AI is about to reset the economics of building software. Tower24 is building the platform for teams to work with AI agents as full team members, not tools: shared sessions, persistent context, real ownership, machine-speed execution. We've already proven the method in production. We're raising a pre-seed round to turn it into a platform.
The first wave of AI at work is autocomplete with better grammar: ask a question, get an answer, copy-paste it somewhere. It's a feature bolted onto old workflows, and it doesn't compound.
The real shift is a working relationship: continuous sessions where AI agents operate as full team members that hold context, keep memory, own tasks, and ship real work across real systems. Whoever builds the platform for that owns how the next generation of teams gets built. That's the market Tower24 is going after.
See how the model works →Two parties, each working in their zone of strength, with a hard boundary between them that keeps the work grounded.
The agent never guesses at a business decision. When it doesn't know something, it writes a clear question, tags the human, and moves on to unblocked work. The human never has to manage implementation details or remember which file changed where. Each party stays in its lane.
"Whole teams in the same agent session. Everyone sees what it's doing, and anyone can grab the wheel and course-correct."The bet Tower24 is built on
AI as a teammate resets the unit economics of building software. It wins not by working harder, but by collapsing the coordination overhead that dominates every engineering org. That's the wedge, and it's why a small team can win a big market.
Raw context in (voice notes, summaries, Slack), a structured decision doc with fill-in-the-blank questions out.
Feedback becomes scoped stories with acceptance criteria and tagged open questions, in minutes, not days.
Specialized sub-agents run at once, frontend against the contract while backend builds the schema.
Build → tests → review → dry-run → scan → merge → deploy → validate. No skipped steps.
Handoff logs mean no lost context between sessions. Say "continue" and the work resumes.
"Build this" → build → test → CR → merge → deploy → validate → next. The whole loop, measured in minutes.
The models are a commodity everyone can buy. The barrier is knowing how to turn one into a teammate, and that's what we've figured out. These operating rules are the hard-won IP the platform is built on.
The relationship is collaborative, not transactional. You're steering, not dictating.
Share the problem, constraints, and existing system. Let the agent architect the solution.
Review, decide, and course-correct, but don't micromanage implementation details.
Handoff logs, ticket states, deploy tracking. The agent holds the state so you hold the decisions.
When something breaks, the agent diagnoses and fixes in minutes. No blame, no lag, just iteration.
The agent flags unknowns and asks. The human decides. That's what keeps the work grounded.
We put the method to the ultimate test: in ~2 weeks, one human and an AI engineering team shipped real software into AWS, handling real business workflows through a real CI/CD pipeline. The bet is de-risked. What's left is to turn the method into a platform teams can adopt.
Infrastructure like ANDES Redshift, VPC, and IAM was fully provisioned. This was a working demonstration of the method, not the product we're building. The pre-seed turns this repeatable playbook into a platform.
We have a repeatable playbook and the proof it ships production software. The pre-seed does two things: turn that method into a product teams can adopt on their own, and put it in the hands of the first pilot teams. This is where the capital goes.
The models just got good enough for agents to own real work, and no one owns the way teams work with them yet. We've already run the playbook end-to-end. The window to define this category is open now, and the pre-seed is how we move before it closes.
"Don't build a tool.The thesis every investor conversation starts from
Hire a role."
To turn a proven method into the platform teams run on. If you invest at the earliest stage in category-defining companies, and you believe the next team is part human and part AI, we'd like to send you the deck and walk you through what we've built.
Request the deck ↗