[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-open-source-tools-vibe-coding-cybersecurity-en":3,"article-related-open-source-tools-vibe-coding-cybersecurity-en":31,"series-tools-ae4915a0-e313-438e-b724-e04e07331683":77},{"id":4,"slug":5,"title":6,"content":7,"summary":8,"source":9,"source_url":10,"author":11,"image_url":12,"cover_image":12,"category":13,"language":14,"translated_content":11,"related_article_id":15,"keywords":16,"key_takeaways":23,"views":27,"created_at":28,"published_at":29,"topic_cluster_id":30},"ae4915a0-e313-438e-b724-e04e07331683","open-source-tools-vibe-coding-cybersecurity-en","Open source tools that make vibe coding safer","\u003Cp data-speakable=\"summary\">I break down the open source stack I’d use for safer \u003Ca href=\"\u002Ftag\u002Fvibe-coding\">vibe coding\u003C\u002Fa> in security work.\u003C\u002Fp>\u003Cp>I've been using \u003Ca href=\"\u002Ftag\u002Fai-coding-tools\">AI coding tools\u003C\u002Fa> long enough to know when they’re helping and when they’re quietly making a mess. In \u003Ca href=\"\u002Ftag\u002Fcybersecurity\">cybersecurity\u003C\u002Fa>, that mess gets expensive fast. The first time I tried to use an AI assistant for a detection script, it looked brilliant right up until I noticed it had guessed at a log field name, skipped input validation, and happily suggested a package I’d never approve in a production repo. That’s the problem with vibe coding in security: the output can feel fast and confident while still being wrong in all the places that matter.\u003C\u002Fp>\u003Cp>So when I read Austin Miller’s piece on \u003Ca href=\"https:\u002F\u002Fsecpro.substack.com\u002Fp\u002Fwhich-open-source-tools-can-help\" target=\"_blank\" rel=\"noopener noreferrer\">SecPro\u003C\u002Fa>, I wasn’t interested in the hype. I wanted the practical answer: which open source tools actually fit the way security teams work? Miller’s post points to a stack built around \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FAll-Hands-AI\u002FOpenHands\" target=\"_blank\" rel=\"noopener noreferrer\">OpenHands\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fwww.continue.dev\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Continue.dev\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Faider.chat\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Aider\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Fopeninterpreter.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Open Interpreter\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Follama.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Ollama\u003C\u002Fa>, with agent frameworks like \u003Ca href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fresearch\u002Fproject\u002Fautogen\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">AutoGen\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Flangchain-ai.github.io\u002Flanggraph\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">LangGraph\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Fwww.crewai.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">CrewAI\u003C\u002Fa> for teams that want to go further.\u003C\u002Fp>\u003Ch2>Stop treating vibe coding like autocomplete with a nicer name\u003C\u002Fh2>\u003Cblockquote>“What began as code completion and documentation assistance has evolved into a new development paradigm often described as vibe coding: a workflow in which developers express intent in natural language and allow AI systems to generate, modify, test, and sometimes deploy software on their behalf.”\u003C\u002Fblockquote>\u003Cp>What this actually means is that the AI is no longer just finishing your line. It’s participating in the whole workflow. That’s a big shift, and in security work it changes the risk profile immediately. If the model can generate code, it can also generate insecure code. If it can modify files, it can also modify the wrong ones. If it can run commands, it can also wander into places you didn’t intend.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781852617883-ajan.png\" alt=\"Open source tools that make vibe coding safer\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>I ran into this when I asked an assistant to build a small parser for Suricata logs. It produced something that looked clean, but it made assumptions about delimiter formats and silently dropped malformed rows. Fine for a demo. Bad for an investigation pipeline. That’s why Miller’s framing matters: vibe coding isn’t “faster typing.” It’s delegated intent, and once you accept that, you start designing guardrails instead of just prompts.\u003C\u002Fp>\u003Cp>How to apply it: define which parts of your workflow are safe for delegation and which are not. I’d split tasks into three buckets:\u003C\u002Fp>\u003Cul>\u003Cli>\u003Cstrong>Low risk:\u003C\u002Fstrong> boilerplate, tests, docs, local scripts, one-off transformations.\u003C\u002Fli>\u003Cli>\u003Cstrong>Medium risk:\u003C\u002Fstrong> detection rules, parsing logic, internal tooling, glue code.\u003C\u002Fli>\u003Cli>\u003Cstrong>High risk:\u003C\u002Fstrong> production changes, auth flows, secrets handling, network-facing services.\u003C\u002Fli>\u003C\u002Ful>\u003Cp>Use AI freely in the first bucket, review aggressively in the second, and keep the third under strict human control. If you skip that line, you’ll end up trusting a model to make decisions it was never qualified to make.\u003C\u002Fp>\u003Ch2>Open source matters because security teams need receipts\u003C\u002Fh2>\u003Cp>Miller makes the case that open source AI tooling is attractive because teams can inspect, audit, and self-host it. That sounds obvious until you’ve sat in a review where someone asks, “Where is this code going?” and the answer is, “Into a vendor box, I think.” In security, “I think” is not a plan.\u003C\u002Fp>\u003Cp>What this actually means is that open source gives you something proprietary tools often don’t: visibility. You can inspect how prompts are handled, where data goes, what gets logged, and which permissions are enforced. That matters a lot if you work with sensitive repositories, regulated systems, or anything that would make your legal team twitch.\u003C\u002Fp>\u003Cp>There’s another practical reason I prefer open source here. It fits existing controls. Security teams already know how to wrap identity, logging, container policies, and software composition analysis around software they can actually see. If the AI tool is open, I can put it behind the same gates I use for everything else. If it’s closed, I’m mostly hoping the vendor’s story is good enough.\u003C\u002Fp>\u003Cp>How to apply it: before adopting any \u003Ca href=\"\u002Ftag\u002Fai-coding\">AI coding\u003C\u002Fa> tool, I’d ask four questions:\u003C\u002Fp>\u003Cul>\u003Cli>Can I self-host it?\u003C\u002Fli>\u003Cli>Can I inspect the code paths that touch prompts and files?\u003C\u002Fli>\u003Cli>Can I route logs into my existing monitoring stack?\u003C\u002Fli>\u003Cli>Can I restrict what the tool can read, write, and execute?\u003C\u002Fli>\u003C\u002Ful>\u003Cp>If the answer is no to two or more of those, I’d treat it as a convenience tool, not a security engineering tool. That’s a useful distinction, because convenience tools tend to sneak into places they shouldn’t.\u003C\u002Fp>\u003Ch2>OpenHands is the one I’d reach for when I want an agent, not a chatbot\u003C\u002Fh2>\u003Cp>Miller calls \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FAll-Hands-AI\u002FOpenHands\" target=\"_blank\" rel=\"noopener noreferrer\">OpenHands\u003C\u002Fa> one of the strongest foundations for cybersecurity-focused vibe coding, and I get why. OpenHands is not just a suggestion engine. It’s an autonomous software engineering platform that can plan work, execute commands, browse docs, interact with repositories, and keep iterating. That’s a different beast from autocomplete.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781852612140-zwme.png\" alt=\"Open source tools that make vibe coding safer\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cblockquote>“OpenHands is an autonomous software engineering platform that allows AI agents to write code, execute commands, browse documentation, interact with repositories, and perform multi-step development tasks.”\u003C\u002Fblockquote>\u003Cp>What this actually means is that OpenHands can take a goal like “build a log ingestion pipeline” and work through the steps instead of waiting for you to drive every keystroke. In security work, that’s useful when the job is repetitive but still nontrivial: generate test data, create validation scripts, wire up parsing, document the result, then fix the inevitable breakage.\u003C\u002Fp>\u003Cp>I’ve seen this pattern work best when the task is bounded and the environment is disposable. If the agent is in a sandbox, has clear repo access, and you can throw away the workspace when it drifts, it becomes a very productive junior helper. If you point it at a live system and hope for the best, you’re asking for an incident.\u003C\u002Fp>\u003Cp>How to apply it: use OpenHands for multi-step tasks with a clear finish line. Good examples include:\u003C\u002Fp>\u003Cul>\u003Cli>turning an incident note into a draft detection pipeline\u003C\u002Fli>\u003Cli>building a proof-of-concept parser for a new log source\u003C\u002Fli>\u003Cli>generating test fixtures and validation scripts\u003C\u002Fli>\u003Cli>scaffolding internal tools that still need human review\u003C\u002Fli>\u003C\u002Ful>\u003Cp>My rule is simple: if the task needs planning, iteration, and command execution, OpenHands is a fit. If the task needs judgment about business risk, keep a person in the loop at every step.\u003C\u002Fp>\u003Ch2>Continue.dev is the calmer option when you still want your IDE to feel like your IDE\u003C\u002Fh2>\u003Cp>Not every security engineer wants an agent that can go wandering through the repo on its own. A lot of us want help without surrendering control. That’s where \u003Ca href=\"https:\u002F\u002Fwww.continue.dev\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Continue.dev\u003C\u002Fa> makes sense. It runs inside VS Code and JetBrains, and it can connect to local or hosted models, which means you can keep the workflow close to what developers already know.\u003C\u002Fp>\u003Cp>What this actually means is that Continue behaves more like a collaborator than a contractor. It can generate code, explain weird codebases, suggest refactors, write tests, and help review security-sensitive functions. But you’re still sitting in the driver’s seat, and that matters when the code touches auth, secrets, or infrastructure.\u003C\u002Fp>\u003Cp>I like this model for detection engineering and internal tooling because it reduces friction without removing judgment. When I’m building a SIEM integration or updating a Sigma rule set, I don’t want a tool that goes off and “finishes” the job in a way I didn’t ask for. I want inline help, model choice, and the ability to keep the repo under human control.\u003C\u002Fp>\u003Cp>How to apply it: use Continue when your team already lives in an IDE and wants a low-drama entry point into AI-assisted coding. It’s especially useful if you want to:\u003C\u002Fp>\u003Cul>\u003Cli>keep code review habits intact\u003C\u002Fli>\u003Cli>use local models for sensitive projects\u003C\u002Fli>\u003Cli>avoid sending source code to a third party\u003C\u002Fli>\u003Cli>let engineers ask for help without changing their whole workflow\u003C\u002Fli>\u003C\u002Ful>\u003Cp>If OpenHands is the agent that can do the job, Continue is the assistant that makes your existing process less annoying. For a lot of security teams, that’s the better first step.\u003C\u002Fp>\u003Ch2>Aider is for people who live in Git and don’t want to pretend otherwise\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Faider.chat\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Aider\u003C\u002Fa> is the tool I’d point terminal-heavy security folks toward first. It works from the command line, understands repository structure, and applies changes directly to tracked files. That sounds small, but it’s exactly why it fits security work so well.\u003C\u002Fp>\u003Cblockquote>“Aider operates directly from the command line and allows developers to use AI models to modify existing repositories.”\u003C\u002Fblockquote>\u003Cp>What this actually means is that Aider respects the shape of normal development work. It doesn’t ask you to abandon Git, and it doesn’t hide changes inside some opaque interaction layer. You can see diffs, review commits, and keep the audit trail intact. In security, that’s not a nice-to-have. That’s the whole point.\u003C\u002Fp>\u003Cp>I’ve used terminal-first workflows for years because they make it easier to keep a clean paper trail. When I ask an AI tool to touch a repo, I want the result to show up in a diff I can inspect like any other change. Aider gets that part right. It’s especially handy when you’re extending internal recon tools, adding protocol parsers, or automating repetitive data wrangling.\u003C\u002Fp>\u003Cp>How to apply it: use Aider when your team already reviews changes through Git and wants AI help that doesn’t bypass that process. Good use cases include:\u003C\u002Fp>\u003Cul>\u003Cli>small refactors across multiple files\u003C\u002Fli>\u003Cli>adding tests to existing code\u003C\u002Fli>\u003Cli>updating parsers and transforms\u003C\u002Fli>\u003Cli>making incremental improvements you can review commit by commit\u003C\u002Fli>\u003C\u002Ful>\u003Cp>The big win here is transparency. If the model makes a bad move, you catch it in the diff before it becomes a problem. That’s exactly the kind of boring safety net security teams should love.\u003C\u002Fp>\u003Ch2>Open Interpreter is powerful, and that’s why it needs fences\u003C\u002Fh2>\u003Cp>\u003Ca href=\"https:\u002F\u002Fopeninterpreter.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Open Interpreter\u003C\u002Fa> pushes vibe coding beyond code generation and into action. It can interact with local computing environments and execute commands on your behalf. That makes it useful for automation, but it also means you’re handing it a lot more power than a plain text assistant gets.\u003C\u002Fp>\u003Cp>What this actually means is that Open Interpreter can be used for operational security work, not just software tasks. If I need to parse firewall logs, enrich the results, and generate a report, I can describe the outcome and let the tool coordinate the steps. That’s great when the task is repetitive and local. It’s not so great if permissions are loose and nobody is watching the audit trail.\u003C\u002Fp>\u003Cp>The security concern is obvious: once a tool can act on the system, you need clear boundaries. That means sandboxing, permission controls, and logging. I wouldn’t put this anywhere near a production environment without a very deliberate setup.\u003C\u002Fp>\u003Cp>How to apply it: reserve Open Interpreter for local automation where the blast radius is small. I’d use it for:\u003C\u002Fp>\u003Cul>\u003Cli>log parsing and enrichment on a workstation\u003C\u002Fli>\u003Cli>report generation from offline datasets\u003C\u002Fli>\u003Cli>batch file transformations\u003C\u002Fli>\u003Cli>internal scripts that don’t need privileged access\u003C\u002Fli>\u003C\u002Ful>\u003Cp>If you want the speed of natural language without giving up all control, Open Interpreter can be useful. But the second it gets real permissions, the burden shifts back to you to make sure the environment is boxed in.\u003C\u002Fp>\u003Ch2>Ollama makes local models practical instead of theoretical\u003C\u002Fh2>\u003Cp>The open source vibe coding stack gets a lot more interesting when the model itself runs locally. That’s why \u003Ca href=\"https:\u002F\u002Follama.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">Ollama\u003C\u002Fa> matters. It gives teams a straightforward way to run large language models on local hardware instead of shipping source code to a third-party service.\u003C\u002Fp>\u003Cp>What this actually means is that your code, prompts, and context can stay inside your own environment. For regulated sectors like healthcare, finance, and defense, that’s often the difference between “we should try this” and “we can actually deploy this.”\u003C\u002Fp>\u003Cp>I’ve found local model setups especially useful when the work involves sensitive repos or internal data. You still need to manage quality and security, obviously, but at least you’re not introducing an extra data exposure problem just to get code suggestions. That’s a trade I’m happy to avoid.\u003C\u002Fp>\u003Cp>How to apply it: pair Ollama with tools like Continue or Aider when you want local inference and predictable data handling. A good starter setup looks like this:\u003C\u002Fp>\u003Cul>\u003Cli>run a local model in Ollama\u003C\u002Fli>\u003Cli>connect it to Continue.dev inside your IDE\u003C\u002Fli>\u003Cli>use Aider for Git-based repo edits\u003C\u002Fli>\u003Cli>keep sensitive projects off hosted endpoints\u003C\u002Fli>\u003C\u002Ful>\u003Cp>That setup won’t solve every problem, but it gives you a much better story for governance, privacy, and internal review. In security, that story matters almost as much as the tool itself.\u003C\u002Fp>\u003Ch2>Agent frameworks are for teams that are ready to stop pretending one bot can do everything\u003C\u002Fh2>\u003Cp>Miller also mentions \u003Ca href=\"https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fresearch\u002Fproject\u002Fautogen\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">AutoGen\u003C\u002Fa>, \u003Ca href=\"https:\u002F\u002Flangchain-ai.github.io\u002Flanggraph\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">LangGraph\u003C\u002Fa>, and \u003Ca href=\"https:\u002F\u002Fwww.crewai.com\u002F\" target=\"_blank\" rel=\"noopener noreferrer\">CrewAI\u003C\u002Fa> as the next layer up. I think that’s right. Once a team gets comfortable with assistants and agents, the next move is usually specialization: one agent for analysis, one for review, one for compliance, one for hardening.\u003C\u002Fp>\u003Cblockquote>“These frameworks enable developers to create specialised agents with distinct responsibilities.”\u003C\u002Fblockquote>\u003Cp>What this actually means is that you stop asking one model to be a genius at everything. Instead, you assign roles. That maps well to security workflows, because security already runs on specialization. Nobody sane expects one analyst to do threat intel, \u003Ca href=\"\u002Ftag\u002Fcode-review\">code review\u003C\u002Fa>, compliance, and infra hardening without support.\u003C\u002Fp>\u003Cp>I’d only reach for these frameworks once the team has already figured out the basics: model governance, prompt boundaries, logging, and human review. Otherwise you’re building a fancy orchestration layer on top of a process you don’t understand yet. That’s how people end up with complex systems that are hard to audit and easy to misuse.\u003C\u002Fp>\u003Cp>How to apply it: use agent frameworks when you need repeatable multi-agent workflows, not when you’re still experimenting. Good candidates include:\u003C\u002Fp>\u003Cul>\u003Cli>agent-based secure code review\u003C\u002Fli>\u003Cli>vulnerability triage pipelines\u003C\u002Fli>\u003Cli>policy checks before merge\u003C\u002Fli>\u003Cli>threat research workflows with clear role separation\u003C\u002Fli>\u003C\u002Ful>\u003Cp>My advice is to start with one narrow workflow and one measurable outcome. If the framework can’t make that workflow better, it’s probably not ready for your team.\u003C\u002Fp>\u003Ch2>Security risks don’t disappear just because the repo is open source\u003C\u002Fh2>\u003Cp>Miller is careful here, and I think he should be. The benefits of open source tooling do not cancel out the risks of AI-generated code. Studies keep finding insecure patterns in generated output, and AI-enabled development environments have their own problems too: prompt injection, data leakage, and even remote code execution paths in some cases.\u003C\u002Fp>\u003Cp>What this actually means is that you still need normal security discipline. You don’t get to skip review because the tool is local. You don’t get to skip testing because the prompt sounded smart. And you definitely don’t get to skip dependency review because a model suggested a package with a nice README.\u003C\u002Fp>\u003Cp>How to apply it: I’d put the same controls around AI-assisted coding that I’d put around any other risky automation:\u003C\u002Fp>\u003Cul>\u003Cli>review generated code before merge\u003C\u002Fli>\u003Cli>scan dependencies and lock versions\u003C\u002Fli>\u003Cli>log prompts and tool actions where appropriate\u003C\u002Fli>\u003Cli>sandbox execution when the tool can run commands\u003C\u002Fli>\u003Cli>separate sensitive projects from casual experimentation\u003C\u002Fli>\u003C\u002Ful>\u003Cp>If I had to boil the whole article down to one sentence, it would be this: open source vibe coding tools are useful in cybersecurity because they let you keep control while still moving faster. But control is the part you can’t fake.\u003C\u002Fp>\u003Ch2>The template you can copy\u003C\u002Fh2>\u003Cpre>\u003Ccode># Secure vibe coding stack for cybersecurity teams\n\n## 1) Pick the interaction style\n- Use OpenHands for autonomous multi-step tasks.\n- Use Continue.dev for IDE-native help.\n- Use Aider for Git-first repo edits.\n- Use Open Interpreter only for local automation with tight permissions.\n\n## 2) Pick the model location\n- Use Ollama for local models when code or prompts are sensitive.\n- Use hosted models only for low-risk or non-sensitive work.\n\n## 3) Set the guardrails\n- Keep sensitive repos in self-hosted environments.\n- Require human review before merge.\n- Log prompts, tool actions, and file changes.\n- Sandbox any tool that can execute commands.\n- Restrict network, filesystem, and credential access.\n\n## 4) Match tool to task\n### Good fits\n- Detection rule drafts\n- Log parsers\n- Internal utility scripts\n- Test generation\n- Documentation\n- Refactors\n\n### Avoid or heavily constrain\n- Auth flows\n- Secrets handling\n- Production changes\n- Internet-facing services\n- Privileged automation\n\n## 5) Recommended starter workflow\n1. Run a local model in Ollama.\n2. Connect it to Continue.dev in VS Code or JetBrains.\n3. Use Aider for repo changes that need clean diffs.\n4. Keep OpenHands in a sandbox for bounded agent tasks.\n5. Review every change through Git and normal security checks.\n\n## 6) Team policy snippet\n\"AI-assisted code may accelerate implementation, but it does not replace review, testing, dependency checks, or security approval for sensitive changes. Any tool that can read, write, or execute must be scoped to the minimum access required for the task.\"\n\n## 7) Practical prompt pattern\n\"Build [task] for [environment]. Use [language\u002Ftooling]. Keep the implementation minimal, include tests, avoid external dependencies unless necessary, and explain any security tradeoffs before making changes.\"\n\u003C\u002Fcode>\u003C\u002Fpre>\u003Cp>That’s the setup I’d start with if I were rolling this out in a security team tomorrow. It’s boring on purpose. Boring is good when the code can touch sensitive systems.\u003C\u002Fp>\u003Cp>Most of this article is original synthesis based on Austin Miller’s SecPro post, but the tool list and framing come from his piece on \u003Ca href=\"https:\u002F\u002Fsecpro.substack.com\u002Fp\u002Fwhich-open-source-tools-can-help\" target=\"_blank\" rel=\"noopener noreferrer\">Which Open Source Tools Can Help Us with Vibe Coding in Cybersecurity?\u003C\u002Fa>. I’ve added my own workflow guidance, ordering, and template so you can actually use it without turning your repo into a science project.\u003C\u002Fp>","I break down the open source stack I’d use for safer vibe coding in security work, plus a copy-ready workflow you can adopt.","secpro.substack.com","https:\u002F\u002Fsecpro.substack.com\u002Fp\u002Fwhich-open-source-tools-can-help",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781852617883-ajan.png","tools","en","819930d2-f83c-42e1-be18-fc65eb212184",[17,18,19,20,21,22],"vibe coding","cybersecurity","open source tools","AI coding assistants","OpenHands","Continue.dev",[24,25,26],"Open source AI tools help security teams keep control over prompts, code, and execution.","OpenHands fits autonomous multi-step tasks, while Continue.dev and Aider suit tighter human-in-the-loop workflows.","Local models with Ollama reduce exposure, but review, logging, and 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