AI didn’t arrive with a clean break from the past. It arrived sideways. At first as autocomplete, then as copilots, and now as something closer to collaborators. Code is written faster than ever. Architectures are sketched in seconds. Entire systems can be simulated before a single line is committed.
And yet, despite all of this acceleration, the projects that succeed still share one thing in common: someone has to be responsible for the outcome.
At Treevine Organization, we’ve been watching this tension closely—the growing power of agentic AI on one side, and the very human need for judgment, prioritization, and accountability on the other. What’s emerged from that tension is a new way of working, and with it, a new kind of development agreement.
Not bigger. Not looser. Not more automated.
Just more honest.
Why the Old Contracts Don’t Fit Anymore
Traditional development contracts assume a world that no longer exists. Either they expect long, linear builds where everything is known upfront, or they promise fixed outcomes that quietly ignore how discovery actually works.
Early-stage development doesn’t behave that way. Especially now.
When you’re exploring something new—an AI-enabled system, a hybrid hardware–software idea, or a product that hasn’t yet proven it deserves to exist—certainty is the wrong goal. What you need instead is a controlled way to find out what’s real.
That’s where most contracts fail. They optimize for deliverables instead of truth.
A Different Kind of Agreement
Treevine’s engagements are built around a simple premise: define the time, define the budget, and commit to real, focused human engineering effort. Everything else follows from that.
AI plays a central role, but not an autonomous one. We use modern agentic tools—Claude Code, Gemini, ChatGPT, and emerging AI-first development environments—to accelerate execution, explore options, and stress-test ideas quickly. But orchestration remains human-led.
Decisions are made deliberately. Trade-offs are surfaced, not hidden. Progress is measured by integration and behavior, not slide decks.
This is not about “letting AI build your product.”
It’s about using AI to move faster without losing the steering wheel.
Grounding the Work in a Real Standard
To avoid ambiguity, we anchor every engagement to something older and far more conservative than AI hype: NASA’s Technology Readiness Levels.
TRLs were designed for systems where failure is not an option, and they offer a rare gift in modern development—clear language for where you actually are.
Here’s the reference point we use:
| TRL | Phase | What It Means | Example |
|---|---|---|---|
| 1–2 | Research | Paper studies, no building | “I have an idea” |
| 3–4 | Concept | Lab experiments, separate pieces | “We proved X is possible” |
| 5–6 | Prototype | Integrated system in realistic conditions | “Here’s a functioning demo” |
| 7 | Pilot | Operational environment | “Beta users are testing it” |
| 8–9 | Production | Proven, deployed, scaled | “It’s live and shipping” |
Treevine operates deliberately in the middle of this chart—the part where ideas either become real or quietly disappear.
We start by helping partners move through TRL 3 and 4, bringing the data acquisition and data analytics needed to prove that an idea is not only plausible, but measurable. Assumptions are replaced with signals. Claims are stress-tested against reality. By the time this phase is complete, something important has shifted: the conversation moves from what might work to what demonstrably does.
From there, we transition into agentic development. Modern AI models and agents accelerate integration, iteration, and exploration, but always under human orchestration. This is where we make a hard commitment: a 90-day guarantee to build a working prototype and carry the system through TRL 5 and 6.
The founders we work with tend to arrive with something rare—a genuinely strong technological idea.
What “Early-Stage Development” Really Means
Early-stage development is not about polish. It’s about proof.
At the end of this phase, you don’t have a mass-market product. You have something far more valuable: a working prototype that runs end-to-end in realistic conditions. Something you can demonstrate to investors without hand-waving. Something early users can touch. Something that either validates your direction—or tells you to change it while it’s still cheap.
Technically, this is TRL 5–6. Practically, it’s the moment where ideas stop being hypothetical.
The 90-Day Commitment
Treevine engagements are time-bound by design. We commit to a 90-day path to prototype, assuming active collaboration and timely decisions from the client.
This isn’t about speed for its own sake. It’s about respecting momentum.
Three months is long enough to build something real, and short enough to prevent drift. At the end of that window, there is no ambiguity. You will know what works, what doesn’t, and what comes next.
That clarity alone often determines whether a project moves forward—or wisely stops.
Human-Led, Even Now
AI can write remarkable code. It can propose architectures, analyze trade-offs, and simulate behavior at a scale no human team could match.
What it cannot do is take responsibility.
Someone still has to decide what matters, what to ignore, and when “good enough” is actually good enough. Treevine exists in that space—between founders and machines—where judgment still matters.
Not louder. Not flashier. Just grounded.
A Simple Invitation
If you’re sitting at that in-between moment—past the idea stage, not yet at production—and you want to know whether your system truly works, we should talk.
Reach out to Treevine Organization to request a link to book a 30-minute technical conversation.
Embark on a discussion about where you are, and what’s realistic next.