New World · AI-Native Systems · Stage 4 Engineering
Silos. Handoffs. Manual review. Slow.
Fast. Observable. Deterministic.
This isn't a nice-to-have. It's survival.
We build new AI-native systems alongside your legacy. The substrate, the harness, the agent fleet, the new workflow. You keep what's earning revenue. We build what comes next.
// No repo access needed to get started. We talk first.
Where is your team?
Locate yourself. If you're already feeling the Stage 3 ceiling — generated code that looks right and isn't, seniors burning out in review — the gap to Stage 4 is the work.
Write it yourself
You write the code. The agent does nothing.
// Slow. But coherent.
Ask for snippets
You write most of it. The agent generates fragments on request.
// Productivity feels up. Coherence drifts.
Steer the agent
You review every line. The agent generates whole features under supervision.
// Looks fast. Seniors burn out. False negatives ship.
Design the system
You design workflows, evals, sensors. The agent executes repeatably. You validate output, not code.
// Requires coherent codebase + graph + checkers.
Refinement only
First draft passes the sensors. Your role collapses to tuning. Generation and validation iterate without you.
// The dark factory. Org-level autonomy.
If you're at Stage 3 today and your senior engineers are burning out reviewing AI output, the bottleneck isn't your team — it's that nothing between the agent and production speaks the same structural language. Stage 4 requires infrastructure most teams don't have yet.
The Stage 3 ceiling
The wound isn't AI. It's the gap between the agent and the rules nobody wrote down.
"It looked right in the PR."
The agent generated a plausible solution that violates architectural rules nobody wrote down. The reviewer signs off. Production catches it.
"Our seniors review AI all day."
The reviewer is the bottleneck. The team got faster at generation and slower at acceptance. Net throughput flat or down.
"Different agents write different patterns."
Without enforced patterns, every prompt produces a new dialect. Codebase entropy compounds with every PR.
"We can't tell what the agent missed."
False positives are noisy. False negatives are silent. The agent moves on; the missing thing surfaces in production.
"We tried evals. They were wrong."
Hand-written evals drift. LLM-as-judge is not a sensor. Deterministic checkers are.
"We can't onboard the agent."
A junior gets a runbook and a map. The agent gets a folder of files. No structure, no memory, no boundaries.
This is the prerequisite work. Consistent patterns, a navigable knowledge graph, and deterministic sensors are what Stage 4 needs to exist. Without them, "agentic coding" just produces faster entropy.
The Stage 4 substrate
Everything we build sits on top of the TypeScript compiler — structural understanding, not text search. The agent operates against the code as the compiler sees it.
Inconsistent patterns make agents guess. We migrate your codebase to a small, opinionated set of architectural patterns — verified by the TypeScript compiler at every step, not by review. The agent stops inventing dialects.
Agents are not faster developers — they're developers with no memory. We build a code-graph the agent (and your team) can query: dependencies, coupling, boundaries, multi-hop relationships. This is what makes structural search beat grep.
LLM-as-judge is not a sensor. We design deterministic checkers — coupling rules, layering rules, naming rules, test rules — that score every agent output against the patterns you actually agreed to. On demand, in CI, or inside the agent loop.
// The harness in motion
Spec → refine → code → verify → deliver → observe. Each stage observable, each handoff deterministic. The human's job is harness engineering — designing the loop, tuning the sensors, validating output. Not writing the code.
Stage 5 — "the dark factory" — is what happens when this loop is mature enough that the agent's first draft passes the sensors most of the time. The human role collapses to tuning and refinement. We don't sell Stage 5. We sell the migration that makes it possible.
How we work
We sign project contracts, not employment deals. You can opt out at any stage. Prices are fixed per scope, not open-ended retainers.
30 minutes. We talk. You tell us where your team is — what you've rolled out, what's working, what's getting worse. We locate you in Stages 1–5 and identify the specific Stage 3 blockers. No selling. No repo access.
We give you a CLI command that runs entirely offline on your machine. It scans your codebase and returns the basics: lines, modules, coupling indicators, pattern consistency. Output framed as: what's missing in Layer 1 / Layer 2 / Layer 3 before Stage 4 is viable.
We review the diagnostic together. We propose a scope menu — staged interventions based on what the data shows. You choose how far you want to go. We agree on deliverables, timeline, and fixed price. Then we sign and start.
Layer by layer. Patterns migrated and compiler-verified at every step. Code-graph deployed and queryable. Sensors written, tuned, and wired into CI. Progress is measurable. You see results from week one — and once the patterns are right, the same problems don't return.
What a Stage 4 org looks like
✓
Estimates become honest because evals make them honest.
✓
Code review becomes design review. Seniors validate workflows, not lines.
✓
The bottleneck moves from senior bandwidth to system design — where leverage lives.
✓
The agent produces patterns the compiler can verify. False negatives surface.
✓
Governance runs on demand. You know your Stage health at any point in time.
✓
New developers — and new agents — onboard against the same structural map.
A coherent codebase isn't the goal. It's the substrate that makes Stage 4 viable. Agents and developers are productive when the patterns are consistent — and the sensors catch them when they're not.
Start with a Stage-readiness review. 30 minutes, no repo access, no commitment beyond a conversation.
Book a Stage-readiness review