u/Original_Iron7191

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I'm a full-stack engineer focused on AI systems, backend infrastructure, and agentic workflows. I enjoy building from 0→1, working directly with founders, talking to users, and shipping fast.

What I've worked on:

- AI agent systems and evaluation frameworks

- Full-stack apps with TypeScript, Next.js, FastAPI, PostgreSQL, and Redis

- Backend APIs, automation, and developer tooling

I'm looking for:

- Early-stage (idea, MVP, or early revenue)

- Cash + meaningful equity

- High ownership and fast execution

- Remote preferred, open to relocation for the right team

If you're building something ambitious and need an early engineer,pls DM me.

I will share my work over DM.

I’m open to joining an early-stage startup as a co-founder/founding team member if the idea, people, and problem are a strong fit.

If you’re building something ambitious, DM me. Would love to hear what you’re working on.

I'm a software engineer looking to join an early-stage startup as a Founding Engineer.

For founders and early startup employees:

• What made you hire your first or second engineer?
• What skills or qualities mattered more than experience?
• Where have you found strong Founding Engineers outside your own network?

I'm particularly interested in 0→1 product development and would like to understand what founders actually look for when making these hires.

I'd appreciate hearing about your experience from either side of the table.

I've been wondering how other teams handle this.

One thing I've run into is that after changing a prompt or switching models, an agent can start making different decisions without anyone noticing. For example, it might approve something it previously rejected, miss an escalation, or classify a case differently. The conversation still looks reasonable, so the regression is easy to miss.

Most of the evaluation tools I've seen focus on conversation quality or benchmark scores. What I'm struggling with is verifying that the agent still makes the same business decision for important cases.

For teams building production agents that make decisions like approve/reject, escalate, or classify:

• How are you testing for these regressions today?
• Are you relying on manual testing, eval frameworks, custom scripts, or something else?
• Have you had any production incidents caused by prompt or model updates?

I've been building an internal CLI to test this by replaying real cases against an agent and checking whether the decision still matches the expected policy. It's been useful for me, but I'm mainly interested in learning how others are solving the problem before deciding whether it's worth taking further.

Curious to hear what workflows people are using.

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Hey,

I'm a software engineer based in India looking to join an early-stage startup as a Founding Engineer or Technical Co-founder.

I've been spending most of my time building AI products and developer tools. My stack is React, TypeScript, Node.js, Python, and PostgreSQL. I've also built multi-agent systems and worked with LLM APIs.

I'm not looking for a big company or a comfortable job. I want to work with founders who ship fast, talk to users, and are obsessed with building.

Remote is fine, and I'm open to relocating if it's a good fit.

If you're building something and need someone to own the product from the engineering side, send me a DM. I'd love to hear what you're working on.

I'm a technical builder (full-stack + AI) looking to connect with people building AI SaaS or enterprise AI products.

If you're:

- brainstorming a new idea,

- validating an MVP,

- or already building something and need a technical co-founder,

I'd love to chat.

I'm comfortable owning the technical side (shipping product, AI systems, backend, frontend) and can also help with fundraising, investor materials, and early-stage strategy.

Not looking for "idea guys" I'm interested in people who've identified a real problem and want to build something meaningful.

If that sounds like you, drop a comment or send me a DM. Happy to brainstorm even if we don't end up working together.

Hi everyone,

I'm looking for a founder who's building something ambitious and is looking for a technical co-founder.

I've built AI products, enjoy shipping fast, and want to work with someone who's obsessed with solving a real problem. I'm less interested in the domain and more interested in the founder's conviction, speed, and willingness to build.

If you're a solo founder who needs someone to own the technical side, brainstorm product decisions, and build from day one, I'd love to talk.

I'm open to founders from anywhere in the world.

If this sounds like you, send me a DM.

Let's build something people can't live without.

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I'm a full-stack AI engineer looking to join an early-stage startup as a Founding Engineer or Technical Co-founder.

I enjoy building from zero to one and have experience with:

- AI agents & LLM applications

- Next.js, FastAPI, PostgreSQL, Redis

- Shipping end-to-end products quickly

- Working directly with founders in fast-moving startup environments

I'm primarily looking for remote-first startups and am open to equity-heavy opportunities if the team and problem are compelling.

If you're building something ambitious or know a team that's hiring, DM me and I'm happy to share my background, GitHub, and projects.

I'm a software engineer based in India and I'm trying to break into early-stage US startups (YC-backed or similar).

I've been building full-stack and AI projects, contributing to my GitHub, and reaching out to founders directly, but I'd like to learn from people who actually made the jump.

A few questions:

- What made the biggest difference in getting interviews?

- Did cold DMs to founders work, or were job boards more effective?

- How important was open-source work compared to personal projects?

- If you were starting from scratch today, what would you do differently?

I'd appreciate practical advice from people who've successfully landed a US startup role while living outside the US.

I'm building in this space, so take this with that context.

I kept seeing the same failure mode: someone updates a system prompt, switches models, or changes a tool, and the agent starts making different decisions. Nobody notices until a real user gets the wrong outcome.

Think of things like:

Approving a refund that should've been denied.

Missing a high-priority support escalation.

Approving a loan that violates policy.

To catch this before deployment, I built a small CLI.

You give it a system prompt and your expected policy. It runs the agent through test scenarios and flags cases where the agent's decision doesn't match what should happen.

The first time I tried it on a medical triage agent, it failed to tell someone with stroke symptoms to seek emergency care. On another agent, it approved a loan for an applicant with a prior default.

I'm not claiming this is a new category. Teams like Coval and Cekura are already doing good work, especially around conversation quality and voice agents.

The problem I'm focused on is simpler: did the agent make the right decision according to policy?I care less about whether the conversation sounded natural and more about whether the final action was correct.

If you're building agents that approve, reject, escalate, or otherwise take real actions, how are you testing them today?

If you're open to it, I'm happy to run this against one of your agents for free. No pitch. I just want to understand whether this solves a real problem or if I'm optimizing for something nobody actually needs.DM me if you wanna test it

I'm building in this space, so take this with that context.

I kept seeing the same failure mode: someone updates a system prompt, switches models, or changes a tool, and the agent starts making different decisions. Nobody notices until a real user gets the wrong outcome.

Think of things like:

Approving a refund that should've been denied.

Missing a high-priority support escalation.

Approving a loan that violates policy.

To catch this before deployment, I built a small CLI.

You give it a system prompt and your expected policy. It runs the agent through test scenarios and flags cases where the agent's decision doesn't match what should happen.

The first time I tried it on a medical triage agent, it failed to tell someone with stroke symptoms to seek emergency care. On another agent, it approved a loan for an applicant with a prior default.

I'm not claiming this is a new category. Teams like Coval and Cekura are already doing good work, especially around conversation quality and voice agents.

The problem I'm focused on is simpler: did the agent make the right decision according to policy?I care less about whether the conversation sounded natural and more about whether the final action was correct.

If you're building agents that approve, reject, escalate, or otherwise take real actions, how are you testing them today?

If you're open to it, I'm happy to run this against one of your agents for free. No pitch. I just want to understand whether this solves a real problem or if I'm optimizing for something nobody actually needs.DM me if you wanna test it

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Building an AI infrastructure startup and targeting YC Winter 2027.

I'm looking for a full-time non-technical co-founder with strong enterprise GTM and customer development experience.

We're currently in the validation stage, so I care far more about someone who is obsessed with talking to customers, uncovering painful problems, closing design partners and pilots, and shaping the product than someone focused only on marketing.

I already have an AI infrastructure idea, but if you have a stronger idea backed by customer insight, I'm completely open to pivoting. The goal is to build the best company, not defend a specific idea.

I'll lead the technical side (building the product) and fundraising, while you own customer discovery, enterprise sales, and GTM.

Open to candidates from the US, India, UK, Canada.

If this sounds like you, DM me with:

- Your background

- Why you want to build a company

- Any enterprise problems or ideas you're excited about

Building Relio made one thing obvious: a great product isn't enough without great distribution.

I'm looking for a non-technical co-founder to own GTM, sales, partnerships, and fundraising .(Equity only)

If you're hungry to build a category-defining AI company from zero, DM me for more details

Hey I am looking for a technical Co founder, building ai saas product. Mvp is ready, applying for YC and equity will be discussed.

DM if you are interested