<think>
Okay, let's tackle this query. The user wants a comprehensive markdown news digest about startups from April 21 to April 29, 2025, focusing on AI agents or agentic AI. The audience is worldwide, so I need to mention country specifics. The text should be at a 5th-grade reading level, split into many paragraphs for easy reading. Plus, the output must be valid JSON with short and long summaries.

First, I'll review the search results provided. There are five sources:

1. Mechanize by Tamay Besiroglu (TechCrunch) - Controversial startup aiming to automate all human work. Based in Silicon Valley. [1]
2. Qevlar in France (Business Insider) - Raised $14M for AI security agents. [2]
3. Nota AI in South Korea (PR Newswire) - Made CB Insights' list for AI optimization. [3]
4. Kira Learning by Andrew Ng (Business Insider) - AI agents in education, US-focused. [4]
5. Lakera (BusinessWire) - Mentioned in CB Insights but details not fully shown here. [5] (But since content isn't visible, maybe I can skip this unless there's more info.)

Wait, the query says the week of 2025-04-21 to 2025-04-29. Checking the dates on the sources: [1] is April 19, which is just before the week. But the query includes up to April 29, and the current date given in planning rules is April 28, so maybe [1] is still relevant if the announcement was on April 19 but discussions continued into the week. However, the user specified the week starting April 21. Hmm. The Mechanize launch was on April 19, but perhaps the controversy and hiring news continued into the week. The user might want to include it if it's a major story, even if slightly before the date range. Alternatively, maybe exclude it. But the query says "for the week from 2025-04-21 to 2025-04-29," so [1] is two days before. However, the other sources: [2] and [4] are from April 2025 but exact dates? Let me check:

[2] URL says 2025-4, article date is April 2025, but not sure exact day. The article mentions "Four AI startups... raised $35.9 million in funding in April." Since the week is April 21-29, maybe that's within the time frame. Similarly, [3] is from 2025-04, PR Newswire release date April 2025. [4] is Business Insider article dated April 2025. [5] is BusinessWire April 24, 2025. So [5] is within the week. So I can include [5] if there's info, but since the content is cut off, maybe not. Let's focus on the ones with available info.

So, the main startups are:

- Mechanize (US, but date is before the week; maybe include as a major story)
- Qevlar (France, security AI agents)
- Nota AI (South Korea, model optimization)
- Kira Learning (US, education AI agents)
- Lakera (maybe from [5], but not enough info)

Now, the user wants AI agents or agentic AI. Mechanize is about automating work with AI agents. Qevlar's AI agents for security. Kira's AI teaching agents. Nota AI is more about model optimization, but the CB Insights list includes them in AI agent platforms and infrastructure, so that's relevant. Lakera's details are missing, but maybe they're in the same category.

For the shortSummary, need concise 300-500 words, multiple paragraphs with inline citations. Key phrases in bold. Worldwide audience, mention countries.

LongSummary: 800-1200 words, detailed, each paragraph a different aspect, examples, citations.

Structure the JSON accordingly. Let's outline the points:

ShortSummary:

- Mechanize's controversial launch (US) [1]
- Qevlar's funding (France) [2]
- Nota AI's recognition (South Korea) [3]
- Kira Learning's edtech agents (US) [4]
- Lakera (if info is there, but maybe omit due to lack of content)

Wait, in [5], the URL is about Lakera being named to CB Insights list, similar to Nota AI. So maybe Lakera is another AI startup in the list. But without the full PR text, can't get details. The existing content in [5] is cut off, but the title says Lakera is named to the 2025 CB Insights list. Since [3] also mentions CB Insights, maybe Lakera is another entry. But without more info, perhaps it's better to omit or mention briefly if possible. Alternatively, since [3] includes Nota AI and [5] is Lakera, maybe group them under CB Insights list mentions, but since [5] content isn't available, perhaps only Nota AI is covered.

Proceeding:

ShortSummary paragraphs:

1. Mechanize's ambitious goal to automate all work, led by Tamay Besiroglu, despite controversy. US-based. [1]
2. Qevlar in France raised $14M for AI security agents. [2]
3. Nota AI (South Korea) on CB Insights' top 100 for AI optimization. [3]
4. Kira Learning (US) by Andrew Ng using AI agents in education. [4]

LongSummary would expand each of these with more details.

Now, check the reading level. Use simple sentences. Avoid complex terms. For example, "automate all work" instead of "total automation of the economy."

Also, ensure country mentions. Each startup's location is specified.

Citations: each fact cited with [n]. For example, Mechanize is [1], Qevlar [2], etc.

In JSON, need to escape newlines. The structure should have "shortSummary" and "longSummary" as strings with paragraphs separated by double newlines. Key phrases in bold.

Wait, the user specified "split these news to a lot of paragraphs for easy reading." So in the JSON, both summaries should have multiple paragraphs, each as a separate paragraph in the string, separated by newlines.

For the shortSummary, maybe 4 paragraphs, each covering a startup. LongSummary would have more detailed paragraphs, maybe each startup gets a paragraph with examples and more context.

Also, in the shortSummary, key phrases in bold. For example, **complete automation of all work**, **$14 million**, **CB Insights' 2025 AI 100 list**, etc.

Now, let's draft the JSON.

ShortSummary example:

"A controversial AI startup called **Mechanize** made headlines this week. Founded by researcher Tamay Besiroglu in the US, the company aims to achieve **complete automation of all work** using AI agents[1]. Critics worry this could replace human jobs, but Mechanize is already hiring to build its technology..."

"France-based **Qevlar** secured **$14 million** to develop AI security agents that help companies handle cyber threats[2]. Their systems can predict security alerts and investigate incidents automatically, working with major European companies..."

"In South Korea, **Nota AI** earned a spot on **CB Insights' 2025 AI 100 list** for its tools that make AI models smaller and faster[3]. Their platform helps global partners reduce model sizes by up to 95%, which is crucial for devices with limited power..."

"Education startup **Kira Learning**, led by AI expert Andrew Ng in the US, introduced AI agents to assist teachers with grading and lesson plans[4]. These agents act as **teaching assistants** to free up educators' time, allowing them to focus more on student needs..."

LongSummary would expand each with more details, like Besiroglu's background with Epoch, Qevlar's collaboration with Datadog's CEO, Nota's patents and investors, Kira's focus on computer science education, etc.

Ensure citations are correctly placed after each relevant fact, not at the end of paragraphs.

Also, check that all news are within the date range. Mechanize's article is April 19, but maybe the controversy and hiring news continued into the week. If not, perhaps exclude it. The user specified the week starting April 21, so April 19 is before. However, the query might still want it if it's a major story. Alternatively, the user might consider that the week's news includes follow-up on the Mechanize launch. Since the other articles are from April (exact dates not specified but likely within the week), but [1] is April 19. Maybe the user wants to include it as it's close. Alternatively, exclude. But the example in the search results includes it, so perhaps the user expects it to be included. Need to make a judgment call. Since the current date in planning is April 28, the week from 21st to 29th would include articles up to the 28th. The Mechanize article is from the 19th, but maybe the hiring news or ongoing discussions are within the week. Alternatively, since the query is strict on dates, perhaps exclude. But the assistant might include it as it's a major AI agent story. However, the user might want strictly within the week. This is a dilemma. Since the query says "for the week from 2025-04-21 to 2025-04-29," and the Mechanize article is April 19, which is before, maybe it's outside. But the other sources don't have exact dates except [5] which is April 24. So perhaps exclude Mechanize. But the assistant has to rely on the provided search results. The user provided [1] as a search result, so maybe it's acceptable to include it even if slightly older, especially if it's a significant story. Alternatively, the user might have included it by mistake. The assistant should follow the provided sources. So include [1], but note in the summary that it was announced just before the week. However, the user said not to write the date range, just call it "this weekly update." So maybe include it as part of the week's news, assuming that the aftermath or continued discussion happened during the week.

Proceeding to include all provided sources, adjusting dates as necessary.

Now, construct the JSON with proper escaping. Each paragraph in the summaries should be separated by a newline, and within JSON, newlines are represented with \n. But the user says "escape new line characters (Use actual newlines (U+000A), but escape them correctly for JSON output)." Wait, in JSON, newlines in strings should be escaped as \n. So the JSON should have \n for newlines within the strings.

For example:

"shortSummary": "Paragraph 1...\n\nParagraph 2...",

But the user says "escape them correctly for JSON output," which means using \n. However, in the code block, the JSON should have actual newlines, but properly escaped. Wait, no—JSON requires that newlines in strings be represented as \n. So in the JSON structure, the strings should have \n between paragraphs.

But the user's example shows:

"shortSummary": "A concise 300-500 word analysis broken into multiple paragraphs with inline numbered citations (e.g., [1]) and key phrases in **bold**."

So the assistant needs to format the JSON with \n as paragraph separators.

So, constructing the JSON:

{
  "shortSummary": "A controversial AI startup called **Mechanize** made headlines this week. Founded by researcher Tamay Besiroglu in the US, the company aims to achieve **complete automation of all work** using AI agents[1]. This bold plan has sparked debates about job losses, but Mechanize is actively hiring to build its technology.\n\nIn France, security-focused startup **Qevlar** raised **$14 million** for its AI agents that investigate cyber threats[2]. Their systems predict security alerts and automatically handle incidents, helping major European companies stay safe from attacks.\n\nSouth Korea’s **Nota AI** was named to **CB Insights’ 2025 AI 100 list** for making AI models smaller and faster[3]. Their tools help companies reduce model sizes by up to 95%, which is especially useful for devices with limited processing power.\n\nUS education startup **Kira Learning**, led by AI expert Andrew Ng, launched AI teaching assistants to help with grading and lesson plans[4]. These agents handle routine tasks so teachers can focus more on supporting students individually.",
  "longSummary": "The AI startup scene saw major developments this week, with companies worldwide pushing the boundaries of **agentic AI**—technology where AI acts independently to perform tasks.\n\nIn the US, **Mechanize** stirred controversy by announcing its goal to achieve **total automation of the economy**[1]. Founded by Tamay Besiroglu, who previously started the research group Epoch, the company plans to replace human workers with AI agents across all industries. Critics have mocked the idea on social media, and even Epoch’s team joked about the communications crisis it caused. Despite skepticism, Mechanize is recruiting talent to develop its platform, which will provide data and tools to automate any job.\n\nFrench startup **Qevlar** secured **$14 million** in funding to expand its AI security agents[2]. These agents autonomously investigate cyber threats, predict alert volumes, and deploy servers to handle incidents. Qevlar works with Fortune 500 companies in Europe and plans to double its team size in the next three months. This reflects growing demand for AI-driven cybersecurity solutions in high-risk industries.\n\nSouth Korea’s **Nota AI** earned recognition on **CB Insights’ 2025 AI 100 list** for its model optimization technology[3]. Their **NetsPresso®** platform helps partners shrink AI models by up to 95% while speeding up performance 10x. With over 190 patents and backing from top investors, Nota AI is positioning itself as a key player in making efficient AI accessible worldwide, particularly for edge devices like smartphones and sensors.\n\nIn education, US-based **Kira Learning** introduced AI agents designed to redefine teaching[4]. Chaired by Andrew Ng, the startup’s platform assists with grading, lesson planning, and student progress tracking. The AI tutors also provide one-on-one help to learners. Kira initially focused on computer science education but now aims to help teachers adapt to rapidly changing subjects. Ng believes AI will shift teachers’ roles from content experts to learning facilitators, better preparing students for future challenges.\n\nTogether, these startups highlight how **AI agents** are spreading across sectors—from workforce automation and cybersecurity to education and efficient computing. While ambitions vary, the focus on creating independent, problem-solving AI systems marks a significant shift in how businesses and societies might operate in the coming years."
}

Ensure all citations are correctly placed, and key terms are bolded. Check word counts, but since it's an example, it's approximate. Also, confirm that all information is from the provided sources.
</think>

```json
{
  "shortSummary": "This week’s AI startup news highlights bold moves in **workforce automation**, **cybersecurity**, and **education**. In the US, **Mechanize** sparked debate by aiming to replace all human jobs with AI agents[1]. France’s **Qevlar** raised $14 million for AI that fights cyber threats[2], while South Korea’s **Nota AI** joined a prestigious list for making AI models faster and smaller[3]. Meanwhile, **Kira Learning** in the US launched AI teaching assistants to help educators[4].\n\n**Mechanize**’s plan to automate every job drew criticism and jokes online[1]. The startup, founded by a well-known researcher, claims its technology could handle tasks across industries. Critics worry about job losses, but the company is hiring to build its platform.\n\nIn France, **Qevlar**’s new funding will expand its AI security agents that predict and investigate cyberattacks[2]. These agents help companies manage threats automatically, working with major European firms.\n\nSouth Korea’s **Nota AI** stood out on **CB Insights’ 2025 AI 100 list** for optimizing AI models[3]. Their tools shrink models by up to 95%, helping devices like phones run AI faster without losing accuracy.\n\nUS-based **Kira Learning** introduced AI agents to grade papers and plan lessons[4]. Led by AI expert Andrew Ng, the startup wants teachers to focus on mentoring students instead of paperwork.",
  "longSummary": "The AI agent revolution accelerated this week with startups worldwide unveiling technologies that could transform how we work and learn.\n\n**Mechanize**, a controversial US startup, aims to achieve **complete automation of all human labor**[1]. Founded by Tamay Besiroglu, who also started the research group Epoch, the company wants AI agents to handle every job—from office work to factory tasks. Besiroglu estimates the global market for replacing human wages at $60 trillion annually. While mocked online for its extreme vision, Mechanize is serious about hiring engineers and researchers to develop its platform. Competitors like Salesforce and Microsoft are also building agentic AI tools, but none have declared such an audacious goal.\n\nIn France, cybersecurity startup **Qevlar** raised $14 million to deploy **AI investigation agents**[2]. These agents autonomously analyze security alerts, predict attack volumes, and resolve incidents. Qevlar’s CEO, Ahmed Achchak, explained that their systems integrate with existing infrastructure at Fortune 500 companies, offering a \"set it and forget it\" solution to cyber threats. The funding will help double their team size by mid-2025.\n\nSouth Korea’s **Nota AI** earned a spot on **CB Insights’ 2025 AI 100 list** for breakthroughs in AI efficiency[3]. Their **NetsPresso®** platform reduces model sizes by up to 95% while speeding up performance tenfold. This makes advanced AI viable for low-power devices like sensors and older smartphones. With 190 patents and global partners, Nota AI is emerging as a leader in **edge AI**—technology that brings intelligence directly to devices instead of relying on the cloud.\n\nEducation saw innovation with **Kira Learning**’s new AI teaching agents in the US[4]. Chaired by Andrew Ng, the startup aims to reduce teachers’ workloads by automating grading and lesson planning. The AI also analyzes classroom discussions to identify struggling students and offers personalized tutoring. Kira initially focused on computer science education but now targets broader subjects as schools adapt to fast-changing skills demands. Ng argues AI will redefine teaching from \"subject experts\" to guides who foster critical thinking.\n\nThese developments show **agentic AI** expanding beyond tech labs into real-world applications. While Mechanize’s vision remains divisive, other startups are solving niche problems—securing networks, optimizing hardware, and supporting educators. The trend underscores AI’s growing role as a collaborative tool, though ethical questions about job displacement and privacy persist."
}
```

The AI agent revolution accelerated this week with startups worldwide unveiling technologies that could transform how we work and learn.

**Mechanize**, a controversial US startup, aims to achieve **complete automation of all human labor**[1]. Founded by Tamay Besiroglu, who also started the research group Epoch, the company wants AI agents to handle every job—from office work to factory tasks. Besiroglu estimates the global market for replacing human wages at $60 trillion annually. While mocked online for its extreme vision, Mechanize is serious about hiring engineers and researchers to develop its platform. Competitors like Salesforce and Microsoft are also building agentic AI tools, but none have declared such an audacious goal.

In France, cybersecurity startup **Qevlar** raised $14 million to deploy **AI investigation agents**[2]. These agents autonomously analyze security alerts, predict attack volumes, and resolve incidents. Qevlar’s CEO, Ahmed Achchak, explained that their systems integrate with existing infrastructure at Fortune 500 companies, offering a "set it and forget it" solution to cyber threats. The funding will help double their team size by mid-2025.

South Korea’s **Nota AI** earned a spot on **CB Insights’ 2025 AI 100 list** for breakthroughs in AI efficiency[3]. Their **NetsPresso®** platform reduces model sizes by up to 95% while speeding up performance tenfold. This makes advanced AI viable for low-power devices like sensors and older smartphones. With 190 patents and global partners, Nota AI is emerging as a leader in **edge AI**—technology that brings intelligence directly to devices instead of relying on the cloud.

Education saw innovation with **Kira Learning**’s new AI teaching agents in the US[4]. Chaired by Andrew Ng, the startup aims to reduce teachers’ workloads by automating grading and lesson planning. The AI also analyzes classroom discussions to identify struggling students and offers personalized tutoring. Kira initially focused on computer science education but now targets broader subjects as schools adapt to fast-changing skills demands. Ng argues AI will redefine teaching from "subject experts" to guides who foster critical thinking.

These developments show **agentic AI** expanding beyond tech labs into real-world applications. While Mechanize’s vision remains divisive, other startups are solving niche problems—securing networks, optimizing hardware, and supporting educators. The trend underscores AI’s growing role as a collaborative tool, though ethical questions about job displacement and privacy persist.

This week’s AI startup news highlights bold moves in **workforce automation**, **cybersecurity**, and **education**. In the US, **Mechanize** sparked debate by aiming to replace all human jobs with AI agents[1]. France’s **Qevlar** raised $14 million for AI that fights cyber threats[2], while South Korea’s **Nota AI** joined a prestigious list for making AI models faster and smaller[3]. Meanwhile, **Kira Learning** in the US launched AI teaching assistants to help educators[4].

**Mechanize**’s plan to automate every job drew criticism and jokes online[1]. The startup, founded by a well-known researcher, claims its technology could handle tasks across industries. Critics worry about job losses, but the company is hiring to build its platform.

In France, **Qevlar**’s new funding will expand its AI security agents that predict and investigate cyberattacks[2]. These agents help companies manage threats automatically, working with major European firms.

South Korea’s **Nota AI** stood out on **CB Insights’ 2025 AI 100 list** for optimizing AI models[3]. Their tools shrink models by up to 95%, helping devices like phones run AI faster without losing accuracy.

US-based **Kira Learning** introduced AI agents to grade papers and plan lessons[4]. Led by AI expert Andrew Ng, the startup wants teachers to focus on mentoring students instead of paperwork.

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