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Alternatives

Products that do what Deep Work Plan does

Models matter. Context matters more. Give your agent a plan.

  1. 1
    Openbase216

    Manage your team of AI agents by voice, from anywhere

    Jul 2026

  2. 2
    N71141

    Give all your AI agents one shared context

    Jul 2026

  3. 3
    Weavable234

    Give every AI agent persistent work context

    May 2026

  4. 4

    Get real work done, moving from idea to shipping in minutes

    11d ago · arena.ai

  5. 5
    Polygraph160

    Let AI agents see cross repo and maintain session memory.

    Jun 2026

  6. 6

    Persistent memory for AI coding agents

    Apr 2026

  7. 7

    Run agent workflows the community already built

    Apr 2026

  8. 8

    Quality control for your software factory

    Mar 2026

  9. 9

    Your AI agents team, terminals, notes: one infinite canvas

    Jul 2026

  10. 10
    GPS83

    Memory layer for LLMs that stores repo rules + past lessons

    May 2026

  11. 11CA

    I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!

    Sep 2025 · infrastructureas.ai

  12. 12IM

    Hey HN, I’m Chris, a solo dev in Melbourne AU. For the past month I've been spending my after work hours building AgentVisa. I'm both excited (and admittedly nervous) to be sharing it with you all today. I've been spending a lot of time thinking about the future of AI agents and the more I experimented, the more I realized I was building on a fragile foundation. How do we build trust into these systems? How do we know what our agents are doing, and who gave them permission? My long-term vision is to give developers an "Agent Atlas" - a clear map of their agentic workforce, showing where…

    2025 · agentvisa.dev

  13. 13RA

    Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…

    Mar 2026 · github.com

  14. 14

    Coding environment and harness. BYOK. Build better.

    16d ago · voidleap.com

  15. 15LO

    Hi HN, Martin, Nils, and Jannes here. We are building Legit, an open source version control and collaboration layer for AI agents and AI native applications. You can find the repo here https://github.com/Legit-Control/monorepo and the website here https://legitcontrol.com Over the last years, we worked on multiple developer tools and AI driven products. As soon as we started letting agents modify real files and business critical data, one problem kept showing up. We could not reliably answer what changed, why it changed, or how to safely undo it. Today, most AI…

    Jan 2026

  16. 16SR

    Hello all, I'm a software developer. Over the last few months more and more of my work has turned into using coding agents instead of typing the whole code myself. Usually a few claude sessions at once, sometimes codex, one per feature or per revealed bug. I ran them in a split terminal for a few weeks, and quickly spotted two main problems. The first is that I couldn't easily tell which agent was stuck waiting on me and which was still working, so I'd cycle through sessions and checking on them. The second one: agents sharing a single branch step on each other. Two of them could be editing…

    Jul 2026 · shikigami.dev

  17. 17AR

    Hi HN. I'm the founder of Phoenix Labs (ex TikTok, Applied AI) and we're open sourcing our internal tooling today which is like a toolchain / meta-harness for CLI agents useful for really scaling eng and creative work. We are a very small team who's building a very ambitious product so we had to find ways to squeeze every ounce of efficiency that we could get our hands on. Harness strengths of different models (Claude, GPTs) and CLI-harnesses (Claude Code, Codex), safe/robust browser integration to speed up UX/QA testing, teams cli to speed up security reviews and parallelize…

    May 2026 · agents-cli.sh

  18. 18RM

    recursive-mode is an installable skill package for coding agents. It gives your agent a file-backed workflow for requirements, planning, implementation, testing, review, closeout, and memory, instead of leaving the whole process scattered in context. Long-running agent work has a common failure mode: requirements, decisions, and plans live in the conversation. Once the session ends or the context window overflows, the agent loses track of what was decided, what was implemented, and why. recursive-mode solves context rot by making repository documents the source of truth for every phase.…

    Apr 2026 · recursive-mode.dev

  19. 19IB

    Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…

    Jan 2026 · github.com

  20. 20IV

    Coding agent management is all the rage right now, and many tools are being created to fill the gap. As a power user for all tools I've used since I've started my software engineering career, I've always taken the time to test multiple tools thoroughly before deciding on one, and an agentic manager was no different. I've tested many tools, but ultimately landed on Agent of Empires (AoE for short). Why ? Because it's fast, the development is active and it's feature complete, and easy to contribute to. So I did (contribute). In my day to day workflow for my job, I need the ability to start…

    May 2026 · github.com

  21. 21IB

    The ability to synthesize a relatively short snipped of code was already demonstrated. But I thought it would be interesting to test whether GPT-4 can replace a programmer completely. To do that, AI needs to plan its actions and work on code incrementally, one piece at a time. The challenge is the context size: the entire code base + plan does not fit into the context. My approach: Add only relevant parts of the code base to the context. Specifically, AI generation engine implements two distinct phases: planning and coding. In the planning phase, GPT-4 receives a tree of tasks and a summary…

    2023

  22. 22AT

    Hi everyone! We just launched Depth AI - a tool that helps you onboard to large and messy codebases. Unlike most dev tools that help in codegen and building smaller apps, this one mainly aims at understanding large repos better - so we have focussed a lot of code search quality. We also launched the first version on product hunt https://www.producthunt.com/posts/depth-ai. Do check us out. Would love to hear feedback here and discuss more how our approach to code search is different.

    2024

  23. 23SA

    Hi HN, This is a project I've been working on since the beginning of 2025 full time, without funding. Coding agents have fundamentally changed the way we write software. When you let an agent write code, pull dependencies, and run scripts, you are delegating trust while still keeping the responsibility. You shouldn't have to choose between moving fast with agents and maintaining basic control over your host machine. Normally, we just inspect the final result, treating the app like a black box. Most security tools only sandbox the app runtime and ignore the build phase. CapaKit is my attempt…

    Jun 2026 · capakit.com

  24. 24CS

    In the following case study, the AI coding agent rebuilds a core system invariant in just three days, with minimal human input, running 31 verification passes and correcting 201 errors, before shipping code with zero bugs, zero regressions, and zero technical debt. https://aisovereignlabs.ai/docs/case-study/liveSession/case-... Disclaimers: This case study is NOT: - a project written from scratch - yet another Rust transpilation - a clone of an open-source project found in the LLM's training data - a Super Mario clone in HTML It IS: - a complex application…

    Jul 2026

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