DevFlow
DevFlow is a local-first desktop platform where you describe a project in plain language and a team of AI agents plans, designs, writes, reviews, tests, and ships it — with hard engineering guarantees standing between the model and the codebase, not just prompting discipline.
Design before code
Most AI coding tools start writing the moment you hit enter, which compounds small misunderstandings into large rewrites. DevFlow adds an Architect stage first: it generates several candidate system designs — entities, API surface, pages, contracts, invariants — and runs a pairwise tournament to pick the strongest one. That winning design becomes the contract registry, a written DESIGN.md, and the task plan every coding agent works from, so the whole build is aimed at one coherent target instead of improvising page by page.
Plan → execute → verify
A PM agent turns the design into a dependency-aware task graph. Independent tasks run in parallel waves (up to three at once) through a Rust orchestrator. Every completed task passes a Code Review gate — only blocking defects (broken code, security issues, contract violations) cost a rework cycle, so reviewer nitpicks don't cascade into endless loops. A QA agent then checks the finished workspace against the original success criteria, routing any failures back to the responsible agent.
Edits that can't corrupt the codebase
Agents never rewrite whole files. Changes go through search/replace-style diff edits with exact-match validation — if the target text isn't uniquely found, the edit is rejected and the agent re-anchors instead of guessing. Every write is syntax-checked immediately, dependency names are validated against the real npm/PyPI registries to catch hallucinated packages, and a deterministic security scanner blocks convergence on hardcoded secrets, SQL string-building, eval, XSS sinks, or missing auth — no amount of agent confidence can skip that gate.
Memory instead of re-reading everything
Large codebases don't fit in a context window, so DevFlow indexes the workspace into symbols and import edges and lets agents navigate by outline and definition — pulling in one function's body and its direct references instead of ingesting entire files. Decisions, corrections, and bug fixes are written to scoped, vector-embedded memory (project-level and agent-level), so the system stops repeating mistakes across a session and across projects.
Three ways in
The same orchestrator sits behind one gateway API and ships three front ends: a Tauri desktop IDE with a real terminal and live file tree, a full-screen terminal UI for working entirely from the command line, and a LAN-served mobile PWA for reviewing progress and approving agent actions from a phone — useful for the human-in-the-loop approval gates the pipeline pauses on before merging or shipping.
Interested in working together?
laksh@lakshjain.com