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Zenflow

orchestrate coding agents without "you're right" loops

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Hi HN, I’m Andrew, Founder of Zencoder.While building our IDE extensions and cloud agents, we ran into the same issue many of you likely face when using coding agents in complex repos: agents getting stuck in loops, apologizing, and wasting time.We tried to manage this with scripts, but juggling terminal windows and copy-paste prompting was painful. So we built Zenflow, a free desktop tool to orchestrate AI coding workflows.It handles the things we were missing in standard chat interfaces:Cross-Model Verification: You can have Codex review Claude’s code, or run them in parallel to see which model handles the specific context better.Parallel Execution: Run five different approaches on a backlog item simultaneously—mix "Human-in-the-Loop" for hard problems with "YOLO" runs for simple tasks.Dynamic Workflows: Configured via simple .md files. Agents can actually "rewire" the next steps of the workflow dynamically based on the problem at hand.Project list/kanban views across all workloadWhat we learned building thisTo tune Zenflow, we ran 100+ experiments across public benchmarks (SWE-Bench-*, T-Bench) and private datasets. Two major takeaways that might interest this community:Benchmark Saturation: Models are becoming progressively overtrained on all versions of SWE-Bench (even Pro). We found public results are diverging significantly from performance on private datasets. If you are building workflows, you can't rely on public benches.The "Goldilocks" Workflow: In autonomous mode, heavy multi-step processes often multiply errors rather than fix them. Massive, complex prompt templates look good on paper but fail in practice. The most reliable setups landed in a narrow “Goldilocks” zone of just enough structure without over-orchestration.The app is free to use and supports Claude Code, Codex, Gemini, and Zencoder.We’ve been dogfooding this heavily, but I'd love to hear your thoughts on the default workflows and if they fit your mental model for agentic coding.Download: https://zencoder.ai/zenflow YT flyby: https://www.youtube.com/watch?v=67Ai-klT-B8

HN · launched Dec 16, 2025 · 33 upvotes (top 26%) · 0 views

Niche: ai agent development platforms · 598 launches, 24 in the last 7 days ▼ -23% · Explore this niche →

Category and tags

  • Horizontal
  • Agent / copilot
  • Developer
  • AI-native
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

Partial A frontend UI for coordinating prompts is straightforward, but robust agent orchestration that prevents loops requires formal state machines, deterministic verification harnesses, and deep LLM telemetry.

What it would actually take: The orchestration platform requires an execution engine (e.g., Temporal or custom DAG runners) coupled with headless sandboxed development environments (Docker/Firecracker). It requires parsing ASTs to verify agent outputs deterministically, linting/running tests in isolated containers, and enforcing guardrail loops using evaluation heuristics. Systems engineering and distributed systems reliability expertise are critical.

Discussion

20 comments analyzed.

Competitors mentioned: Cursor, vibe-kanban, v0

Concerns raised: No Linux version, API abuse risk with certain features for free tier, How to compete with vendors like Cursor that have highly tuned prompts by programming language, Pricing value proposition unclear when bringing own LLM keys

Feature requests: View/edit built-in workflow prompt files directly instead of starting from scratch, Ralph Wiggum-style continuous loop workflow support, Pre-built workflow templates for common patterns like Implement > Review > Fix, Gallery for workflows so users can pick best one for specific situations

Competitors

Other products that read as similar to this one : 2048 launches clear the similarity bar, closest 8 shown.

Attention rank: #653 of 2049 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 48 days after the earliest competitor.

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