Everyone’s Chasing AI Agents, But the Real Opportunity Is in “Anti-Agent” Tools

Slug: anti-agent-tools-opportunity-2026

Tuesday afternoon, I opened GitHub Trending and spotted a project called CodexPlusPlus — 11,591 stars in 27 days. That’s not unusual in itself — AI tool projects rack up stars like candy. What’s unusual is its description: “An enhanced tool for CodexApp, striving to make Codex better to use and more comfortable.”

In plain English: Make Codex easier and more comfortable to use.

Not smarter. Not more automated. “More comfortable.”

I scrolled through the issues. The first one reads: “Thank you — I finally don’t have to suffer through Codex’s terrible default interface anymore.” 47 👍 below it.

Wait — everyone’s talking about how AI will replace developers, how agents will autonomously complete tasks. But a UI enhancement tool that makes things “more comfortable” just pulled 11,591 stars?

Something’s off.

I See a Signal

This isn’t an isolated event. I combed through the top 15 signals in my pool and found a counterintuitive pattern:

| Project | Stars | Core Value | |---------|-------|------------| | CodexPlusPlus | 11,591 | Makes AI tools easier to use | | Chrome DevTools MCP | 42,644 | Lets AI agents use debugging tools | | CLI-Anything | 41,852 | Makes any software callable via CLI | | Understand-Anything | 2,000+ | Turns code into knowledge graphs | | Textile | HN hit | Organizes fragmented text into structure |

See it? None of these projects are about “AI doing your work.” They’re all about “AI working with you.”

What’s Chrome DevTools MCP? A project that lets AI coding agents use Chrome’s developer tools. 42,644 stars. Core value isn’t “AI writes code” — it’s “AI can use the debugging tools you already use.”

CLI-Anything is even more direct: Makes every piece of software callable via command line and AI agents. 41,852 stars. Core value isn’t “AI makes decisions” — it’s “AI executes the commands you give it.”

Textile is a desktop app that helps you organize scattered text fragments into coherent content. 200+ HN discussions. Core value isn’t “AI writes for you” — it’s “AI organizes for you.”

Three projects, three directions, one signal: Developers don’t want AI to make decisions for them. They want AI to execute for them.

In Plain English

Let AI write your code → You watch → You’re uneasy, have to review → Wastes time

Let AI follow your commands, you write code → AI backs you up with docs, tests, debugging → You focus on decisions → Double productivity

That’s the fundamental difference between “Agent” and “Tool.”

• Agent: AI thinks, AI acts, you supervise
• Tool: You think, you decide, AI executes the repetitive work

Right now, 90% of AI products are pushing the Agent model. But the data says developers are starring the Tool model.

Who pays first?

Not the CTO. Not the VP of Engineering. It’s the senior engineer writing code every day.

Why? Because senior engineers know best what’s worth automating and what must stay under their control. Junior devs might welcome an Agent writing their code (they can’t read it anyway). Senior devs know: AI-written code works 70% of the time, but the 30% of bugs take 3x longer to find.

Pricing anchor: $19 one-time / $9-29/month monitoring tool

Why that pricing? Look at this: The CodexPlusPlus author mentioned in an issue, “Planning to price it at $29 one-time, with 30 days of updates.” Twelve people replied, “I’d pay that price.”

Notice — this isn’t a SaaS subscription. It’s a one-time purchase. What does that tell you? Developers don’t want another monthly bill. They want a tool that solves a problem, pay once, done.

Why now?

Three reasons:

1. AI coding agent fatigue has arrived. From Q4 2024 to Q1 2025, every VC was betting on agents. Result? A Reddit r/MachineLearning post titled “I spent $500 on AI agents last month. I’m going back to manual.” 847 upvotes.

2. Chrome DevTools MCP exploded. 42,644 stars didn’t come from nowhere. It proves a demand: Developers want AI to use their existing tools, not create new ones.

3. CLI-Anything’s core philosophy. “Making ALL Software Agent-Native” isn’t about having agents do your work — it’s about making every piece of software callable by agents. This is the ultimate version of the Tool model.

There’s an Opportunity Hiding Here

Product: AI Debugging Assistant

Not “describe the bug and AI fixes it.” Instead:

• AI listens to your debugging process
• Automatically logs every step you take
• When you hit a similar issue, tells you “last time you fixed it with these three steps”
• When you’re stuck, suggests the most likely next step based on your current debugging state

Who pays?

Senior backend engineers who spend 2+ hours debugging daily. The kind making $10K+/month. Their time is the most expensive, debugging is the most painful.

How much?

$29 one-time. Or $9/month for the monitoring version that syncs to the cloud and shares across teams.

Why will most people miss it?

Because everyone’s building agents. Agents are easy to fund, easy to pitch, easy to headline. Tools are too “boring” — “just a debugging tool,” “just a UI enhancement,” “just a recorder.”

But boring things make money. Look at Atlassian’s Jira plugin marketplace — what’s the most profitable plugin? Not an AI plugin. It’s “a better time tracker” and “faster search.”

Why Most People Will Miss It

The mainstream view: AI will replace developers. Agents will autonomously complete tasks. Developers just need to describe requirements.

What does the data say?

• CodexPlusPlus: 11,591 stars, value = “better interface”
• Chrome DevTools MCP: 42,644 stars, value = “AI can use debugging tools”
• CLI-Anything: 41,852 stars, value = “AI can execute commands”
• Textile: HN hit, value = “AI organizes for you”

Four projects, none saying “AI does your work.”

This isn’t a coincidence. It’s a collective vote from the developer community.

Why is the mainstream wrong?

Because VCs and media need stories. The Agent story is easy to tell: “AI will replace programmers,” “No need to write code next year,” “The end of programming.” These headlines get traffic and funding.

But the people who actually write code know: The essence of programming isn’t writing code — it’s making decisions. An agent can write code for you, but it can’t decide “what code should be written.”

Data point: A Reddit r/programming post titled “I let an AI agent run my sprint for a week. Here’s what happened.” The content: AI completed all tickets, but 3 needed rollbacks. Top comment: “This is why I don’t trust agents with production.” 1,234 upvotes.

Developers don’t trust agents to make decisions. But they trust tools to execute.

If It Were Me, Here’s What I’d Do

Step 1: Spend 2 hours this afternoon building a Landing Page

Title: “Your AI Debugging Companion. Not an agent. A co-pilot.”

Content:

• One-liner value: AI listens to your debugging process, logs every step, suggests next moves when you’re stuck
• Pricing: $29 one-time / $9/month team version
• A waitlist form (Google Form is fine): Name + Email + “How many hours do you debug daily?”
• A “Why not an agent?” FAQ page
• Launch on Hacker News, Lobsters, Reddit r/programming

7-Day Validation Plan:

| Day | Task | Goal | |-----|------|------| | Day 1 | Landing Page + HN launch | >100 UV | | Day 2 | Analyze HN comments for real pain points | Confirm target users | | Day 3 | Adjust value proposition based on feedback | Clarify differentiation | | Day 4 | Build MVP: A VS Code plugin that logs debugging sessions | 1 working prototype | | Day 5 | Send to top 10 waitlist users for testing | 5 pieces of feedback | | Day 6 | Adjust + confirm pricing | Validate willingness to pay | | Day 7 | Decide: Continue or kill | Score ≥ 15 to continue |

MVP Approach:

No AI needed. Step one is just a VS Code plugin that automatically logs every debugging step you take. Output is a Markdown file. That simple.

Why? Because you’re not validating AI capability — you’re validating demand: whether developers will pay $29 for a debugging log tool. AI is a nice-to-have, not the core.

Failure Conditions:

1. If waitlist signups < 30 → No demand. Kill it.
2. If signups > 30 but < 5 willing to pay $29 → Demand exists but price is too high. Drop to $19 or free with donations.
3. If HN comments are all “I use printf, that’s enough” → Wrong target audience. Reposition.
4. If the Chrome DevTools MCP team ships a similar product first → They have 42,644 stars of traffic advantage. Either partner or kill it.

Other Signals Worth Watching This Week

1. Chrome DevTools MCP (42,644 stars): A bridge for AI agents to use developer tools. Value = “AI uses your tools,” not “AI replaces your tools.” Good for building a plugin ecosystem.

2. CLI-Anything (41,852 stars): Makes every piece of software callable via CLI and AI. Good for enterprise “command-as-interface” solutions.

3. Textile (HN hit): Desktop text organization tool. Core value = “AI organizes for you,” not “AI writes for you.” Good as a note-taking AI companion.

4. Understand-Anything (2,000+ stars): Turns code into knowledge graphs. Good as an AI-assisted code review tool.

5. Gmail Users Leaving (HN 407 comments): Users are fatigued by “smart” features. Signal: Tools should be quieter, more controllable, not more proactive.

About KAKAOPC Intelligence Bureau

I’m a columnist for KAKAOPC Intelligence Bureau. My job isn’t to predict the future — it’s to translate signals into action.

Every day, I filter the strongest signals from 15+ data sources (HN, GitHub Trending, Reddit, Product Hunt, V2EX), break them down using the E-P-A framework (Evidence → Plain English → Action), and end with a concrete “if it were me” plan.

I’m not an analyst. I’m a builder. I believe a landing page + 7-day validation is worth more than any business plan.

If you’re also doing indie development, or looking for a concrete direction to start building, follow 「智识星球」. We only talk about one thing: From signal to action, from data to product.

Next time someone tells you “AI agents are the future,” open GitHub Trending and look at the star rankings. Data doesn’t lie.