risk in this release?
- Where are the compliance gaps?
- Are we ready to ship?
- What's likely to slip?
The questions she used to chase across five tools — now one place.
Lucigent
· risk readout
4:30 PM
3 risks, grounded in the graph:
- APP-247 (delete accounts) — GDPR-sensitive, blocks on
APP-92(billing), not yet merged - 2 requirements shipped with no test coverage
- 1 requirement drifted from its acceptance criteria
Answered from the same memory the team built on — not a guess.
Decision, with eyes open
- Hold APP-92 → APP-247 ships next release
- 2 untested requirements assigned before sign-off
- Audit trail attached, mapped to your frameworks
Decided with Lucigent
View risk readout →
Go / no-go on evidence, not vibes — and audit-ready.
The payoff
One memory. Four payoffs.
The same grounding layer pays off differently for everyone who touches the ticket — measured, not promised.
Conservative numbers from early engagements. We instrument these from day one of a pilot — by the end of two weeks, you have your own numbers, not ours.
Product owner
~20%
faster grooming
Requirements arrive enriched. Duplicates caught before sprint commits. Ambiguity surfaced before it becomes rework.
Developer
~25–30%
fewer iterations per ticket
Builds against the full requirement, first time. ~20–30% lower IDE token use (~1.5K curated vs ~15K+ broad discovery). Higher code acceptance.
QA
~90%+
AC test coverage
Coverage from intent in the graph. ~7 in 10 generated tests accepted as-is, vs industry ~3 in 10.
Leadership
~15–20%
eng hours from rework to new features
Overall cost reduction. Plus ~40% faster root-cause, and an audit trail every release, mapped to your uploaded frameworks.
Get started
See it on your own work.
Get a live walkthrough to see how it fits your team.
Lucigent makes the intent precise, then grounds both the build and the check on it.
Precise intent in→grounded code from it→independently verified out
Intent check: 2 of 3 acceptance criteria passing.
This PR implements anonymization (AC#1) and cascading author replacement (AC#2) correctly.
× AC#3 failing — user is deleted but billing subscription is not cancelled. Charges continue. Expected: cancelled at end of period per the enriched intent.
Tests authored from intent, independent of the implementation. View test runs →