Find out what it takes to make your team AI-native
Most transformations don't fail on model quality — they fail when a rushed rollout breaks a working process and stalls delivery for months. Discovery maps what's safe to transform, what needs prep first, and what's revenue-critical and off-limits — so you move fast without breaking what works.
3-week fixed sprint
You own every deliverable
NDA-first
Senior engineers & architects who've done this before
What's actually on the table
If you're still weighing whether AI-native is worth the disruption, this is the size of the prize.
Delivery speed, structurally changed
Not autocomplete shaving minutes off a task. When AI operates with real context on your system, work that took a sprint lands in days, and work that waited on a specialist gets unblocked without one. A different throughput ceiling — and once your team crosses it, the old pace is hard to justify.
Ship like a bigger team than you have
Understaffed, over-scoped, hiring frozen — AI-native engineering is how a lean team delivers like a larger one. Not by replacing engineers, but by pulling them off the low-leverage work that eats their week.
Turn tribal knowledge into company property
Your most valuable context lives in a few people's heads, and walks out the door when they do. AI-native development forces that knowledge into a durable, structured form the whole org can build on. Knowledge stops being a person you can't afford to lose and becomes an asset the company owns for good.
The teams waiting this out aren't playing it safe — they're widening
the gap their competitors are already closing.
You've bought the tools. You've hit the ceiling. Now the pressure is to move — fast, and without breaking a delivery process that already works.
Discovery gives you the shortest safe path: a plan you can put in front of a board, and a number you can put in front of a CFO.
Built for teams that need AI fast, and can't afford to break their pipeline
If any of these sound like your engineering org, this is for you.
You don't trust AI output enough to scale it
AI produces real work, just not reliably enough to trust at scale. Discovery finds what's blocking reliable output on your codebase, and what it takes to fix it.
You've hit an AI ceiling on your core code
AI helps on small tasks but stalls the moment it touches core logic. Discovery shows what's transformable, what needs prep, and what to leave alone.
Your AI tools have plateaued
Big gains on the small stuff, little on the complex work that matters. Discovery finds the structural gap you're paying for, and whether it's worth closing.
You need a plan the board will back
Before you reorganize or commit budget, you need a plan you can defend. Discovery hands you one — in a shape that holds up to a CFO.
You can't afford a two-year rebuild
No rebuild from scratch, no two-year initiative. Discovery finds the highest-leverage moves for your context, not a generic playbook.
Your team is split on A
Adoption is uneven, standards inconsistent, no one owns the direction. Discovery maps where AI is actually working across your team, and what a consistent, org-wide way of working would take.
Six deliverables. All yours to keep.
No slideware. No "best-practices library" we hold the rights to.
Operational map of your delivery pipeline
How work actually moves from request to release. Where friction concentrates, which paths are revenue-critical, which points carry the highest leverage.
Codebase readiness assessment
Where AI-native development is viable today, where it needs prep, where legacy debt requires bounded rework. Prioritized by leverage and risk.
Context & specification audit
What documentation exists, where it lives, what's stale, and what must be captured — including the context in people's heads that never made it into a doc.
Transformation roadmap
A sequenced plan for 90 days, six months, and beyond. Each step earning the next. Runnable with your team, with us, or with anyone.
Cost & effort model
Engineer-months by workstream, P50/P90 timelines, where the risk sits. The cost of doing it — and of not. Numbers your CFO can work with.
Go / reshape / no-go memo
A board recommendation in three paragraphs. "Start now," "fix these first," or "not ready — here's what to do instead." We've said not yet before and will again.
How a Discovery sprint runs
Three weeks. Three stops.
The front door to our AI-Native Engineering methodology, focused into a fixed three-week engagement.
Ecosystem mapping
Codebase walkthrough, tooling inventory, docs/comms audit, stakeholder interviews, observation of current AI use. → We know the operational reality on the ground.
Depth analysis
Subsystem assessment, reverse-engineering feasibility test on one real feature, documentation-form validation, cost model buildout. → We know what would actually work in your context.
Synthesis & delivery
Roadmap assembled, memo written, all six deliverables prepared, 90-minute leadership working session. → You have a plan you can act on — with us or without us.
The same stack we install, in the room from day one
AI development environments
Claude Code
Cursor
Coder
Codex
Models
OpenAI
Azure
Gemini
Qwen
DeepSeek
Context orchestration
MCP servers
Custom skill libraries
Persona-driven prompt frameworks
Internal spec-driven-development toolkit
Evals & observability
Custom eval harnesses
LangSmith
Helicone
Promptfoo
Codebase intelligence
Tree-sitter analysis
Custom reverse-engineering harness
Semantic code search
Free 30-minute
architecture review
Before any paid engagement, we’ll spend 30 minutes pressure-testing your AI architecture or vendor proposal — no slides, no pitch. Often that’s enough to surface the next move.
Because the details decide everything
The operational reality isn't the diagram on the wall
A transformation has to be calibrated to how you actually run, not how you see yourself. Discovery closes that gap.
Context is the constraint — not code generation
Almost every AI ceiling is a context problem, not a model problem. Discovery diagnoses which context is missing, latent, or recoverable.
The right answer might be "not with this codebase — yet"
Some codebases are ready, some need prep, some are too far out. We'd rather tell you in week three than month nine.
Either side should be able to walk
A phased contract protects both parties. No one's committed beyond what's been earned.
The team in the room is the team that does the work
Senior AI engineers in the room
The same people who'd run your transformation, not consultants relaying notes.
We've installed this in production
Real infrastructure, not a theoretical framework.
18 years of engineering depth under the AI
Most "AI failures" are ordinary engineering failures. The engineering underneath is what holds up under production traffic.
AI-accelerated, and you can see it
Six weeks of consultant time compressed into three weeks of senior engineering time.
Domain depth where it matters
Ad-tech, fintech, healthcare, B2B SaaS, marketplaces, regulated workflows.
Falsifiable deliverables — and you own them
No exclusivity, no lock-in.
Independent perspective
We'll tell you "not now" when the honest read says so. That's what makes the "yes" worth trusting.
Two ways to work with us. You choose after Discovery, not before.
Discovery only
fixed three-week sprint, deliverables you own outright, take them anywhere.
Discovery + transformation
If it green-lights and you continue with us, we install the methodology with the roadmap already agreed.
Success stories of our clients
We set up AI-native development across RedTrack's ad-tracking platform
We built the AI Moderator that runs Maze's user research interviews
We're building Raivan — an AI-powered next-gen veterinary PMS for M3 VIA
We built VetLeo — an AI companion pet owners ask anything about their pet
We set up AI-native development across RedTrack's ad-tracking platform
We built the AI Moderator that runs Maze's user research interviews
Explore our
amazing case studies
Let’s build something
great together.
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