This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
I built Zagens because I kept hitting the same loop: the agent writes code confidently, I find a hallucinated function name three files deep, and suddenly I'm spending an hour auditing everything it touched. It didn't mean to break things — it just has no way to verify its own work.
The problem isn't model IQ. We dropped superhuman autocomplete into an engineering workflow with no code review, no CI, no "are we actually done?" — just tokens and on to the next turn.
So instead of waiting for a smarter model, I built the engineering layer around it — a Windows harness, not prettier chat bubbles:
If you've wrestled with agents that sound confident but ship broken code — what verification patterns have you wired into your own workflow? Would love to hear it. 🙏
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About Zagens on Product Hunt
“Desktop agent harness for DeepSeek V4”
Zagens was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #33 on the daily leaderboard. Agents quit early — patches land, tests still red. Zagens harnesses DeepSeek V4 on Windows: phased runs, review loops, verify before done. • Phased work — checklist, auto-continue, gates before steps close • Review pipeline — explore, implement, review; loops on failure • One window — tree, terminal, diffs, turn-by-turn replay • Cost panel — tokens, cache hits, savings per session • Approvals, skills, MCP — you control risky scripts & tools Local-first. BYOK. Windows preview.
Zagens was featured in Productivity (653.8k followers), Developer Tools (514k followers) and Artificial Intelligence (471k followers) on Product Hunt. Together, these topics include over 311.7k products, making this a competitive space to launch in.
Who hunted Zagens?
Zagens was hunted by Jason Lin. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Zagens stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Jason Lin
Hey Product Hunt 👋
I built Zagens because I kept hitting the same loop: the agent writes code confidently, I find a hallucinated function name three files deep, and suddenly I'm spending an hour auditing everything it touched. It didn't mean to break things — it just has no way to verify its own work.
The problem isn't model IQ. We dropped superhuman autocomplete into an engineering workflow with no code review, no CI, no "are we actually done?" — just tokens and on to the next turn.
So instead of waiting for a smarter model, I built the engineering layer around it — a Windows harness, not prettier chat bubbles:
• Multi-agent pipeline — explore (read-only), implement, review; failed review loops back automatically
• Verification gates — builds, tests, and grep weigh in before a step is marked done
• Long-session discipline — checklist, auto-continue, turn-by-turn replay so work doesn't quietly drift
I also merged Office (Excel, Word, PowerPoint, PDF) into the same app — I was tired of switching between AI and document tools.
Local-first preview · BYOK · keys stay on your device · built for DeepSeek V4 (OpenAI-compatible too). Not affiliated with DeepSeek Inc.
zagens.com · [email protected]
If you've wrestled with agents that sound confident but ship broken code — what verification patterns have you wired into your own workflow? Would love to hear it. 🙏