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route","\u002Fthank-you",{},"data\u002Fshared\u002Furls","P27xKEauu8D-8sfyr0wR4giF0teFSaCuAQ8kgcICQdI",{"id":590,"title":591,"author":592,"authorPhoto":593,"authorPhotoAlt":594,"authorSlug":595,"body":596,"buttonText":847,"buttonUrl":594,"category":848,"date":849,"description":850,"draft":851,"editorsPick":851,"extension":852,"featured":851,"image":853,"imageAlt":594,"meta":854,"navigation":20,"ogImage":594,"ogImageAlt":594,"path":855,"seo":856,"stem":857,"tags":594,"__hash__":858},"blog\u002Fblog\u002Fandrey-gavrilenko-ai-summit.md","No code? No problem: Andrey Gavrilenko shows how to break into Data Science with just English and an LLM","The Pieces Team","https:\u002F\u002Fstorage.googleapis.com\u002Fpieces-marketing-website\u002Fimages\u002Fblog\u002Fdevops-platforms\u002Fauthor.png",null,"the-pieces-team",{"type":597,"value":598,"toc":838},"minimark",[599,603,606,609,612,615,618,623,634,643,646,649,652,655,662,665,668,674,678,681,689,694,697,700,722,725,728,731,735,738,741,744,747,750,753,757,766,769,772,775,779,782,785,788,791,794,811,814,818,821,830,833],[600,601,602],"p",{},"In a session that raised eyebrows and sparked plenty of Slack DMs, technical speaker Andrey Gavrilenko laid out a compelling,and surprisingly practical, case for becoming a data scientist without writing a single line of code.",[600,604,605],{},"His argument?",[600,607,608],{},"You don’t need to be a Python wizard anymore.",[600,610,611],{},"All you need is English and access to a solid large language model.",[600,613,614],{},"The talk, delivered as part of a developer-focused AI summit, raised a question that’s top-of-mind for a growing segment of tech newcomers and non-technical founders: Can LLMs replace traditional code workflows for data science?",[600,616,617],{},"Andrey says yes, at least to get started.",[619,620,622],"h2",{"id":621},"ai-powered-data-science-no-code-required","AI-powered Data Science – no code required",[600,624,625,626,633],{},"Ten years ago, Andrey got his start in data science through an Andrew Ng course. Now, he says, we’re living in a world where ",[627,628,632],"a",{"href":629,"rel":630},"https:\u002F\u002Fpieces.app\u002Fblog\u002Ffuture-of-ai",[631],"nofollow","AI is becoming as fundamental"," as electricity.",[600,635,636,637,642],{},"And, for those who understand ",[627,638,641],{"href":639,"rel":640},"https:\u002F\u002Fpieces.app\u002Fblog\u002F10-prompt-engineering-best-practices",[631],"how to ask the right questions",", that world no longer requires code.",[600,644,645],{},"LLMs like ChatGPT and Claude are unlocking the ability to perform complex data workflows with nothing more than natural language.",[600,647,648],{},"That means anyone, from startup founders and PMs to high school students, can run exploratory data analysis, build MVPs, and surface insights, all by typing what they want.",[600,650,651],{},"But this new frontier has its limits. Prompts can be misinterpreted. Results may vary. And if you’re piping sensitive data through a public API, there are real risks.",[600,653,654],{},"For larger datasets, there’s also the constraint of limited memory – most models can’t process huge volumes of information at once.",[600,656,657],{},[658,659],"img",{"alt":660,"src":661},"","https:\u002F\u002Fstorage.googleapis.com\u002Fpieces-marketing-website\u002Fimages\u002Fblog\u002Fandrey-gavrilenko-ai-summit\u002Fimg-001.png",[600,663,664],{},"Slide deck from Andrey’s presentation covering why less coding is required for Data Science.",[600,666,667],{},"Still, Andrey’s message was clear:",[669,670,671],"blockquote",{},[600,672,673],{},"“This changes who gets to build. It’s no longer about knowing Python – it’s about knowing what to ask.”",[619,675,677],{"id":676},"from-web-summit-to-real-world-insights","From Web Summit to real-world insights",[600,679,680],{},"To prove his point, Andrey walked the audience through an analysis of a real dataset from Web Summit 2023 in Lisbon.",[600,682,683,684,688],{},"It included ",[685,686,687],"strong",{},"information on over 2,700 startups",", including descriptions, categories, and growth stages.",[600,690,691],{},[658,692],{"alt":660,"src":693},"https:\u002F\u002Fstorage.googleapis.com\u002Fpieces-marketing-website\u002Fimages\u002Fblog\u002Fandrey-gavrilenko-ai-summit\u002Fimg-002.png",[600,695,696],{},"screenshot from Andrey’s presentation showcasing records from Web Summit startups",[600,698,699],{}," Using ChatGPT, he:",[701,702,703,707,710,713,716,719],"ul",{},[704,705,706],"li",{},"Cleaned duplicates and missing values",[704,708,709],{},"Analyzed stage distribution (Alpha, Beta, Growth)",[704,711,712],{},"Surfaced top categories like AI and SaaS",[704,714,715],{},"Ran comparisons across countries",[704,717,718],{},"Explored pitch deck availability",[704,720,721],{},"Broke down support partners",[600,723,724],{},"All of it, visuals included, was generated with prompts, not scripts.",[600,726,727],{},"What would typically take hours of Python took minutes in natural language.",[600,729,730],{},"It wasn’t flawless, at one point, the model miscounted country totals but it worked well enough to validate the approach.",[619,732,734],{"id":733},"getting-even-deeper-category-extraction-and-web-scraping","Getting even deeper: category extraction and web scraping",[600,736,737],{},"Andrey didn’t stop at basic EDA. He asked the model to infer multiple categories per startup, based on descriptions.",[600,739,740],{},"The results were mixed: the LLM surfaced secondary categories but lacked consistency across the full dataset.",[600,742,743],{},"His fix?",[600,745,746],{},"Break the task into smaller chunks or offload it to a locally run script.",[600,748,749],{},"Naturally, the model offered to write that script too, automatically generating Python code to scrape metadata from startup websites.",[600,751,752],{},"In under two minutes, it returned enriched data from five sites.",[619,754,756],{"id":755},"how-it-actually-works-under-the-hood","How it actually works under the hood",[600,758,759,760,765],{},"To unpack the architecture behind this magic, Andrey walked through the role of the ",[627,761,764],{"href":762,"rel":763},"https:\u002F\u002Fpieces.app\u002Fblog\u002Fmcp",[631],"Model Context Protocol"," (MCP), a growing standard in AI infrastructure.",[600,767,768],{},"MCP connects AI agents to tools like calendars, databases, and design platforms using a secure, shared protocol.",[600,770,771],{},"In this flow, the user gives a prompt, the AI agent interprets it, and MCP bridges the gap to the actual tools needed to execute the task.",[600,773,774],{},"It’s a way to plug natural language into real-world software systems.",[619,776,778],{"id":777},"vibe-coding-the-cool-and-the-caution","Vibe coding: the cool and the caution",[600,780,781],{},"Andrey acknowledged the hype around “vibe coding” – the idea of building software by prompting AI tools rather than writing code.",[600,783,784],{},"While the concept was popularized by former Tesla AI director Andrej Karpathy, Andrey pushed for a more responsible approach.",[600,786,787],{},"“There’s a dark side,” he said. “Lost work, security gaps, rogue agents making unintended changes. You can’t just fire off prompts and hope for the best.”",[600,789,790],{},"His advice?",[600,792,793],{},"Follow a few best practices:",[701,795,796,799,802,805,808],{},[704,797,798],{},"Use version control to catch changes",[704,800,801],{},"Ask your agent to explain itself",[704,803,804],{},"Use trusted MCP servers only",[704,806,807],{},"Choose LLMs that are reliable and benchmarked",[704,809,810],{},"Create rules and use hint files to guide behavior",[600,812,813],{},"One feature Andrey highlighted was Goose’s .gooseignore – a file that blocks the AI from accessing sensitive areas, like test environments or secret keys.",[619,815,817],{"id":816},"ai-as-teammate-not-replacement","AI as teammate, not replacement",[600,819,820],{},"Andrey closed with a message of balance. Language models are changing the game but they’re not magic. You still need core knowledge of programming, data theory, and how systems work.",[600,822,823,824,829],{},"Tools like Pieces for Developers, he noted, are helping with ",[627,825,828],{"href":826,"rel":827},"https:\u002F\u002Fpieces.app\u002Ffeatures\u002Flong-term-memory",[631],"long-term context management",", enabling more advanced workflows while still grounding users in technical fundamentals.",[600,831,832],{},"“We’re in the early innings,” he said.",[669,834,835],{},[600,836,837],{},"“But the opportunity is massive. Just by knowing English and having access to a strong LLM, you can do a lot. The next step is learning how to build safely and smartly.”",{"title":660,"searchDepth":839,"depth":839,"links":840},2,[841,842,843,844,845,846],{"id":621,"depth":839,"text":622},{"id":676,"depth":839,"text":677},{"id":733,"depth":839,"text":734},{"id":755,"depth":839,"text":756},{"id":777,"depth":839,"text":778},{"id":816,"depth":839,"text":817},"Get started","Insights","2025-05-13T00:00:00.000Z","Break into data science with just English and an LLM. 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