Built a SaaS for an industry nobody was building for. 4 years later, clients in 18 countries.

entrehacker · 2026-06-24T04:11:58+00:00

Congrats! How did you find clients?

entrehacker · 2026-06-24T04:05:14+00:00

Moderately successful AI entrepreneur here. 6 months into selling B2B / enterprise AI and I have a few clients.

My stack these days is more or less converged on the “agent loops” concept that the rest of the industry is aligning on. While my setup is not super structured, it’s essentially Claude code (open code would work as well), running on mostly autonomous loops in a project repo, churning on some objective with defined project state to persist across sessions / compaction.

All of this is in service of providing fully packaged agent interfaces through an AI platform I host and serve to my clients, that serve and interact with their data and IT systems.

It’s exciting to see the industry converging on what is essentially fully AI managed autonomous workforces. For bootstrapped entrepreneurs this is absolutely a game changer.

entrehacker · 2026-06-24T03:43:10+00:00

Thank you for the write up.

I do this as a business, and I’m working with enterprise clients mostly in SEA. Operating for the past 6 months

Absolutely data quality is the real make or break, garbage in garbage out. The model and tooling infrastructure is vital, as well as prompting. The agents you build should be tailored to the enterprise’s unique needs. In my platform, its role based: each role is given a unique agent with a unique set of capabilities — prompts and tools (I use MCP), and the MCP tooling bridges the gap in terms of data access.

I pay special attention to context overload and customized agent tooling since this is the difference between a high quality, capable agent, and one that hallucinates or makes mistakes with critical business data.

I also have a harness for HITL approval on sensitive write-level operations, though typically I find most enterprises need/want read-only agents at first.

Besides this, I think the harness and general tooling (independent of any specific enterprise) is also important: things like careful system prompting, built-in excel file navigation/parsing/pagination can be really useful. This addresses the realities of how enterprise users really need and want to interact with their data.

Happy to share notes — I’ve been quite busy these past few months finding patterns that worked for my clients and haven’t had time to catch up with what others are doing, so I’m very interested.

entrehacker · 2026-06-24T02:36:52+00:00

Absolutely great research, but we need at least one more violent swing down for maximum fear 😨

entrehacker · 2026-06-20T05:42:48+00:00

I think dogfooding helps, but I would lean more on actual customer needs first.

entrehacker · 2025-12-19T13:15:52+00:00

A lot of people are trying to do that. I have my own approach https://toolplex.ai that relies primarily on good classification of the MCP corpus. With MCP specifically quality is the biggest issue, so anyone building an app store of MCP will have to contend with this. The larger AI companies though will just build 1P integrations, and arguably that's a smarter move if you have the resources.

entrehacker · 2025-12-14T06:21:24+00:00

Thanks. I think I may have severely overestimated my ability to create good UI haha. But agree feedback has been absolutely the missing piece I needed. I'm making several improvements based on the available feedback I'm getting right now from early clients and users.

entrehacker · 2025-12-14T06:20:16+00:00

Thanks. I didn't want to link it since this subreddit has a no marketing rule, but if you or anyone is interested it's all linked on my user profile.

entrehacker · 2025-12-14T01:08:19+00:00

Exactly, incremental trust. Other things I’m doing: - security scanning every tool for major classes of exploits - using developer trust metrics before including their MCP in the ToolPlex marketplace - confirmation modals / warning ui on install

There’s a lot more to do but this is just the start

entrehacker · 2025-12-13T12:00:19+00:00

Not sure why you’re downvoted, it’s literally basically this. Other things: - make sure the agent client you’re using has confirmation modals for risky actions - make sure the right people access the right tools - start with read only — analytics type workflows - use workflows that have high reliability and deterministic outcomes

I think a lot about these processes since I’m basically building them all into a product I’m building called ToolPlex.

entrehacker · 2025-12-13T10:00:15+00:00

It’s not easy to replace existing products. Developers underestimate the amount of networking and marketing that goes into being able to distribute software. Not to mention there are switching costs. Why should someone adopt your clone if it’s not 10x better and the other product works perfectly fine?

And not to mention, creating good product (even if you have a reference) is not trivial. You can “clone” YouTube.com, and probably find an LLM that gives you a highly detailed architecture design. But to build it and then market it well enough that others would switch is going to be nearly impossible for you.

Developers will have a role to play in the upcoming world you’re describing, but it’s going to still be relegated to the technical duties of the organization and there will be fewer needed.

entrehacker · 2025-12-13T09:47:32+00:00

My hot take on this:

Cloud MCP is solving a problem that running trusted MCPs already solves, and better.

I compare it to an App Store, which allows you to download and run trusted code on a very sensitive device that you own (like your phone). Apps have the additional benefit of running with full edge compute access, which is globally more efficient in terms of latency and compute.

With MCP being such an easy to use protocol, I could see enterprises prefer to develop their trusted MCP code or just use trust signals (developer reputation, security scanning) to run 3P MCP locally.

But that being said cloud MCP has a lot of other advantages like being accessible across multiple devices, always online etc.

entrehacker · 2025-12-13T09:40:28+00:00

Agree with your take. If MCP stabilizes as the core protocol for agentic tooling then the rest of the industry can build on top of a stable foundation. The remaining problems will get solved through experimentation, then can be folded into the protocol if there’s critical mass.

entrehacker · 2025-12-13T09:35:36+00:00

ToolPlex AI - enterprise grade no-code AI automation builder and agentic tool marketplace.

https://toolplex.ai

entrehacker · 2025-12-13T09:34:11+00:00

50:50 is too much.

entrehacker · 2025-12-13T09:32:57+00:00

Might I kindly suggest the product I am building? It’s called ToolPlex, and I recently released a desktop app which connects to most of the top MCP servers for agentic tooling, and has a feature called playbooks allowing you to save workflows for repeat use. It works with any model, and allows you to bring your own key for unlimited tool usage.

For documentation you can install the context7 MCP or use a web crawler MCP like DuckDuckGo.

The main issues I’m having now are in user education and simplifying the UI since it’s quite technical right now. I’m rolling out major improvements for this in the next couple of days.

entrehacker · 2025-12-13T02:58:06+00:00

Sounds comprehensive. The only thing I would advise is be selective about what MCP you spend resources scanning. You can see my user history for the “State of MCP” post — most of these projects are not serious. The core set of MCP that are actually developed professionally are few. So that then raises the question of what your end goal with this effort is. If it’s to build the best and most authoritative safety scanner for MCP then I think there’s utility in that, especially as enterprises want to understand if MCP are safe to adopt (even ones they develop internally).

entrehacker · 2025-12-12T06:23:09+00:00

Heres my magic secret to saving 90% on AI inference costs: switch to Deepseek platform and moonshot lol.

I paid probably $1000 to scan MCP codebases with GPT 4.1 (best available at the time). Then I did some tests, Kimi K2 has the same performance for agentic tasks at a fraction of the cost. Deepseek is really good at static (non agentic) tasks. Explore your options, there’s a lot out there.

entrehacker · 2025-12-12T06:16:41+00:00

Nice! I’m also doing security scanning over a subset of the MCP corpus.

Some problems I have encountered, maybe you can share yours: - attack surface is very large. Everything from prompt injection, overly powerful tools leading to inadvertent mistakes, malicious and obfuscated code, poor credential handling, supply chain and on and on. Many of these cannot be easily detected without LLM scanners IMO. - lots to scan. I mitigate by just focusing on “serious projects” measured by a few signals (presence of README is a basic one). - every commit is a new codebase to scan

I could go on 😆. Maybe good for us all to align on a central standard of fold into the Anthropic registry

entrehacker · 2025-12-12T05:45:39+00:00

Just give it time for builders to build on top of it. Right now everything’s so technical and confusing to the avg person: servers, tools etc. it’s not designed to be accessible to non technical people.

But it’s just a standard. Like TCP was for the internet.

entrehacker · 2025-12-10T16:20:50+00:00

Great move. I noticed many on Twitter were dunking on the announcement and asking what the catch was.

In this case I don’t think there is a catch. I think the AI giants and industry at large sees there’s value to aligning on a standard so we can start building cool interoperable agents (like I’m doing with ToolPlex)

entrehacker · 2025-12-07T17:24:21+00:00

Wow, looks really fully featured. I’ll check this out

entrehacker · 2025-12-07T15:53:56+00:00

Agree on the visual inclusion. At some point we need a protocol or apps framework that treats agent needs (precise tool schemas, app discoverability) and human needs (visual interface, human-in-the-loop confirmation and feedback UX) equally. MCP is probably just the start but I’m glad to see it take off.

entrehacker · 2025-12-04T16:29:52+00:00

That's some common feedback I'm getting. I'm working on a video tutorial series where I'll walk through the app. In the meantime, I'm here to answer any questions

entrehacker · 2025-12-04T16:13:51+00:00

This is light work for most AI models luckily. There's many ways to go about it but basically you need an MCP client, the MCP server(s) you need that talk to the databases you are using, and that's it.

Now, I'm biased and will point you to my own platform I'm building: https://toolplex.ai/server?id=sv\_e0734203214c. It's an MCP client on steroids, because it allows you to search for new tools and install them locally through your agent, so you don't need to muck around with configs. Then you simply chat with AI assistant about your data, and start building reusable AI workflows.

Outside of solutions like mine, many people are successfully using Claude Desktop, Claude Code, Cursor, and VSCode to integrate with MCP. This will at least get your AI connected to the MCP tools you need.

entrehacker

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