Report by The Next New Thing.
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Software ships as a finished app, not as source code, so when you see a feature you want to understand you are mostly guessing. REA is an MCP server — the plug that lets AI tools talk to outside software — that hands your coding agent real inspection tools, so it can open the app on your own machine and explain how that feature actually works.
View on GitHub →The README table runs from native binaries and Android apps to Electron apps, .NET, websites, saved network traffic, firmware and SQLite files.
Analysis runs locally, and REA returns the code, references and remaining unknowns behind a finding instead of a confident-sounding summary.
In the DX-Ball case study the rebuilt sound-pan function passes 3,205 original x86 test cases and reproduces all 63 bytes of the compiled original.
Curated reverse-engineering tools and learning resources for binaries, apps, firmware, formats, and protocols.
Composable mathematics tools for agents
Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.
“I pointed it at a famous game and got back a working copy in one file. Reverse engineering for regular people.” About 7 minutes, and it needs Node 22 or newer.
Open Ravi’s run → rea-test.codeshiftagent.comThe biggest thread on this week’s show, and the fight is on three fronts at once. Front one is “does this add anything?” — one commenter asks how REA beats just telling Claude to install Ghidra yourself, and the reply thread lands on “probably it is not better… aimed at people who do not have a current RE methodology,” with somebody renaming the whole category “vibe-reverse-engineering.” Front two is grief: a hobbyist RE argues the tool “kinda just… totally eliminates that as a hobby entirely,” tearing apart the communities that formed around slow manual teardowns. Front three is legal — “the lawyers at all those companies will be readying their lawsuits.” And the very first comment mocks the install: “We have achieved the next evolution of installation by curl pipe bash.”
Read the discussion →AnyPS5 rewrites a PS5 game's program file into the native format Linux, Windows or macOS already understands, so the title runs as an ordinary app rather than inside an emulator. The repo opened on 3 August 2026 and is already at 38.5k stars with 408 contributors, which is most of the story: this is a fast-moving work in progress, not a finished product.
View on GitHub →A relinker converts the executable into the target system's own native format, and the project ships its own PS5 system libraries to link against.
The project's GitHub Pages site hosts an online relinker, and the README says your files never leave your device. The CLI adds Windows and macOS output.
Today the project's own badges read 88.83% for system libraries and 100.0% for shaders, and a community blocker map tracks how far each individual game gets.
Two arguments worth putting on screen. The first is survival: the top comment is people setting up private mirrors and self-hosted Forgejo instances because “they may eventually be taken down through legal threats eg, Yuzu and Ryujinx,” and others point at Sony cease-and-desist letters. The second is the AI question the project never answers itself — one commenter writes “from the amount of activity and how much this all smells like heavy AI usage, I have zero doubt that something will be working shortly after launch. The agents won’t sleep until it boots,” and calls it “the first hint I’ve seen of the complete destruction of all copy protection schemes.” Nobody in 326 comments challenges the 87 percent figure — which is exactly the thing worth challenging, since the project’s own footnote says it is a percentage of the functions known so far.
Read the discussion →A coding agent's most expensive habit is confidently building the wrong thing. This is one developer's personal folder of 27 small instruction files — “skills” — that make the agent interview you first, write a failing test before the fix, and review its own work before it commits.
View on GitHub →/grill-me and /grill-with-docs make the agent ask you detailed questions before it builds, because the top failure mode is simple misalignment.
The README's pitch against GSD, BMAD and Spec-Kit is that they own your process; these are kept small, composable and easy to edit, and work with any model.
You type the user-invoked ones like /grill-me and /triage; the agent can reach for the model-invoked ones itself, like /tdd, /diagnosing-bugs and /code-review.
A 'CSS reset' for TypeScript, improving types for common JavaScript API's
Orchestrate sandboxed coding agents in TypeScript with sandcastle.run()
AI coding jargon, explained in plain English.
“One skill file, and my coding agent started testing first like a careful engineer.”
Open Ravi’s run → skills-test.codeshiftagent.comThe repo’s headline skill is an interview that refuses to stop, and this is the thread where users say so. Someone asks for a cap on the questions; Matt Pocock answers “remember that you are the one in charge… It’s a conversation, not an exam,” then closes it as wontfix — “grilling is intentionally open-ended.” A user posts a screenshot of a 4.5-hour session and says the result “was way over-engineered, like using a cannon to kill a mosquito.” The sharpest pushback is direct at the author: with GPT 5.5, “IMO, this should be addressed by the SKILL itself, I don’t think telling the user to steer it is the right solution.”
Read the discussion →An open-source framework that turns an ordinary HTML page — text, CSS, video clips, music, animation — into a finished MP4. Because the source is just HTML, an AI coding agent can write the video for you.
View on GitHub →A composition is an HTML file with data-start and data-duration attributes. Headless Chrome seeks every frame and FFmpeg encodes it, so no build step.
A “/hyperframes” router plus 20 more skills teach Claude Code, Codex, Cursor and Gemini CLI the loop: plan, write HTML, lint, preview, render.
Both render through headless Chrome and FFmpeg. Remotion bets on React components and a source-available license; this is plain HTML, Apache 2.0.
Open-source HyperFrames compositions behind HeyGen's product launch videos.
HeyGen AI agent skills — avatar creation and video production via the v3 Video Agent pipeline
“I typed one sentence and got back a Short that looks like a motion designer made it.” It took fifteen minutes and the right version of Node.
Open Ravi’s run → hyperframes-test.codeshiftagent.com/simpleA reviewer found that 11 of the 25 skill files in HeyGen’s own repo opened with a directive telling the agent to run an npx update “silently, don’t ask” — fetching and running code from the hyperframes npm channel on every invocation, which is why Snyk and Socket were flagging the pack. The blunt reply: “Self-updating skills, and invoking commands, telling the agent to do it silently, feels malicious… Definitely not ok,” from a developer whose unrelated pr-to-video skill got overwritten. This one has an ending you can show: the line in the live file now reads “confirm with the user before running.”
Read the discussion →Imagine giving your AI helper a big key ring. One connection lets it use thousands of apps, such as Gmail and Notion, to do everyday chores for you.
zapier.com/mcpNot an app — a set of written instructions you install into your AI coding tool. Ask for a diagram in plain words and it writes one self-contained HTML file with hand-placed SVG inside, styled like an editorial magazine rather than a default Mermaid chart.
View on GitHub →Architecture, flowchart, sequence, Gantt, Wardley map, Sankey, exploded axonometric and more. Each opens by double-clicking, with no build step or JavaScript.
Say “onboard diagram-design to yoursite.com” and it reads your palette and fonts, maps them to paper, ink, accent and title, and checks contrast.
Point it at a .drawio, Mermaid or Excalidraw file and it redraws the same content in this style, ending with a ledger of what it merged or dropped.
OpenClaw operations skill with health checks, repair scripts, watchdogs, update triage, and security scans.
Give Claude Code a second opinion using OpenAI Codex - automatic plan review via hooks
Orchestrator drives, Codex codes — execute an approved plan one task at a time with a test gate before every commit and exactly one PR at the end
“I asked for a diagram of a to-do app and got something that looks like a designer drew it.” About 4.5 minutes, because it plans and checks its own work.
Open Ravi’s run → diagram-design-test.codeshiftagent.comThe skill’s selling point is that it verifies WCAG AA contrast before it writes your brand colors. A user measured the skill’s own default skin and found the famous tangerine accent at 2.86:1 against paper, under the 3:1 minimum, with the sublabel gray at 3.48:1 against a 4.5:1 bar — and showed why nothing caught it: the linter only checks that colors come from the palette and never computes a ratio, while axe-core skips SVG text entirely. “A rule that only lives in prose is a rule that ships broken examples.” Cathryn Lavery reproduced every number, then changed the default accent to #bf4520 at 4.71:1 — which is the tangerine in the repo today.
Read the discussion →The National Security Agency’s own software reverse-engineering toolkit, published free on GitHub in 2019. Feed it a compiled program and it hands back readable code, so you can see what the thing actually does.
View on GitHub →Disassembly, assembly, decompilation, graphing and scripting across Windows, macOS and Linux binaries, with your own extensions in Java or Python.
New AI reverse-engineering agents, rea among them, hand native binaries to an existing Hopper, Ghidra or IDA install. Ghidra is the free one of the three.
Master merges the 12.2 branch daily and its release notes add beta “timeless” time-travel debugging. The last shipped build, 12.1.4, landed 21 Sep 2026.
A system automation and configuration management stack targeted toward operational flexibility and policy compliance.
Log-based transactional graph engine
DataWave is an ingest/query framework that leverages Apache Accumulo to provide fast, secure data access.
“I handed it a compiled program and it gave me back the secret PIN in eight seconds. Just bring Java 21.”
Open Ravi’s run → ghidra-test.codeshiftagent.comEveryone wants to drive Ghidra’s decompiler from the outside — scripts, plugins, now agents — and this thread is where contributors say they cannot. The decompiler is “a black box” to scripts: bytes go in, pseudo-C comes out, and any change re-runs the whole chain. The contested part is the answer they got. A commenter posts a screenshot of the NSA team replying “I’m sorry but it is against project policy to share internal project planning, timelines, roadmaps, etc.” The requester’s conclusion: “With the apparent lack of transparency from the Ghidra team… the most effective way forward is to build some sort of hooking framework.” The thread then points at ReOxide, an EU-grant-funded project that patches hooks into Ghidra from outside. Open since December 2025.
Read the discussion →A long chat with an AI coding tool eventually fills up the model’s memory, and then it goes vague or dies. This is a local middleman that folds the older part of the conversation into summaries it can unfold again, so one session keeps running.
View on GitHub →A local proxy rewrites requests on their way out, so the tool itself needs no changes. The README wires up 21 clients, from Claude Code to Zed.
It hands the model four tools — compress, decompress, search_context and acp_status — and the model calls them itself as the chat grows.
The Status section says compression passes 500+ mock tests and that testing against real models is still “the next milestone”.
稳定可用Active Context Pruning — model-driven context management for OpenCode ,200K tokens is enough. ,主动压缩上下文,20w token足以
稳定可用 Use billion-context instead .Active Context Pruning for pi ,100K tokens is enough. ,主动压缩上下文,10w 上下文足矣
压缩内核ACP compression & state management engine — standalone, zero runtime dependencies
“It took one fix to get running, and it worked after that. Whether it really gives you endless sessions needs a much longer test.”
Open Ravi’s run → billion-context-test.codeshiftagent.comA pack of skills you bolt onto a coding assistant so it can do mechanical design. You describe a part in plain words and it writes the CAD, exports a real file, draws the dimensioned print, and checks a shop can make it.
View on GitHub →They cover CAD modelling, 2D DXF drawings, dimensioned engineering drawings as PDFs, robot description files, G-code slicing and Bambu Lab printing.
Parts come out as STEP first, with STL, 3MF and GLB as options, built on Open CASCADE 7.9 through the build123d Python library.
The DFM skill reviews a part for sheet metal, CNC or injection moulding with measured evidence and cites the rule behind each finding.
12,000+ open source STEP parts for your next CAD project
Interactive browser-based CAD viewer for inspecting STEP, STL, 3MF, GLB, DXF, URDF, SDF, and SRDF files
A library for modelling 3D objects with mathematical primitives
“I described a phone stand in one sentence and got a file I could send straight to a 3D printer.” About 7 minutes.
Open Ravi’s run → text-to-cad-test.codeshiftagent.comThe dossier’s biggest gap is that this repo publishes no accuracy numbers at all, and this thread is where someone said it to the maintainer’s face: “Without benchmarks and/or a whole suite of non-cherrypicked examples, this means nothing because you can trivially make an AI generate anything from text.” The reply, from the person who posted the project: “Working on benchmarks at the moment! Always open to feedback / PRs.” That was five months ago and the README still has none. Elsewhere a commenter says the demo project “doesn’t seem to understand how servo motors work” and gets a one-character answer: “:(”. The deeper objection is structural — “LLMs are still very weak at spatial reasoning” — and a CAD professional argues the niche is hobbyists, because “for professionals, where results have dollar values, there needs to be a much deeper understanding of the problem domain.”
Read the discussion →An agent skill — a written rulebook an AI reads first — that teaches Claude Code, Codex, Gemini or Cursor how to write modern SwiftUI, the code behind iPhone and Mac app screens. There is no program in here, only Markdown.
View on GitHub →The repo is one SKILL.md plus twelve reference files on deprecated API, views, data flow, navigation, design, resizing, accessibility and performance.
Paul Hudson says the rules target real LLM habits: buttons left invisible to VoiceOver, deprecated API, and code that causes surprise performance problems.
A single npx skills add line installs it for Claude Code, Codex, Gemini or Cursor; you then run a review by typing /swiftui-pro, or $swiftui-pro in Codex.
“No Mac, no app, but the skill still made the AI write cleaner, more accessible SwiftUI.”
Open Ravi’s run → swiftui-agent-skill-test.codeshiftagent.comA skill with no benchmarks rests entirely on whether its rules are right, and here a working developer says one of them is wrong: using it on his open-source CreditsKit, the rule flagged four private single-use helpers and told the agent to scatter them across new files, which “would have made the code harder to read… this is the first of potentially several reports where a rule actively worsens code.” Paul Hudson defends it on performance grounds — SwiftUI reinvokes computed properties when the parent body changes — and notes Miguel de Icaza hit exactly that problem three days after the skill shipped. He also warns against the fix being proposed: do not apply @ViewBuilder by default, it creates conditional-content views that are slower and break animations. He merged it anyway, with a line that gives the whole repo away: “Claude particularly has a terrible habit of overusing computed properties, so we need to find a balance.”
Read the discussion →A workout app you run on your own server or home machine instead of renting one from a fitness company. You plan routines, log every set and your body weight, and the whole history sits in a folder you control.
View on GitHub →A docker compose up -d and it answers on localhost:8080; the exercise animations ship inside the image, so there is nothing else to download.
It imports from FitNotes, Strong and Hevy (CSV or an API key) plus Apple Health weight exports, and exports everything back out as one JSON file.
An opt-in coach drafts a week of routines on your own provider key, and an MCP server (the plug that lets AI tools read outside data) is read-only and local.
“No Docker needed to try it. Two commands and I had a clean, private workout tracker running in my browser.”
Open Ravi’s run → opengym-test.codeshiftagent.comThree days before this show, the maintainer tagged roughly 55 past contributors and asked each one to post a single sentence signing a new CLA. The reason is stated plainly: “the iOS app is next, and Apple’s App Store terms don’t mix well with code that is only under the AGPL.” Contributors keep copyright but grant openGym the right to relicense their work. The striking part is the unanimity — every single comment in the thread is the signature line, with zero objections, even though the ask is for an AGPL project to collect relicensing rights for a closed store build. The offer if you refuse is in there too: “that’s completely fine. Just say so and I’ll rewrite the parts that are yours.” Pair it with the other licensing catch — the exercise animations are not AGPL at all.
Read the discussion →A skill for Claude Code and Codex CLI that routes bulky, already-decided work — boilerplate, test stubs, the same edit across many files — to GPT through Codex, Gemini or a cheaper Claude subagent, while your main model plans and checks every diff. He also sent skillview, which puts every skill, plugin and MCP server you have installed into one table.
View on GitHub →Praj saw the Sep 25 episode open with Jev making decisions fast and cheap, and he uses it the same way: his main model plans the work and reviews every diff, and a model he is already paying for does the bulk typing.
Building something? Send it to hi@TheNextNewThing.ai
An open content-rating standard for books and stories: instead of one vague star or a pile of content warnings, every work gets spice, heat, darkness and transgression in one string, written SHOW S3·H4·O2·W5. The repo holds the v2.1 spec, machine-readable data with a JSON Schema, and a Claude skill that rates a chapter with evidence. Free under CC BY-SA 4.0.
View on GitHub →Lani built the SHOW Standard for indie, romance and romantasy authors, readers and platforms that want a shared vocabulary for what is actually inside a book.
Building something? Send it to hi@TheNextNewThing.ai
A small open-source skill that keeps Karpathy’s four coding rules — think before coding, simplicity first, surgical changes, goal-driven execution — and adds a gap check: if a missing fact would change the result and the agent cannot look it up, it asks at most three questions, each with a recommended default. Works with Claude Code, Codex, Cursor and Gemini.
View on GitHub →Anshuman built it to stop coding agents from filling in the blanks and shipping a guess. If nothing is missing, it skips the questions and just does the work.
Building something? Send it to hi@TheNextNewThing.ai
A skill that authors a narrated presentation and publishes it to a shareable watch URL, with free narration that runs on your own machine. Nick’s bisque.today is where those presentations get shared — a YouTube for AI-authored talks.
View on GitHub →Nick recently quit his job at Google to work on Bisque full time, and asked for the audience segment pointing out that Andrew would be extremely early: the repo had one star, his own.
Building something? Send it to hi@TheNextNewThing.ai
Install Docker and Container, type container, and you land in a persistent Linux workspace with Claude Code, Codex and OpenCode already set up, so an agent can work without touching your real computer. More than 1,200 people use it.
Kevin, whose magic-compact was on the Sep 11 show, built it for people who watch the channel, want AI to build something, then quit after installing six tools and hitting thirty error messages — especially on Windows. It is his most popular project.
Building something? Send it to hi@TheNextNewThing.ai
MemHooks drops small recall cues in the folders where they matter, so an agent that has the right fact stored actually thinks to go and look. Aron also sent Token-Terminator, which strips repeated tool output before it reaches the model while keeping the original exactly recoverable — its benchmark cuts a worst case from 651k tokens to 80k.
View on GitHub →Aron sent two tiny repos he thought fit the hidden-find radar. His point with MemHooks: long-term memory can store exactly the right fact and still fail, because the agent never thinks to look for it.
Building something? Send it to hi@TheNextNewThing.ai
A ranker for real-estate photos that runs on your own machine: open vision models (CLIP and SigLIP) score staging, clutter, how usable the room looks, brightness and composition in about 285 ms a photo on an M1 laptop — no GPU, no cloud.
View on GitHub →Yatin’s team wanted to know which photo to lead a listing with, rather than only A/B testing it, so he built the ranker — then open-sourced it because the approach is useful well beyond that one problem.
Building something? Send it to hi@TheNextNewThing.ai
A dashboard that runs on your own network for watching your agent machines, sending tasks to them, and taking over the controls, all over Tailscale — a private link between your own devices.
View on GitHub →Alex built AgentScreen for people running Hermes across several computers, and says it lets you take control “just like Grokbot does.” He has no idea how to charge for it.
Building something? Send it to hi@TheNextNewThing.ai
ManuView runs a manuscript past five adversarial reviewers — methods, domain expert, editor, statistician and devil’s advocate — and checks every reference against Crossref, OpenAlex and Retraction Watch. It can run fully offline, so unpublished work never leaves your machine. MIT licensed, with a web version too.
View on GitHub →Bishal, a PhD who maintains ManuView, saw researchers paying consultants $39 to $1,800 and up per paper just to catch the flaws that get papers desk-rejected, while generic chatbots are too agreeable and make up citations.
Building something? Send it to hi@TheNextNewThing.ai
A Claude Code mod (command /glanceflow) that replaces the stream of tool calls with one checklist above the prompt: the plan in plain English, live progress per step, and a clear “Needs you” when Claude is waiting on you. One button flips to Details with the code plus time, models and tokens per step, and it writes a plain-English team report. MIT licensed.
Andreas, co-founder and CTO of SigniVoice, watches the weekly GitHub roundup and built GlanceFlow for the non-engineers on his team, who had started using Claude Code and found it overwhelming.
Building something? Send it to hi@TheNextNewThing.ai
A small Windows app: point it at an e-book window (he tested the Kindle app) and it turns the page, takes a screenshot, and repeats to the end, then uses Windows’ built-in OCR to rebuild the text as a single file you can hand to an AI, or a PDF of the pages. It breaks no copy protection, so it is for books you own. Free and open source.
View on GitHub →Christopher, author of the novel Dealing with Murder, heard Andrew say on the show that he was not sure how people give a whole book to an AI to follow — so he built Book Snapper as a proof of concept.
Building something? Send it to hi@TheNextNewThing.ai
Sends Paperclip agent requests — hiring another agent, spending budget, or a question that needs answering — to Slack or Telegram, where you tap Approve or fill in a short form and Paperclip records the decision under your own account. There is deliberately no AI in the bot, so nothing an agent writes can talk it into approving something. One Python file, MIT licensed.
View on GitHub →Christopher’s team at sthreelabs runs a small team of agents on Paperclip, from the Sep 25 episode, and kept wanting to answer agent requests without opening the dashboard — especially when he is remote and would otherwise set up a tunnel or wait until he is back at the office.
Building something? Send it to hi@TheNextNewThing.ai
An open benchmark and inference engine for big AI models on ordinary computers: instead of loading the whole model into memory, where normal runtimes crash or freeze, the weights stay on a fast NVMe drive and Kura streams the next layer in while the processor works on the current one. One-command install, with a terminal interface and an OpenAI-compatible API server.
View on GitHub →Fraol wrote in to say he had built a tool he wanted Andrew to look at, and offered to walk him through it.
Building something? Send it to hi@TheNextNewThing.ai
James’s second repo, written in Rust: fast web scraping that is built to be hard to detect and to fix itself when a page it depends on moves. Early days, with a site at netweir.com.
View on GitHub →James says his second repo has dropped, it is still in the early stages, and it is the first time he is adding some vibe coding into the mix, so “we will see how it goes.”
Building something? Send it to hi@TheNextNewThing.ai
A self-hosted “family office” for Claude Code or Codex: one command gives a full risk profile for any ticker (value at risk, Sharpe, drawdown, beta) from a fresh clone, your data stays in a private SQLite ledger on your own machine, and guardrails block a risky action when its inputs are missing instead of guessing.
View on GitHub →Ossie watches every Top 10 episode and built it on one rule: agents propose, typed code computes — so every number an agent quotes comes out of a tested Python calculator you can run yourself.
Building something? Send it to hi@TheNextNewThing.ai
A note-taking and knowledge-management system with AI, built on the beads practice (vakana) of Madagascar, and made to work on a phone. Site at vakana.mg.
View on GitHub →Donovan, a YouTube follower from Madagascar, based it on the Vakana beads practices of his Malagasy ancestors. He has just open-sourced it and would love the show to give it its first star.
Building something? Send it to hi@TheNextNewThing.ai
A completely offline Android password manager with local sync between your own devices — no account, no cloud service in the middle.
View on GitHub →Simon has been watching Andrew’s videos for ages and is building a whole host of completely offline Android apps. plain-vault is the first one he feels happy sharing, with a few more ready soon.
Building something? Send it to hi@TheNextNewThing.ai
A self-hostable tool that brings agents like Claude Code and Codex into shared Slack, Teams or Discord channels, working alongside the people already in them.
View on GitHub →Lisa asked Andrew and Corey to review Switch — whether the agents can genuinely work together, how much setup it takes, and how permissions and costs are handled.
Building something? Send it to hi@TheNextNewThing.ai
A free, local-first security review tool: it scans code on your own machine with networking off by default, flags exposed credentials, unsafe execution patterns and risky configuration, can block unsafe commits, and shows evidence of what it checked. AI review is optional. Still early, at v0.1.0.
View on GitHub →John, founder of BlackSnow Intelligence with a background in cybersecurity governance, risk and compliance, noticed that AI code-review tools and scanners can themselves leak source code, credentials or sensitive context to outside services.
Building something? Send it to hi@TheNextNewThing.ai
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