Scott AI Wants Your Coding Agents to Argue Before They Build

Ask a founder in Y Combinator's Fall 2025 batch what breaks when a coding agent gets good, and most will describe the same scene. The agent writes a thousand lines before lunch. Then three engineers spend the afternoon figuring out whether those lines were the right ones. Scott AI, a New York company founded in 2025, was built for that afternoon.

The pitch is short enough to fit on a napkin: coding agents are getting absurdly good at writing code, but engineering teams are not getting absurdly good at coordinating around them. Agents now produce roughly ten times the code they did a year ago. The humans reviewing that code, and deciding what it should be in the first place, are still working at their old pace. Scott AI calls itself the planning layer for teams that build with coding agents, and it exists to close that gap on the planning side rather than the typing side.

01 / THE IDEAMake the agents disagree, on purpose

Most tools in this category race toward a single answer as fast as possible. Scott AI does something closer to the opposite. It runs several coding agents side by side, gives them secure access to a codebase, and lets each one explore a different design path. Then it surfaces where they disagree.

That disagreement is the point. When two capable agents look at the same problem and pick different architectures, that fork is usually the exact spot where a human should be paying attention. Scott turns those forks into a comparison a team can actually decide from: here are the tradeoffs, here is what each path costs, pick one. Only after the spec is settled does the work get handed to an execution tool such as Claude or Cursor.

It is a subtle inversion of how these products usually feel. A single agent gives you one answer and a lot of confidence, and confidence is exactly the thing you cannot audit. A swarm that disagrees gives you something more useful: a map of the decisions that were made silently, quickly, and without anyone in the room weighing in. Scott's interface is built to make those hidden decisions visible before they harden into code that someone has to unwind later.

02 / THE PROBLEMThe bottleneck moved

For most of software's history, the constraint was output. Typing was slow, so anything that made engineers type less was valuable. Coding agents flipped that. When an agent can draft an entire feature in minutes, the scarce resource is no longer keystrokes. It is agreement - a team knowing, before the build starts, that they are all pointing at the same target.

Left unmanaged, that mismatch produces a familiar mess. Five agents, five confident opinions, no shared plan. Code that compiles but solves the wrong problem. Review queues that grow faster than anyone can drain them. Scott AI's wager is that the next wave of engineering productivity comes from fixing coordination, not generation.

03 / THE FOUNDERSTwo engineers who scaled other people's platforms

Scott AI was started by David Maulick and Devin Cintron. Maulick, the CEO, was a staff engineer and manager at Coinbase, where he built developer platforms that reportedly powered 95% of the company's UI and around 65% of its edge traffic, used by more than 700 engineers a day. His job, in other words, was already coordination at scale - making it easier for a large group of people to build in the same direction.

Cintron, the CTO, was a founding engineer and head of mobile at Comun, a fintech backed by Redpoint and Costanoa, where he helped scale the product from zero to millions of installs. He studied computer science with an AI focus at Stanford and did earlier stints in consulting at Bain. The through-line between the two is unglamorous but relevant: both spent their careers on the plumbing that lets teams move together, which is precisely the problem Scott now sells.

04 / THE PRODUCTPlan mode, with more than one brain

The company frames its core feature as "Coding Agent Plan Mode with Super Powers." Underneath the phrase is a discovery layer that runs multiple coding agents in parallel across a codebase, has them debate architecture and design decisions, and pulls the key divergences into the interface. Builders compare the competing approaches, weigh the tradeoffs, and choose - then the chosen plan goes downstream for execution.

The practical promise is threefold: reach a good specification faster, get a team aligned faster, and let coding agents take on larger and more complex tasks without drifting from intent. None of that requires Scott to write the final code. It requires Scott to make the decision that comes right before the code.

There is a reason the founders keep circling the word "spec." A specification is where intent and implementation meet, and it is also where most projects quietly go wrong. Get it right and the agents can run hard without supervision. Get it vague and every downstream tool amplifies the ambiguity, ten times faster than before. Scott is trying to be the place where a team pins the spec down while it is still cheap to change, rather than discovering the gaps in review, or in production.

05 / THE MARKETA small, contrarian corner of a loud category

AI developer tooling in 2026 is crowded and loud. Cursor, Claude Code, GitHub Copilot Workspace and Cognition's Devin all compete on how much they can build for you. Scott AI sits deliberately upstream of that fight. Its competitors are, in a sense, also its handoff partners: the tools that execute once Scott has helped a team decide what to execute.

That positioning is a bet on where value moves next. If code generation keeps commoditizing, the durable advantage shifts to whoever helps humans decide faster and with less friction. Scott is a three-person team in New York arguing that the planning layer is that place. Whether the market agrees is the open question, but the reasoning is clean.

There is also a defensibility angle hidden in the neutrality. A tool that plugs into every agent and favors none of them is harder to displace than one more code generator competing on raw speed. The more agents a team runs, the more it needs something to sit above them and referee. If that turns out to be true, being early and neutral is a better place to stand than being fast and locked-in. It is a quieter kind of moat, and Scott seems comfortable with quiet.

06 / WHAT'S NEXTEarly, and honest about it

Scott AI is seed-stage, backed by Y Combinator with Garry Tan as its primary partner, and it came out of stealth in late 2025 to a friendly reception from other builders. Pricing and detailed traction numbers are not yet public, which is normal for a company this young. The team is hiring product and design engineers in New York with equity in the 0.5% to 2% range, the usual signal of a founding-stage company handing out real ownership.

What Scott AI is selling is not more code. It is the moment before the code, when a team and its agents figure out what they are actually building. If that moment turns out to be the expensive one in the agent era, a small workspace that makes it faster could matter more than its headcount suggests.