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description=A beginner s guide to Vibe Coding by Addy Osmani. Learn to build applications by describing what you want in plain language and letting AI handle the rest.;
keywords=AI development, vibe coding, AI-assisted programming, software engineering, Addy Osmani, Bolt, Lovable, Cline, AI coding tools, AI coding, beginners;

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Text of the page (random words):
ckly build apps with bolt filter by category or search for specific ideas all productivity social dashboard utility ai powered showing 30 prompts vibe coding pro tips for intermediate engineers to an experienced developer vibe coding isn t about letting an ai take the wheel but rather using it as a force multiplier for their own expertise a senior engineer knows that the ai s output is only as good as the prompt the context and the review process that follows it s a collaborative approach that pairs the ai s speed with human judgment here are 20 tips for senior engineers to master vibe coding and deliver production grade results mindset and process be a pilot not a passenger the ai is your copilot not the pilot you are ultimately responsible for the code that ships do not blindly copy and paste always review understand and own every line act like it s an over enthusiastic junior dev think of the ai as a junior who needs constant guidance and feedback you wouldn t let a new hire write and merge a large feature without a clear plan and code review treat the ai the same way start with the design not the code use the ai as a rubber duck for architecture before writing any code prompt it to propose a plan discuss tradeoffs and outline the steps embrace the spike approach treat the ai s initial output as a prototype or a spike use it to explore concepts quickly then discard or rewrite the code from a position of understanding build a collaborative feedback loop review the ai s work and use its failures as a teaching moment learn from what it gets wrong and refine your instructions for the next iteration prompting techniques provide explicit examples if you want the ai to follow a specific pattern include a well formatted code example follow the createuserinput zod schema format is better than asking for one from scratch give constraints liberally tell the ai what not to do for example do not use a new library avoid using any or never write tests that hit a real database leverage a custom rulebook for team settings maintain a shared rulebook e g cursor rules file this codifies conventions and ensures consistency load the relevant context always provide relevant files type definitions configuration files etc so the ai has enough context break down complex tasks for large multi step features create smaller chained prompts this improves accuracy and allows step by step verification quality and maintenance test driven prompting tdp just as with tdd write your tests before asking the ai to generate code this ensures correctness focus on security never trust the ai with security critical code always run automated scanners and do manual reviews for sensitive areas conduct targeted code reviews ai often misses edge cases review error handling input validation and pattern consistency carefully document the why when integrating ai code explain why you accepted its output this preserves context and transparency schedule ai code cleanup sessions dedicate time to refactor and reduce ai introduced technical debt regularly performance and optimization profile the generated code ai favors readability over efficiency profile data structures loops and queries before committing refine bad refactoring let the ai suggest refactors but guide it when it s inefficient your judgment remains key use ai for data heavy tasks let it handle tedious structured tasks like writing sql regex or schemas it excels there continuous learning learn from the code use the ai to explore new libraries and languages ask for explanations instead of full solutions experiment with different models some models excel at debugging others at planning test and adopt the right tool for each task vibe coding pro tips for senior engineers 50 tips for working with ai in development spend more time providing context to the ai before generating code to ensure better alignment with your vision break the work into small manageable chunks to maintain control and reduce errors associate tests with each chunk of work to verify functionality early make tests robust and exhaustive to catch issues before they compound review and understand every piece of ai generated code to avoid black box problems commit changes to a repository only after tests pass for easy rollbacks use a structured format find the issue create a plan review the plan then execute it do a two step process first plan without coding then implement use different ais for planning e g gemini and coding e g sonnet for optimal results see yourself as the manager and the ai as a literal direct report give clear specific instructions go slower to enjoy the process and build deliberately rather than rushing log sessions for future context to track decisions and iterations create a full plan but don t give it all to the ai at once vibe and chat to build features gradually spend time on context engineering to elevate beyond hobbyist slop and achieve professional results start with a readme file including requirements tech stack and milestones vibe pming first break tasks into one small micro step at a time for better manageability never stop vibing but always break into smaller parts start with components that have no dependencies to build momentum use frameworks to standardize and speed up development avoid ambiguity in prompts be explicit about what you want name variables functions and components consistently and clearly commit to github with prompt response summaries and changed files for better tracking work alone if you want to go fast add resources later for scaling trace the full user flow and identify root causes when fixing bugs treating symptoms as clues commit changes to git often for easy rollbacks and to help agents reference older code versions apply systems thinking design the architecture yourself let ai handle execution details start with something simple and deploy test every turn make incremental improvements rather than big leaps ask ai to explain technical aspects and confess limitations create an architecture md file with explanations of files and functions update it with every change understand the vibe as grounded in technical reality know what s possible expensive or fragile use a setup with multiple tools for efficiency like cursor for coding and claude for planning baby step prompts feed context gradually read docs and plan in small concrete steps adopt practices like frequent testing to prevent unintended consequences from piling up write a high level plan and break it into small phases add as much context as possible to each phase s plan including what to build and avoid discard and restart if the ai messes up don t force fixes on bad foundations know the ai s coding personality to tailor prompts effectively create frequent checkpoints to revert to working versions easily start with plain english descriptions then iterate by specifying refinements solve hyper specific personal problems first they often scale to broader use embrace browser centric development like chrome extensions for high user engagement integrate real world inputs like image recognition or voice for intuitive apps automate repetitive workflows such as meeting prep or email handling build for daily use and stickiness by solving ongoing pain points use supabase for easy backend integration in tools like lovable or bolt deploy and share early to evolve personal tools into shared products use animation and visual feedback for engaging uis generate detailed product requirements and user stories with ai before coding learn new technologies through ai assisted exploration troubleshooting issues as they arise pitfalls and gotchas to watch out for vibe coding is powerful but it isn t magic you still need human judgment to avoid bugs security issues and other pitfalls as a beginner using these tools keep the following caveats in mind to make your journey smoother and safer the 70 problem ai s last mile weakness it s often said that ai can get you 70 of the way to a working app very quickly but the final 30 of polish is the hardest 92 93 in practice you might have an app that basically works but edge cases and subtle bugs lurk underneath for example you generated a shopping cart app in minutes but upon testing you find it doesn t handle an empty cart correctly on checkout or it fails if the product name has special characters these kinds of issues often require traditional debugging and careful thinking don t be discouraged this is a normal part of software development the ai got you very far very fast which is amazing but be prepared to roll up your sleeves for the troubleshooting phase use the ai to help with debugging by all means ask it to explain errors or suggest fixes but know that you might need to iteratively test numerous times many vibe coders say the first 1 2 prompts feel like magic but the refinement stage can still be time consuming this is where you build your understanding and improve the app beyond the initial vibe vibe coding your way to a production codebase is clearly a terrible idea most of the work we do as software engineers is about evolving existing systems and for those the quality and understandability of the underlying code is crucial simon willison test as you go ruthlessly when you re not inspecting code testing becomes your safety net run your app frequently most tools let you preview live in the browser and try to break it enter weird inputs click all the buttons use it as a real user would after every major change the ai makes do a quick sanity check that previous features still work sometimes a new change can introduce a regression a phenomenon one might call the two steps back pattern 94 it s much easier to catch and fix issues when you test incrementally rather than letting the ai build 10 features and then discovering nothing works in vibe coding small iterative testing prevents nightmare debugging later 95 if something breaks you can immediately point it out to the ai while the context is fresh don t blindly trust generated code especially for sensitive logic vibe coding tools can and do make mistakes they might use an inefficient approach miss a security check or produce code that works on the surface but isn t best practice if you re building something that involves payments personal data or anything security critical pause and review the relevant code carefully or have the ai explain it line by line for instance if you had the ai integrate stripe for payments double check that the api keys aren t exposed and that webhooks are handled properly the ai might not handle secrets safely by default there have been cases of vibe coded apps accidentally leaking database credentials or api keys because the ai didn t know better 96 the motto here is trust but verify use vibe coding to accelerate development but if you intend to deploy to real users allocate time for a thorough code review or use tools like cursor s code analysis to catch issues 97 98 be mindful of security and privacy building on the above remember that the ai is trained on general data and doesn t automatically know your security or privacy requirements it may for example include an analytics script you didn t ask for or allow actions that should be restricted always specify security needs in your prompts e g ensure only logged in users can access the dashboard and test those boundaries if your app handles user data confirm that the ai set up proper access control some vibe coding platforms include basic guardrails zapier s review noted all the top tools had authentication and security checks by default 99 100 but you should not assume everything is safe until you ve verified it also be cautious not to paste truly sensitive info into these tools while many have privacy policies you re still sending data to an ai service watch out for model limitations and hallucinations ai models sometimes hallucinate produce code or answers that look confident but are incorrect you might see it import a library that doesn t exist call functions with wrong parameters or invent an api response format if something in the output looks unfamiliar or too good to be true double check it when the ai says i ve set up a secure authentication for you confirm that by testing registration and login flows if it says using the payment api s createcharge method verify that method in the api s docs some ais might reference outdated versions in short keep a critical eye the ai is a partner but not infallible token limits and cost most vibe coding platforms run on powerful models like gpt 4 or claude which have context length limits and can incur cost as you use more tokens if your conversation becomes very long the ai might forget earlier details or code though many tools handle this by summarizing or focusing on recent messages you might need to re provide context occasionally additionally pay attention to your credit usage on each platform it s easy to get carried away adding features and then find out you ve exhausted the free tier as one blogger joked the risk of overspending on api calls is a real consideration 101 to avoid this plan your prompts thoughtfully batch small changes into one prompt if you can and take advantage of free tiers across tools if needed e g do some in bolt some in lovable some platforms like tempo won t charge for bug fix prompts to alleviate this 70 still it s good to keep an eye on usage dashboards when in doubt ask for help or search the community vibe coding is new and you may run into an issue where you re not sure if it s your prompt or the tool s fault the good news communities are forming around each of these platforms discord servers forums subreddits like r vibecoding if you hit a wall say the ai just isn t producing the feature you want chances are someone else encountered a similar challenge don t hesitate to ask has anyone gotten x to work in tool y often another user or the devs will have guidance maybe a special syntax or a workaround prompt this human layer of support can complement the ai s assistance maintain a learning mindset if you re new to programming vibe coding is a fantastic gateway but if your goal is to eventually build more complex or production grade systems treat each ai interaction as a learning opportunity when the ai fixes a bug read the diff if you can and try to understand the change when it outlines a plan absorb the rationale over time you ll start picking up programming concepts and patterns one potential downside of relying solely on ai is skill atrophy if you never challenge yourself to understand the code you won t grow your own abilities 102 103 to counteract that take moments to review or even manually tweak small parts of the code you might try writing a tiny function yourself and see if the ai accepts it this keeps you in the loop and helps you become a better builder remember vibe coding should empower you not make you complacent as i argued in vibe coding is not an excuse for low quality work you ...