Dmitry Kislov
Co-Founder & Software Engineer
20+ years Java. Built the TW AI multi-agent platform from the ground up.
About
Software should build itself.
We built the factory that makes it happen. An orchestrated swarm of AI agents handles every stage of delivery — from understanding requirements to shipping production code.
tw@totallywild — zsh
No meetings.No delays.Just working software.Multi-agent coordination.AWS-native security.Durable workflow orchestration.Enterprise and government ready.Brisbane-based AI company.No meetings.No delays.Just working software.Multi-agent coordination.AWS-native security.Durable workflow orchestration.Enterprise and government ready.Brisbane-based AI company.
Our team
Our technology
We use a multi-agent orchestration approach where specialised AI agents collaborate on every aspect of software delivery. Each agent is trained for a specific role and communicates over a shared substrate — Postgres for state, Neo4j for the task graph, and Anthropic Claude with prompt caching for the language model layer.
Business AnalystClarifies briefs, surfaces hidden requirements, produces the spec.
ArchitectDecomposes work into a task graph, picks the stack, defines acceptance criteria.
EngineersWrite code in parallel. Investigate, solve, verify. One commit per task.
ReviewerReads diffs, checks acceptance criteria, posts blocking and advisory feedback.
ResearchHandles web investigations and produces findings the others consume.
Doc writerDrafts markdown, diagrams, and slide decks from the finished artefacts.
Why we built this
Software is too slow. Most teams ship a fraction of what their customers need, because each step in delivery is a human bottleneck — requirements sit in a queue, architecture waits on a meeting, code reviews stall on availability. We rebuilt the pipeline as software.
The agents work in parallel, persist their state to disk between steps, and recover from interruption without losing progress. What used to take a team of engineers a quarter, our swarm ships in days. Building this substrate is what unlocked the speed.
What we believe
- AI should ship code, not just suggest it. Production output is the only useful metric.
- You own the code. Always. We don't host your data, we don't train on your work, we don't lock you into our runtime.
- Multi-agent review beats single-model output. A reviewer that reads diffs catches things a generator misses.
- Speed without quality is a liability. The pipeline includes testing, security review, and acceptance checks before anything ships.