Alternatives
Products that do what AI Engineer’s Field Guide does
A practical playbook for designing production AI systems
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The best AI design agent to go from idea to production
Apr 2026 · magicpatterns.com
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- 3MA
I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
2025 · aicode.danvoronov.com
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Curated resources on how AI is reshaping Design Systems
Jan 2026
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- 6AS
Hi HN, I’m a former C++ dev turned Product Manager. I’ve noticed many engineers struggle with the "politics" side of things when they become Leads. To help with this, I’m building a text-based simulator. It is NOT an AI chatbot. It is a hand-crafted, branching narrative (logic tree) based on real experiences. I just launched the first scenario: "The Backchannel VP." The Setup: Your VP Engineering is bypassing you and giving tasks directly to your juniors, causing chaos. Your Goal: Stop the backchanneling without getting fired. It’s a short, specific puzzle. I’d love to know if you think the…
Jan 2026 · apmcommunication.com
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Turn real workflows into safe, measurable AI systems
26d ago · github.com
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Learn how AI is actually built, tested, and shipped
May 2026 · danielhightower.gumroad.com
- 10IA
Hello HN! My name is Max, and I’m a co-founder at Lynx (https://uselynx.ai). We’re building an AI-powered incident resolution platform to help engineers debug and resolve on-call issues faster. If you’ve ever been paged in the middle of the night and had to spend hours piecing together logs, metrics, and code, we’d love your feedback. * The Problem * On-call hasn’t kept pace with modern engineering. Even with great observability tools, diagnosing incidents is slow because: - Systems are increasingly complex. - Logs, dashboards, and documentation are scattered. - Context often…
2025
- 11FA
Built Figr AI because I got tired of AI builder tools market themselves as design tools and end up skipping the hard part. Every tool I tried would jump straight to screens. But that's not how product design actually works. You don't just design screens. You think through the problem first. The flows, the edge cases, the user journey, where people will get stuck. Then the design comes finally. Figr does that thinking layer first. It parses your existing product via a chrome extension or takes in screen-records, then works through the problem with you before designing. Surfaces edge cases,…
Jan 2026 · figr.design
- 12GT
Hi folks, I built this guide after watching AI agent prototypes repeatedly fail in production. It demonstrates transforming a monolithic marketplace assistant into a resilient multi-agent system using orra, an open-source platform I also built for production-ready multi-agent applications. The patterns shown are valuable *even if you're building your own orchestration layer*. Each stage builds on the previous one, showing the evolution from fragile prototype to resilient system. What makes this guide valuable: * Architectural transformation with working code examples - split monolithic…
2025 · github.com
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Build zero-latency AI products for the next billion users.
Jun 2026 · rumiza07.gumroad.com
- 14AA
I'm a VP of Engineering with 20 years in the field. I've been thinking deeply on why AI is breaking every engineering practice, and it led me to the conclusion that the Agile Manifesto's values need updating. The core argument: AI made producing software cheap, but understanding it is still expensive. The Manifesto optimizes for the former. This addendum shifts the emphasis toward the latter. Four updated values, three refined principles, with reasoning for each. Happy to discuss and defend any of it.
Mar 2026 · github.com
- 15SF
Hi HN, Over the past two years I’ve built and debugged a fair number of production pipelines—mainly retrieval‑augmented generation stacks, agent frameworks, and multi‑step reasoning services. A pattern emerged: most incidents weren’t outright crashes, but silent structural faults that slowly compromised relevance, accuracy, or stability. I began logging every recurring fault in a shared notebook. Colleagues started using the list for post‑mortems, so I turned it into a small public reference: 16 distinct failure modes (semantic drift after chunking, embedding/meaning mismatches,…
2025 · github.com
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we had hundreds of discussions with engineering leaders over the past few months, and everyone's trying to understand where they are in the AI journey. we collected all this data into a benchmark and built a free grader to let you know where you stand. you answer on a 1–5 scale (e.g., autonomy runs from "suggestions only" to "agents own multi-hour workflows across code, infra, and external systems") - takes about 5 minutes. https://agent-benchmarks.com/software-factory/ waiting for your results!
Jul 2026 · agent-benchmarks.com
- 18FT
Hey HN! When implementing an AI-powered feature for a project, we—and many people we've talked to—often reach a point where we have to choose an AI model but aren’t sure which one best fits our constraints or where to even start. Unfortunately, the advice to "just use chatgpt" is not always a good one. What if I want an open-source model? What languages does it support? What about context window size or the number of parameters? There are thousands of AI models already out there and many of them are perfect for certain problems. That’s why we’ve carved out this part of our product as a free…
2024 · app.elementera.ca
- 19AG
I’ve been building LLM tooling for a small VC fund and found myself explaining the same mental model over and over to non-technical people around me: how a stateless LLM becomes a chatbot, how tool use works, what an agent is mechanically, and why context windows shape all of it. I never found a guide that covered that full chain at the level I wanted, so I wrote one. It’s nine short chapters, each building on the last. Deliberately simplified: the goal is a useful mental model, not a textbook. Feedback, corrections, and contributions welcome: github.com/ymyke/aiaiai
Apr 2026 · aiaiai.guide
- 20GC
Hey HN, I built ProductMap AI, a tool that automatically identifies features implemented in source code and organizes them in a visual hierarchy. The goal is to help developers quickly understand poorly documented codebases. Link: https://product-map.ai/ I’d love feedback from the HN community! Let me know what you think. Would this be useful for you?
2025 · product-map.ai
- 21IB
Oct 2025 · github.com
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Free AI workflow guides for professionals who hate hype
13d ago · github.com
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