Connect with the Product Hunt community

We obsess over features, performance, and tech stack but the moment a developer can't get from "install" to "aha moment" in under 5 minutes, they're gone forever.

I've been building developer tools for a while now, and the #1 reason people churn isn't bugs. It's confusion.

Here's what I've learned:

README files are not onboarding

Are you using a dedicated tool, checking prompts manually, or not measuring this yet?

I m especially curious about:

• Which AI platforms do you monitor?

• Do you track mentions, citations, sentiment, or share of voice?

• How do you choose the prompts worth tracking?

• Have you found a tool you genuinely trust?

• What is still missing from the tools you have tried?

Would love to hear what your current workflow looks like.

Real question for anyone running coding agents daily.

I started counting how often Claude Code and Codex ask for permission during a typical session. It's around 100 prompts per hour. Read file? Yes. Run test? Yes. Lint? Yes. git push --force? Also yes if you're zoned out.

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.
Restricting access to advanced AI technologies based on geography, nationality, or policy decisions may become increasingly common in the years ahead.

If that happens, countries that are already behind in the AI race could find themselves falling even further behind.

The choices may eventually become simple:

Build and invest in your own AI capabilities
Or depend on technologies controlled by others

We ran a benchmark to see how well @Claude Code actually refactors legacy code alone and then redid the same test, but this time with code-health guidance via MCP server.

• To limit any vendor bias, we used a public data set of 25,000 source code files from competitive programming, including carefully crafted unit tests. 

• We assessed agent correctness by running those tests. 

• We measured the Code Health impact using CodeScene.

• (See our research Code for Machines, Not just Humans for more details on the methodology and data)

Claude Code that was MCP-guided achieved 2 5x more more improvements in Code Health compared to unguided refactoring.

For the last 6+ years I've been curating amazing WFH setups in a weekly newsletter called Workspaces (500+ interviews and counting!). I'll start:

2024 14-inch MacBook Pro (personal)

2024 13-inch MacBook Air (work)

I'm a non-technical founder (well, semi-technical I can read some basic code, but writing it from scratch isn't my thing).

A few weeks ago, I launched Belink, a free link-in-bio tool that competes with Linktree.

The entire thing was built using Manus, an AI agent that writes code, deploys it, and manages your project end-to-end.

The answer is yes.

Team size community engagement is the strongest predictor
B2B categories (API, Payments, Fintech) convert at 3 the baseline
Rank #1 on launch day 2.2 more likely to raise Series A

Your favorite agentic terminal @Warp is now open source!

@zach_lloyd explains the rationale here.

• Repo

• Contributing guide

• Roadmap

A lot of launch advice focuses on getting attention on day one.

But I m starting to think the harder part is what happens after the spike.

Recently our team concluded in our peer-reviewed research that that code health determines AI-performance. The study "Code for Machines, Not Just Humans: Quantifying AI-Friendliness with Code Health Metrics" concluded that when agents operate on unhealthy code, the defect risk increases by 60% (at least).

It s was a large-scale study of 5,000 real programs using six different LLMs to refactor code while keeping all tests

passing.

Makes me wonder if we're all pitching too hard and not demonstrating enough. Anyone else noticed this pattern?

We ve been seeing a consistent pattern across agent systems:

GPT-5 works well as a judge on average cases
but breaks down on edge cases and policy boundaries.

That s exactly where reliability matters.

In our recent work, we took a different approach:

You finish a session, close Cursor, come back the next day. Ten minutes gone just reconstructing where you were. Stack decisions, rejected approaches, half-finished threads.

Nobody talks about this part. Everyone optimizes the coding flow but the between-session memory problem just sits there.

Most have garbage terms lifetime deals, 70% commissions, heavy discounts. The math doesn't work unless you're already at scale, and by then you're locked into bad contracts. Wondering how many founders realize their unit economics are actually just paying off vendor debt.

Hey there,

Bit of context first: I am a member of a 30 people+ team and most API clients we used felt like they were built for a different job than what we actually did.

But the ones actually landing bigger contracts show clients what their market is saying about them first then the creative makes sense. I've been thinking about how MentionFox could be the intelligence layer agencies pitch before the deck.

How much do you spend on monthly subscriptions?

If you re already on a premium plan like Claude Max or ChatGPT Pro, stick with it, unless you really want to optimize your "vibe coding" workflow.

I spent 25 years on construction sites. Today, I don't write code I orchestrate it.

While my latest launch ('What Do I Say?') was trending on PH, I spent the afternoon using agentic loops to build a Full-Stack AI Navigation App.

The Stack:

• Backend: Real-time Google Maps/Waze data orchestration.

• UI: High-end 'Co-Pilot' dark mode dashboard with 2D/3D perspective switching.

• AI Layer: A multi-intent voice brain that handles routing, traffic interrupts, and 'Pit Stop' predictions.

• The Result: A production-grade, voice-first navigator built without writing a single line of manual code.

In MentionFox.com, we can usually identify startup founders, medical doctors, interim CEOs/CFOs, professional sports players, recruiters 29 personas we have built custom war rooms for we call them Fox Dens: your home for engagement, for developing yourself in the public s reagrd as a though leader in your chosen carreer path* you can self-declare persona, though we usually deduce from info you provide in the onboarding. 

* Coming Soon: tools for those who have no effing idea what to do with their lives.

great indication on where they see the biggest opportunities right now.
Here is the latest list:
1. AI for Low-Pesticide Agriculture
2. AI-Native Service Companies
3. AI Personalized Medicine
4. Company Brain
5. Counter-Swarm Defense
6. Dynamic Software Interfaces
7. Electronics in Space
8. Hardware Supply Chain
9. Industrial Capabilities in Space
10. Inference Chips for Agent Workflows
11. SaaS Challengers
12. Software for Agents
13. Startups That Want to Sell to Huge Companies
14. Supply Chain 2.0 for Semiconductors
15. The AI Operating System for Companies
details here: https://www.ycombinator.com/rfs

I have been noticing a lot of fake testimonials on many of the recently launched products. It went from mild annoyance to pure concern. Wrote a small piece on it. I would love if every one of us starts calling it out more.
Link to the article if anyone is interested : https://medium.com/design-bootca...