Deep-Agnt is an interactive browser platform created by Deep-ML for practicing AI engineering. Instead of using video lessons, it offers hands-on Python problems across topics like retrieval-augmented generation, tool calling, and agent loops. Exercises run directly in the browser and test how code handles realistic failure conditions, token limits, and model errors.

How much does Deep-Agnt cost in 2026?

Deep-Agnt offers three listed pricing plans: Free at 0.00, Premium monthly at 18.00, and Premium yearly at 144.00. Based on publicly available information, specific currencies, billing intervals, and included plan features are not verified in the published directory data. Learners can try an initial problem on the platform without creating an account.

Yes. Based on publicly available information, Deep-Agnt has a free tier. A free plan usually caps how much you can use it or which features you get, and those caps may have changed since the last product update. Check the official pricing page for what it includes today before you rely on it for regular work.

Deep-Agnt vs Agents by Athena AI: what is the difference?

Practically, Deep-Agnt focuses on hands-on code execution, debugging, and engineering evaluations for Python developers building agent architectures. In contrast, feature breakdowns and operational workflows for Agents by Athena AI are not verified in the provided data. Deciding between them depends on whether you need targeted technical problem sets or alternative agent workflows.

What are the best alternatives to Deep-Agnt?

Known market alternatives in the agents category include Agents by Athena AI, Watermelon, Rumora, Mixus, and ChatNode. Direct feature comparisons, pricing differences, and exact capability tradeoffs across these platforms are not publicly available in this dataset. Prospective users should evaluate whether their priority is code-level engineering practice or managed agent tools.

Is Deep-Agnt safe for general business use?

Data privacy protections, enterprise certifications, and general business compliance policies for Deep-Agnt are not verified. The platform is designed primarily as an educational environment for writing and testing Python code against language models. Organizations with strict corporate data handling or security requirements should note that governance documentation is currently not publicly available.

Does Deep-Agnt have an API?

Not verified: API availability is not publicly verified for Deep-Agnt. Buyers should not assume a usable public API exists until the vendor publishes developer documentation or confirms access directly. Before planning an integration, verify endpoints, authentication, rate limits, pricing, support terms, and whether API access is generally available or limited to partners.

How does Deep-Agnt work?

Learners write and debug Python code directly in a browser interface across curated tracks such as foundations, agents, connections, engineering, and production. Deep-Agnt grades submissions against real language models using built-in model calls or scripted behavior. Solutions are assessed on test pass rates, token consumption, call counts, and operational efficiency.

What does Deep-Agnt do?

Practicing AI engineering through real-world software tasks forms the core function of Deep-Agnt. Users repair broken repositories, parse malformed model outputs, manage tool timeouts, and optimize retrieval pipelines. Exercises expose learners to realistic system failures using standard libraries, PyTorch, and Hugging Face models rather than passive video lectures.

Does Deep-Agnt train on user data?

Specific data training policies for Deep-Agnt are not verified, and details regarding whether submitted code or prompts are used for model training are not publicly available. Anyone submitting proprietary algorithms, sensitive prompts, or company code should exercise caution until explicit terms of service are published.

Deep-Agnt

Deep-Agnt · 总部位于 US

Practice the work of an AI engineer: fix and build RAG pipelines, tool calling, agent loops, MCP servers and evals, graded against real runs.

AI 辅助研究|数据更新于 2小时前|2 个来源|今年更新 1 次

数据更新于 2小时前2 个来源

智能体

Practice the work of an AI engineer: fix and build RAG pipelines, tool calling, agent loops, MCP servers and evals, graded against real runs.

AI 辅助研究|数据更新于 2小时前|2 个来源|今年更新 1 次

数据更新于 2小时前2 个来源

智能体

Mindber 评分™

—/10

分数待定 - 需要更多数据

解锁 30 秒结论

Mindber 评分™

—/10

分数待定 - 需要更多数据

解锁 30 秒结论

起始价格

$0起

最适合

智能体

免费试用

✓ 有免费层

月访问量

—

社媒监听

10条提及

首次收录

2026年11月7日

探索选项

看看 Deep-Agnt 如何对比

对比替代产品访问网站

Deep-Agnt is a practical fit for buyers evaluating Agents tools.

定价: freemium · 查看定价
替代方案: Agents by Athena AI v1.1.5,Watermelon,Rumora

产品信息

这个产品能做什么

Practice the work of an AI engineer: fix and build RAG pipelines, tool calling, agent loops, MCP servers and evals, graded against real runs.

来源 deep-agnt.com

兼容生态

支持平台

网页
iOS系统

公司与创作者

谁打造了 Deep-Agnt？

公司: Deep-ML (theresanaiforthat.com)
产品: Practice the work of an AI engineer: fix and build RAG pipelines, tool calling, agent loops, MCP servers and evals, graded against real runs.
总部: US
上线时间: 2026年11月

创作者尚未发布我们可以核实的公开声明。

解决的问题

Deep-Agnt 解决了什么问题？

Eliminate passive video learning by writing raw Python agent loops from scratch
Debug real failure modes like tool timeouts, malformed JSON, and retrieval defects
Practice running against live models without needing personal API keys
Optimize agents against realistic constraints on token, call, and dollar budgets

实机演示

Deep-Agnt 是否提供演示？

提供 — 下方查看演示视频。

AI 辅助研究 · 数据更新于 2小时前 · 评分方法

探索选项

Unlock preview

Score generating — full report available when data is complete

适合谁使用

买家适配度来自已批准的画像和用例证据。搜索量噪音会单独标记。

最适合的工作流

Agents

基于公开数据推断查看来源 →

Power-user

定价实况

最近更新 2026年11月

供应商定价页

起始价格

$0起

免费版可用。

套餐信息按供应商发布内容展示

Mindber 只在套餐卡片来自关联定价证据时展示具名套餐。如果套餐数据不完整，页面会回退到已列出的起始价格，而不是虚构套餐名称或 $0 档。

Free

$0/月

Every problem in the catalog
The Docs and reference solution on every problem
Unlimited submissions to scripted and local problems
Monthly credits for live grading and repair-agent turns
Your own coding agent, and your work pushed to your GitHub

Premium

$18/月

Everything in Free
33× the monthly credits
AI hints, in four levels
Access to premium projects
Interview Prep: the AI engineer track, its resume projects and timed mocks
Priority execution when it is busy

通用购买建议

适用于大多数软件订阅，并非针对该产品的发现。

自动续费通常默认开启，退款范围较窄。

Beta、Linux 或恢复类边缘场景通常没有 SLA 覆盖。

团队和商业套餐通常会转向销售报价。

一次性或终身优惠常在版本切换时消失。

你的实际成本

实时估算

使用场景所需月份

预估支出

$0

真正的成本通常来自持续订阅，而不是首月标价。

查看实时定价对比替代产品打开标准评测

价格经常变动，购买前请在供应商官网确认。

直接对比这个产品

从推荐替代品开始，或搜索另一个工具进行并排对比。

活跃度信号（30 天）

基于 6 个已关联公开条信号。

活跃度评分

评分已锁定

我们如何计算认领此资料报告不准确信息

AI 产品分析

创新度和能力评分会在该产品分析完成后显示。买家适配建议仍显示在上方的“适合谁”表格中。

右侧栏可查看分步生成日志。

流量与搜索证明

公开视图保留比例概况。付费视图解锁精确月访问量、完整地区覆盖及 CPC 级关键词情报。

Google Trends 实时关注度

Deep-Agnt 的实时 Google Trends 数据：兴趣随时间变化、地区分布、相关话题与查询。

打开 Google Trends

在 0-100 的相对兴趣区间内追踪 12 个月的 Google 搜索兴趣。

包含地区需求，方便读者了解搜索兴趣最集中的地区。

包含相关话题与相关查询，揭示相邻需求与搜索意图。

常见问题

只显示已关联的问答条目。空 FAQ 数据不会展示。

社媒提及

这里只显示已关联的公开提及证据。

10 条已关联

每月提及数

近 30 天 10 条

每月提及数
12月	0
1月	0
2月	0
3月	0
4月	0
5月	0
6月	0
7月	0
8月	0
9月	0
10月	5
11月	5

显示前 3 条，共 10 条已关联提及。

来源与方法论

只有能追溯到已关联来源记录或明确功能来源的证据才会在此展示。无来源的数据不上页面。

证据链

定价证据vendor-pricing-llm-browser90% 置信度

社媒提及增强 · 社媒提及75% 置信度

FAQ / 问答Mindber Faq Ai

已关联来源

Taaft

Deep-Agnt

评价0最近发现Nov 7, 2026

我们如何验证

Mindber 只展示能够追溯到已关联来源记录或明确功能来源的数字。证据不足时，页面会隐藏字段而不是猜测。活跃度和适配摘要会在首屏、主面板和侧栏复用同一组已审核推断，避免同一个产品出现两套说法。

评分方法论活跃度信号方法论报告数据问题

社区积分

用过 Deep-Agnt？赚取积分。

已验证的贡献能让页面保持可信。更多会员操作仍在你的仪表盘中，公开页面只保留两个最高信号的流程。

写一篇已验证评价（200+ 字）→ 赚 1 积分

分享设置背景、有效之处和遇到的问题。Mindber 奖励具体、有证据支撑的评价，而不是一句话夸奖。

写已验证评价

发现数据不正确？提交更正 → 赚 1 积分

标记过期价格、错误流量信号或失效链接，编辑团队会重新验证记录。

提交更正

创作者访问、评论、评分和验证请求仍可在你的仪表盘.

社区评测

会员观点，并非 Mindber 评估

成为第一个评测 Deep-Agnt 的会员

还没有会员评测。给它打 1 到 5 分，并分享好用与不足之处。

撰写第一条评测厂商？在此回应

关于此数据: 活跃度信号来源于公开数据。智能卡片由 AI 根据公开来源生成；其中仅适配评估、需要权衡的问题和“不适合谁”部分在发布前经 Mindber 编辑审核。评分仅反映公开更新频率，不代表产品质量、公司状况或投资价值。数据可能存在最多 7 天的延迟。了解更多

Deep-Agnt

看看 Deep-Agnt 如何对比

这个产品能做什么

谁打造了 Deep-Agnt？

Deep-Agnt 解决了什么问题？

Deep-Agnt 是否提供演示？

Unlock preview

适合谁使用

定价实况

直接对比这个产品

活跃度信号（30 天）

流量与搜索证明

Google Trends 实时关注度

流量和搜索数据待验证

常见问题

社媒提及

来源与方法论

用过 Deep-Agnt？赚取积分。

社区评测

Deep-Agnt

看看 Deep-Agnt 如何对比

这个产品能做什么

谁打造了 Deep-Agnt？

Deep-Agnt 解决了什么问题？

Deep-Agnt 是否提供演示？

Unlock preview

适合谁使用

定价实况

直接对比这个产品

活跃度信号（30 天）

流量与搜索证明

Google Trends 实时关注度

流量和搜索数据待验证

常见问题

社媒提及

来源与方法论

用过 Deep-Agnt？赚取积分。

社区评测

Deep-Agnt

看看 Deep-Agnt 如何对比

这个产品能做什么

谁打造了 Deep-Agnt？

Deep-Agnt 解决了什么问题？

Deep-Agnt 是否提供演示？

Unlock preview

适合谁使用

定价实况

直接对比这个产品

活跃度信号（30 天）

流量与搜索证明

Google Trends 实时关注度

常见问题

What is Deep-Agnt?

How much does Deep-Agnt cost in 2026?

Is Deep-Agnt free?

Deep-Agnt vs Agents by Athena AI: what is the difference?

What are the best alternatives to Deep-Agnt?

Is Deep-Agnt safe for general business use?

Does Deep-Agnt have an API?

How does Deep-Agnt work?

What does Deep-Agnt do?

Does Deep-Agnt train on user data?

社媒提及

用过 Deep-Agnt？赚取积分。

社区评测

Deep-Agnt

看看 Deep-Agnt 如何对比

这个产品能做什么

谁打造了 Deep-Agnt？

Deep-Agnt 解决了什么问题？

Deep-Agnt 是否提供演示？

Unlock preview

适合谁使用

定价实况

直接对比这个产品

活跃度信号（30 天）

流量与搜索证明

Google Trends 实时关注度

常见问题

What is Deep-Agnt?

How much does Deep-Agnt cost in 2026?

Is Deep-Agnt free?

Deep-Agnt vs Agents by Athena AI: what is the difference?

What are the best alternatives to Deep-Agnt?

Is Deep-Agnt safe for general business use?

Does Deep-Agnt have an API?

How does Deep-Agnt work?

What does Deep-Agnt do?

Does Deep-Agnt train on user data?

社媒提及

用过 Deep-Agnt？赚取积分。

社区评测